Portraits of Gentrification: When Neighborhood Change Becomes News

Zawadi Rucks Ahidiana

A dissertation submitted in partial satisfaction of the

requirements for the degree of

Doctor of Philosophy

Sociology

in the

Graduate Division

of the

University of California, Berkeley

Committee in charge:

Professor Claude Fischer, Co-chair Professor Margaret Weir, Co-chair Professor Sandra Smith Professor Carolina Reid

Summer 2018

Abstract

Portraits of Gentrification: When Neighborhood Change Becomes News

Zawadi Rucks Ahidiana

Doctor of Philosophy in Sociology

University of California, Berkeley

Professor Claude Fischer, Co-chair

Professor Margaret Weir, Co-chair

The term gentrification was coined in the mid-1960s to describe the process by which neighborhoods were changing from predominately low-income to middle-class. While the term has expanded in usage in the academy since then, we know little about what gentrification means in its every day use and how that might vary depending on city size, demographic composition, and housing and labor market conditions. In this study, I investigate the representations of gentrification by one cultural institution, the media, to understand the depictions that contribute to public opinions, attitudes, and assumptions about what the term means, who is affected, what is driving the change, and how those representations vary by context. Using data from 4 newspapers published in Baltimore, Maryland and San Francisco, California between 1990 and 2014, as well as Census data, I found that the news media replicates and reinforces racial and class hierarchies in its representations of gentrification by reflecting the patterns of uneven (re)development of the past and present, and reinforcing stereotypes of racial and class groups.

How gentrification was framed in the news unfolded through three mechanisms that are embedded in reporting. The news media associated race and class with gentrification through descriptions of neighborhood residents and recent in-movers, categorized certain types of neighborhood change as gentrification, and spun the changes as positive, negative, or mixed. All three of these mechanisms were shaped and influenced by the racial and class demographics of the gentrifying neighborhood and the larger context of race, class, and space of the surrounding city.

Despite distinct racial and class demographics, the Baltimore and San Francisco articles represented gentrification in similar ways. Gentrification was frequently associated with poor and black neighborhoods in articles from both cities. Changes in poor and black neighborhoods that were categorized as gentrification were most often about new and state-led development and given a more positive spin by the journalists and their sources. In contrast, residential and

commercial changes were most often categorized as gentrification for working-class and white ethnic neighborhoods in Baltimore, and diverse and Latino neighborhoods in San Francisco and presented with a negative spin. These differences reflect both the history and current patterns of (dis)investment by racial and class demographics in the cities and the influence of racial and class-based stereotypes on the opinions of journalists and their sources. That is, poor and black neighborhoods have historically experienced less investment in infrastructure and amenities, which have made them spaces that need some form of structural investment. However, most modern-day processes of residential gentrification by which developers and higher income homebuyers invest in a community are not occurring in high poverty and majority black neighborhoods, but are happening in working-class and white ethnic neighborhoods in Baltimore and Latino and diverse neighborhoods in San Francisco. Thus, new development funded by and implemented by the City was more frequently occurring in poor and black neighborhoods. The actual patterns of (dis)investment and (re)development reinforce common stereotypes about poor and black neighborhoods as blighted, high in crime, and high in poverty.

These findings demonstrate how the historical patterns of investment and decline by racial and class composition influence how neighborhood change is understood today. The neighborhoods we see as blighted, disinvested, and in decline are frequently the same neighborhoods that have been purposefully overlooked and ignored by developers, banks, city governments, and homebuyers. The differences in how gentrification was interpreted and spun in the media representations studied here suggest that policy responses to gentrification are likely to vary by the racial and class demographics of the affected neighborhoods, meaning that residents of some neighborhoods are more likely to experience protection than others. Thus, we are likely to see more demolishment of homes and continued large-scale dispersal of poor and black communities under the guise of “investment,” while residents of working-class, white, and diverse neighborhoods are more likely to be protected from having to leave their homes.

Table of Contents

Acknowledgements………………………………………………………………………………………………………………… ii

Chapter 1: Constructing Narratives of Neighborhood Change: The News Media’s Role in Defining Gentrification …………………………………………………………………………………………………………… 1

Chapter 2: The Cases …………………………………………………………………………………………………………..… 18

Chapter 3: Who is Gentrified? Who is Gentrifying?: Race and Class Associations …………………. 31

Chapter 4: Gentrification of Some Other Neighborhood Change: Categorization ………………….. 48

Chapter 5: Gentrification as Improvement, Gentrification as Harm: Spin …………………………….… 64

Chapter 6: Summary and Implications …………………………………………………………………………………… 82

References …………………………………………………………………………………………………………………………….. 90

Appendix A: Race and Class Demographics Over Time …………………………………………………………. 102

Appendix B: Coding for Association ……………………………………………………………………………………… 104

Appendix C: Coding for Concerns and Benefits ……………………………………………………………………. 106

Acknowledgements

It took a village to produce the pages before you, so I’d like to take some space to properly acknowledge all those who made this journey possible.

None of this would have been possible without my family. My rock, Montaigne, left his lifetime home of New York to let me follow my dream. He’s had my back in every step along the way, always there to pick me up and remind me that I could do this. My mother, Anayezuka, was there for every step along the way to cheer me on, support my personal and professional moves, and remind me how proud she is to be “Zawadi’s mom.” My father, Mack, who we moved closer to in coming to Berkeley, was a constant reminder of home and a great source for original jazz. Monte cannot possibly understand how much he has motivated me and may not fully grasp his contributions until he has a child of his own. It was his birth that pushed me forward full force despite the delays and challenges of data collection. Monte’s “aunties” Elena Spitzer, Nancy Rosas, and Traci Sanders have been the best friends along the way despite distance, busy schedules, and a new baby. Finally, my sisters Monica and Tahllia, brother Najee, second dad Renard, step-mom Michelle, mother-in-laws Margareth and Linda, aunt-in- laws Mireille and Evelyne, and sister-in-law Jennie all cheered me on from the east coast.

I wouldn’t have even thought to apply to a Ph.D. program without a number of key mentors and role models. Core to my trajectory to graduate school was my prior work in evaluation, which was my first exposure to research. As my mentor at MDRC, Alissa Gardenhire pushed me on my educational goals and made me seriously consider a Ph.D. instead of stopping at a Master’s. Donna Wharton-Fields, Frieda Molina, and Nandita Verma encouraged my growth and development in research and advocated for me to get new opportunities to learn and apply my skills. Alissa Gardenhire, Jim Riccio, Lashawn Richburg-Hayes, Nandita Verma, and others served as role models for what I might get out of Ph.D. program. Finally, I was lucky enough to make some amazing friends during my 6 years at MDRC including my work wife, Nancy Rosas, who knows me like the back of her hand, and LaFleur Stephens-Dougan who I’ve been lucky enough to get advice and support from at every point in my graduate school process.

At the Community College Research Center, I had the pleasure of working with an amazing team of women who inspired and motivated me. Nikki Edgecombe, Melinda Mechur Karp, and Shanna Smith Jaggars gave me the opportunity to be a first author on a paper, gave me countless rounds of feedback, and were amazing role models and mentors. Rachel Hare Bork, my CCRC work wife, made the hard days tolerable and pushed me on my grad school applications to make sure they saw my best me. Sue Bickerstaff and Melissa Barragan were brilliant co-authors and colleagues. I am so glad to have had the opportunity, albeit short, to join the CCRC family.

Finally, there were several people outside of work who saw what I was capable of before I could even see it in myself. My life coach, Susan Carroll-Berck, pushed me professionally and academically to pursue bigger things. At NYU, Ellen Schall and Angela Hendrix Terry saw how I

was holding myself back with negative thinking and pushed me to stop being my own worst enemy, without which I would not have survived graduate school. David Schacter gave me the space and exercises to figure out that my next step was a Ph.D. in Sociology. Finally, Colleen Gillespie, Erica Foldy, Ingrid Ellen, Kathy O’Regan, and Lisette Garcia all gave me invaluable advice about graduate school and supported my decision to leave the world of policy.

When I got to Berkeley, I was lucky enough to find an amazing group of friends along the way. I don’t know if this process would have been possible without the camaraderie and support of my grad school friends. When I was miserable during qualifying exams, they understood my struggle and pushed me to the finish. When I had those rare moments of success, they celebrated with me. I have ended this process a whole and healthy human being thanks in part to them. Shelly Steward was the first Berkeley student I met after accepting the offer at the ASA conference in Denver and I couldn’t have asked for a better first friend! My cohortmates Gill Gualtieri, Esther Cho, Jess Schirmer, Michaela Simmons, and Paul Chung made less inviting classrooms tolerable and formed the basis of my writing groups, accountability buddies, and support systems throughout the years. I found an unlikely bestie in Gill despite a 10-year age difference. She has been my support, advisor, cheerleader, and reviewer even from across the country, always ending our weekly check-ins with “I believe in you!” Outside of the fierce 10 of 2012, I was lucky enough to connect with a number of amazing people through the Sociologists of Color and Allies (SoCA), which made it easy to meet other graduate students of color across cohorts. Angela Fillingim, Jessica Compton, and Kristen Nelson became my sistas in the struggle through SoCA, always lending an ear when I needed one. Véronique Irwin was a wonderful friend, co-organizer, and gym buddy. Nora Broege supported me through pregnancy, motherhood, and the challenges of balancing parenting and academic life. Sarah MacDonald and Michel Estefan provided sage advice on the program and the classroom, and shared parenting stories. And my Irvine buddy Alyse Bertenthal was a source of constant support and commiseration as we underwent parallel paths in our personal and professional lives.

Finally, I have been lucky enough to have friends who have undertaken a Ph.D. before me and been there along my journey with sage advice. Jacob Faber, LaFleur Stephens-Dougan, Liz Everton, Nicolette Bruner Olson, and Rachel Hare Bork have generously shared their graduate school experiences and given me invaluable advice about applying to grad school, getting through qualifying exams, applying to fellowships, and going on the job market.

Now to those who made the pages written here actually happen. My Dream Team Committee, Claude Fischer, Margaret Weir, Sandra Smith, and Carolina Reid, made this all possible. Claude, you helped me find the tools to make my idea happen whether in solidifying a research question, modifying the research design due to some unforeseen bump in the road, or giving every single chapter a close read with detailed feedback. You’ve impacted my academic life in more ways than you know. I will always be grateful I was able to take your final writing seminar, which turned out to be the most useful course I took in grad school. Thank you for your wisdom and time.

iii

Margaret, I should have known right away that you would end up being an important part of my grad school journey given all the important Margarets in my life. Thank you for pushing my thinking on each of my projects to get me to the forest and out of the weeds, reminding me of my focus when I have been distracted, and being consistent support even after you left Berkeley. You have challenged me to think about my research in ways that aren’t my natural inclination and helped me figure out my process for research.

Sandra, I can’t thank you enough for all of your encouragement and support. Even when you weren’t directly involved in my research as with my MA paper, I could always count on you for honest and direct feedback on my ideas and direction. Thank you for believing in my research and seeing beyond the mess on the page to what my contributions could be.

Carolina, I am so thankful for your support on this dissertation. While most of my colleagues have outside committee members who barely respond or provide input, I could always count on your response with feedback that was both encouraging and critical. Thank you for always being positive and reminding me of my roots in urban policy.

In addition to my dream team, I have benefitted from the mentorship and guidance of Ann Swidler, Cristina Mora, Cybelle Fox, David Harding, Larry Rosenthal, Mara Loveman, and Raka Ray. I am particularly in debt to Cybelle Fox for her wisdom on archival research and document analysis, and her emotional support during some of the harder periods of graduate school. Cybelle, you were my mentor in grad school, whether you knew it or not.

I’ve also greatly benefited from my relationships with the people who make the Sociology department run smoothly who helped me navigate the bureaucratic systems at Berkeley and figure out the next steps in the process. To Anne Meyer, Carmen Privat-Gilman, Carolyn Clark, Rebecca Chavez, and Tamar Young, I owe you each for your help and support along the way. Thank you for keeping your door open, easing my mind about the next steps, hearing my ideas, and generally making sure that my departmental life went smoothly. A special thank you for Tamar for keeping me laughing even when I wanted to cry.

A special thank you to the research support provided by the D-Lab! Nora Broege kept me from poking my eyes out when dealing with text in Stata. Jon Stiles helped me navigate Census and ACS data. Patty Frontiera showed me some cool new mapping tricks. Susan Grand gave me a corner to hide in with a smile and a hug. And Quinn Dombrowski helped me figure out that OCR was too much to undertake before I needed to file.

Lastly, I’d like to thank the funders who made my dissertation research possible. Over the last 6 years, I’ve been lucky enough to have the support of the Cota Robles Fellowship, the Social Science and Policy Forum Summer Institute of Inequality, the Mentored Research Award, the Student Mentoring and Research Teams Program, the Institute for the Study of Societal Issues (ISSI) Graduate Fellows Program, the Bendix Fellowship, and the American Association of University Women. I am particularly grateful for the opportunities to be a part of the Summer

Institute of Inequality and the Graduate Fellows Program at ISSI. Tom Sugrue, John Skrentny, and my colleagues Alyse Bertenthal, Courtney Boen, Devin Fernandes, Fiona Chin, Max Hell, Mike Zabek, Sam Plummer, Vittorio Merola, and Wendell Adjetey provided invaluable feedback on my Master’s research which was instrumental in the development of my dissertation, while connecting me with an interdisciplinary group of up-and-coming scholars of inequality. In the Graduate Fellows Program, I got invaluable support and feedback from Christine Trost, David Minkus, Deborah Lustig, and my cohortmates Cynthia Ledesma, Esther Cho, Hector Beltran, Jen Smith, Kelechi Uwaezuoke, and Melody Tulier. They read countless drafts of dissertation related research and job market materials, as well as sitting through multiple iterations of my job talk to help me put my best foot forward on campus interviews. I hope that someday I can recreate even a third of the support that the Graduate Fellows Program has given me.

While not a funder of this project, I would also like to thank UC Berkeley’s Student Mentorship and Research Training (SMART) program and the Undergraduate Research Program (URAP) for supporting my dissertation research for 6 semesters. SMART and URAP gave me the opportunity to train and mentor undergraduates, which made dissertating less lonely. I am especially thankful for the space Linda von Hoene and Sabrina Soracco provided to think about how to develop a mentoring relationship. I am eternally grateful to the 52 students who helped me compile data for my dissertation: Aakash Vashee, Allan Nava, Allison Kim, Amanina Shofry, Amena Jannat, Ana Choc, Arjun Gadkari, Brieanna Martin, Catherine Pham, Ceci Vu, Chris Soria, Dominique Fernandez, E’Niyah Wilson, Eli Ward, Emilio Flamenco, Emily Valdez, Gurpreet Gill, Hannah Cho, Hanzhi Zhang, Heather Tran, Irene Varea, Isabella Farinelli, Jamila Cervantes, Javier Rara, Katherine Lazalde, Katherine Sheng, Lucy Tang, Luisa Camacho, Mai Tran, Marie Kim, Micaela Romero, Michael Sillers, Nathan Park, Nirvana Felix, Noelle Atkins, Pilar Montenegro, Qing Bao, Raana Mohyee, Rachel Miller, Robin Pyo, Sander Lutz, Savannah Schoelen, Seamus Kirkpatrick, Shalita Williams, Siedah Morrish, Simon Zhu, Simrjot Mahal, Sinporion Phuong, Steven Au, Sylvia Longworth, Synclaire Butler, Taheerah Mujahid, Thea Matthews, and Zoe Reier. I’d especially like to thank Taheerah Mujahid for being my guinea pig as my first undergraduate mentee; Amanina Shofry and Javier Rara for helping me develop the microfilm protocol; Steven Au for developing formulas to simplify data entry for the team; Nirvana Felix for returning to the team after graduating to continue contributing to the project; and Amanina Shofry, Chris Soria, Javier Rara, Noelle Atkins, Pilar Montenegro, Raana Mohyee, Sinporion Phuong, Sylvia Longworth, and Thea Matthews for serving as Team Leads. Finally, Cynthia Green and Sally Lawton helped me collect microfilm in Baltimore.

I dedicate this dissertation to my maternal grandmother, Margaret Pierce Dent, who graduated second in her class at law school at a time when women couldn’t be secretaries in law firms. She was a determined and stubborn woman whose professional and personal story inspired me as a teen. While she passed before I finished my Bachelor’s degree, her story gave me the inspiration and strength to pursue a career path where I would always be underrepresented, sometimes be unheard, and, for some, be unwanted.

Chapter 1: Constructing Narratives of Neighborhood Change: The News Media’s Role in Defining Gentrification

Cross Street used to be one of the city’s busiest markets, but conversations with some longtime tenants—Steve of Steve’s Lunch and the lady who runs Big Jim’s Deli—and even newer arrivals affirmed that customer traffic has steadily dwindled. There are times the market still rocks, like game days at the nearby stadiums, but overall business is down. Vendors blame it on gentrification. As Formstone came down and roof decks went up, the blue-collar backbone of South Baltimore morphed into white-collar professionals who work, and apparently shop, elsewhere.

- Excerpt from “Cross Street Market – Cheap Eats” published March 6, 2013 in the Baltimore City Paper

When you think of gentrification, the process by which a neighborhood changes from predominately low-income residents to middle-class, the neighborhoods of Baltimore, Maryland are probably far from the first that come to mind. Yet, neighborhoods in Baltimore City have been undergoing gentrification since as early as the 1980s. While the literature on gentrification has predominately focused on New York City (Barton, 2016; DeSena, 2009; Freeman, 2006; Hyra, 2006, 2008; N. Smith, 1996; Taylor, 1992, 2002; Timberlake & Johns- Wolfe, 2016; Zukin, 1989) and Chicago (Hwang & Sampson, 2014; Pattillo, 2008; Timberlake & Johns-Wolfe, 2016; W. J. Wilson & Taub, 2011), moderate and small sized American cities have been undergoing change driven by the middle-class’ return to city living and city officials’ efforts to attract new residents and businesses through redevelopment and incentives. In this study, I focus on one aspect of this gap in the literature: how variations in city size, demographic composition, and labor market conditions affects local representations of gentrification and what “gentrification” means. By studying the representation of gentrification in the news media, I further our understanding of the use of the term “gentrification” in everyday life. I document (1) the differences in how gentrification is represented in a global city and a post-industrial city and (2) how the representations of gentrification reflect and reinforce historical racial and class inequalities. Using newspaper articles from four newspapers published in Baltimore, Maryland and San Francisco, California between 1990 and 2014, I explain the similarities and differences in how the news media represents gentrification that are likely to influence policy responses.

As a cultural institution, the news media plays an central role in what issues are defined as “social problems” (Hilgartner & Bosk, 1988). The news media, including newspapers, television news, news magazines, and radio, presents and represents the world around us in ways that reinforces readers’ common understandings based on personal experiences and insight from their social circles, and provides new information through which readers develop opinions on issues with which they have no experience (Eschholz, Chiricos, & Gertz, 2003; Gamson, 1988; Gamson & Modigliani, 1989; Hallin & Mancini, 1984; Hester & Gibson, 2007; Sacco, 1995).

While representations in the news media are only one factor that influences public opinions and attitudes, the news media plays a more influential role in what social issues readers think about and which they overlook (Altheide, 2000; Andsager, 2000; Bleich, Bloemraad, & De Graauw, 2015; Briggs & Hallin, 2007; Cappella & Jamieson, 1997; Eschholz et al., 2003; Gamson, 1988; Gamson & Modigliani, 1989; Gilens, 1996; Gitlin, 2003; Hester & Gibson, 2007; Sacco, 1995; Schudson, 1982). Thus, whether gentrification is acknowledged as a social issue by city residents and politicians is in part based on whether the news media covers the issue.

This study documents the news coverage of gentrification in two cities to answer the question: How does the news media represent gentrification? Central to my findings is that because the news media as an institution is embedded in the broader social context, news representations replicate and reinforce racial and class hierarchies (Binder, 1993; Chavez, 2013; Dávila, 2008; Earl, Martin, McCarthy, & Soule, 2004; Entman & Rojecki, 2001; Gilens, 1996; Gray, 2013; Hall, 1997; Kendall, 2011; Schudson, 2002). Because gentrification is a place-based process, the news media representations studied here are influenced by the relationship between racial and class hierarchies and urban development. Poor and black neighborhoods were targeted for bulldozing through urban renewal in the 1950s and 1960s (Hartman, 2002; Hirsch, 1993; Kusmer & Trotter, 2009; Sugrue, 1996). Public housing was built in predominately low-income neighborhoods to maintain racial and class segregation (Hirsch, 1993; Stoloff, 2004; Sugrue, 1996). And real estate and mortgage lending practices legally kept white neighborhoods white and black neighborhoods black (Pietila, 2010; Rothstein, 2017; Sugrue, 1996), a practice that continues to have repercussions for patterns of investment and segregation today (Faber, 2018; Rugh & Massey, 2010). Urban development has created a landscape that varies in zoning, concentration of poverty, and proximity to resources and amenities based on racial and class demographics, which in turn affects where gentrification is taking place and how it is unfolding. These differences in where and how gentrification occurs is then reflected in media representations. Thus, I found that gentrification in black neighborhoods was more likely to be associated with state-led development and new development, while gentrification in white, Latino, and diverse neighborhoods was more likely to be residential or commercial development and change.

To understand how the news media replicates and reinforces the racial and class hierarchies, I analyzed how race and class were represented in the news about gentrification, how race and class demographics were associated with the kinds of change categorized as gentrification, and how race and class influence whether gentrification was presented as a beneficial or harmful change. The results contribute to the fields of culture and urban sociology by documenting the common understandings of gentrification, the process by which race and class hierarchies are reproduced through the news media, and how race and class hierarchies continue to contribute to inequalities in (re)development and neighborhood change.

How the News Media Frames Gentrification

The chapters that follow document what the news media contributed to local understandings of gentrification and how those representations reflected and reinforced Americans’ common assumptions about neighborhood desirability based on racial and class demographics. How gentrification was framed unfolded through three mechanisms embedded in reporting: categorizing, associating, and spinning. The news media categorized a change in a neighborhood as gentrification, associated race and class with the process by describing the stakeholders involved, and spun the change as positive, negative, or mixed for those affected. The kind of representation these mechanisms produced was informed by the race and class demographics of the affected neighborhood and the position of those characteristics in the social hierarchy, as described further below.

Categorization

The term gentrification was rarely defined in the newspaper articles. In fact, only 11 articles in 950 (0.01 percent) included an explicit definition of what kind of change “gentrification” referred to. Instead, newspaper articles presented a change that was happening in a neighborhood and categorized it as gentrification through labeling or applying the term gentrification to describe what was occurring in that neighborhood. Thus, certain types of changes happening in certain neighborhoods were categorized as gentrification rather than redevelopment, revitalization, urban renewal, or some other descriptor. Race and class influenced categorization because the kinds of changes neighborhoods were experiencing varied by their racial and class demographics. That is, the newspaper articles reflected the uneven development both cities were experiencing by middle- and upper-class in-movers, developers, businesses and the government along dimensions of race and class. Thus, while other mechanisms like spin reflected the assumptions and biases triggered by the race and class compositions of the neighborhoods affected, categorization reflected the realities that developers were more likely to build new housing in neighborhoods that guaranteed a return on investment and that middle- and upper-class in-movers were more likely to move to white or Latino neighborhoods than black or Asian neighborhoods (L. Bobo & Zubrinsky, 1996; Charles, 2006; Farley, Steeh, Krysan, Jackson, & Reeves, 1994; Quillian, 2002).

Association

In describing the changes in the gentrifying neighborhoods, journalists wrote about key stakeholders involved in the process including neighborhood residents, recent in-movers, business owners, developers, real estate agents, government officials, and nonprofit representatives. Descriptions of neighborhood residents and recent in-movers often included class and racial descriptions, which associated race and class with the dynamics of gentrification. In this way, the articles presented readers with an explicit image of who was affected by gentrification in varied neighborhoods. Specifying the race and class demographics of who lived in a neighborhood and who was moving in allowed readers to connect the process of gentrification to their commonly held stereotypes and biases about people of those race and class demographics.

Spin

Finally, newspaper articles offered opinions about whether the changes that were occurring in the gentrifying neighborhood were positive or negative. In fact, the majority of articles across both cities included both positive and negative opinions about gentrification. Together, these opinions provided a spin about whether gentrification is a positive, negative, or mixed change for those affected. While association relies on the readers’ stereotypes and assumptions about the race and class demographics portrayed, spin relies on the journalist’s and their sources’. That is, whether gentrification was spun as a positive, negative, or mixed change was affected by the race and class demographics of the neighborhood affected because of racial and class stereotypes and assumptions that influenced the opinions and attitudes of journalist’s and their sources.

The Social Construction of Meaning

The process by which an idea, object, or phenomenon becomes identified and labeled by society is the process of social construction (Gamson, 1988; Hall, 1997; Hilgartner & Bosk, 1988). Through social construction, words are linked to meaning (Hall, 1997). While this includes linking a word to what it refers to, this also includes linking that word to connotations about that word (Hall, 1997). The process of social construction is one that involves individuals, groups, and institutions as how a word is connected to an idea, object, or phenomenon and what that connotes must be decided on and distributed. The word “Hispanic,” for instance, was created in the U.S. to refer to individuals of Latin American descent by Census officials and nonprofit leaders (Mora, 2014). Through Spanish language media, the idea that people of Latin American descent should identify as Hispanic was disseminated to Mexican, Puerto Rican, Cuban, and other Latin American communities (Mora, 2014). As the use of the term by the community increased, Americans began associating that label with certain characteristics, largely building on stereotypes of Mexican-Americans and reinforced by news media representations of Hispanics (Chavez, 2013; Dávila, 2008). While institutions like the government and nonprofits are not always involved, the role that the media played in the example of constructing Hispanic is common in the construction, dissemination, and reinforcement of meaning (Chavez, 2013; Dávila, 2008; Eschholz et al., 2003; Gamson, 1988; Gamson & Modigliani, 1989; Hall, 1997; Hallin & Mancini, 1984; Hilgartner & Bosk, 1988; Hudson & Martin, 2010; Sacco, 1995; Schudson, 1982, 2002).

In fact, many argue that the news media’s role as a cultural institution is to construct and reinforce meaning through the (re)presentation of social issues and events (Altheide, 2000; Andsager, 2000; Bleich et al., 2015; Briggs & Hallin, 2007; Chavez, 2013; Gamson, 1988; Gamson & Modigliani, 1989; Gitlin, 2003; Hall, 1997; Hallin & Mancini, 1984; Hilgartner & Bosk, 1988; Hudson & Martin, 2010; Sacco, 1995; Schudson, 1982, 2002). The news media defines what social issues their readers and viewers should care about, identifies the actors in those social issues, and presents perspectives on the issues, usually with pro and con sides (Dávila, 2008;

Gamson & Modigliani, 1989; Gans, 2004; Gitlin, 2003; Hester & Gibson, 2007; Hudson & Martin, 2010; Schudson, 1982). Through their use of language which has a preexisting connection to assumptions and stereotypes, the media connects the stereotypes that readers hold with new issues and events (Chavez, 2013; Gray, 2013; Hall, 1997; Schudson, 2002). Furthermore, despite a commitment to objectivity (Gamson, 1988; Gamson & Modigliani, 1989; Gans, 2004; Gilens, 2009; Gitlin, 2003; Hallin & Mancini, 1984), the media can bias readers towards one side of the issue or another by unequal coverage, use of experts on only one side of an issue, and limiting perspectives on the issue to only two opinions (Gamson, 1988; Hudson & Martin, 2010). Through this process, the media constructs a social issue and raises its profile to be of note to its readers and viewers (Schudson, 1982).

In fact, the prior literature suggests that one of the most important things the news media does is to present certain frames on an issue (Andsager, 2000; Binder, 1993; Cappella & Jamieson, 1997; Entman, 1993; Gamson, 1988; Gamson & Modigliani, 1989; Gitlin, 2003; Hilgartner & Bosk, 1988; Kendall, 2011). As Gitlin describes, “Frames are principles of selection, emphasis, and presentation composed of the tacit theories about what exists, what happens, and what matters” (2003, p. 7). These patterned accounts that organize information facilitate interpretation by readers and viewers and focus them on certain aspects of the issue (Andsager, 2000; Binder, 1993; Cappella & Jamieson, 1997; Entman, 1993; Gamson, 1988; Gitlin, 2003). Framing is the result of journalists choosing what information to present or exclude and how to present the information included (Andsager, 2000; Binder, 1993; Cappella & Jamieson, 1997; Chavez, 2013; Entman, 1993; Gitlin, 2003; Hilgartner & Bosk, 1988; Schudson, 1982).

Importantly, framing often reinforces common stereotypes (Binder, 1993; Entman & Rojecki, 2001; Gray, 2013; Hall, 1997; Kendall, 2011; Schudson, 2002). Blacks are more commonly represented in news reporting on poverty and crime (Earl et al., 2004; Entman, 1992; Entman & Rojecki, 2001; Eschholz et al., 2003; Gans, 1995; Gilens, 1996, 2009; Soss, Fording, & Schram, 2011), reinforcing stereotypes that blacks are poor, lazy, and violent. Latinos are predominately represented as undocumented immigrants or agricultural workers (Chavez, 2013; Dávila, 2008), reinforcing stereotypes that Latinos are uneducated and “illegal” immigrants. Whites are predominately represented as experts (Voorhees, Vick, & Perkins, 2007), reinforcing stereotypes that whites are hardworking, educated, and predominately middle-class. Finally, the middle-class are represented as the moral high ground of our society (Kendall, 2011). Since framing is particularly effective when it reinforces commonly held stereotypes and assumptions, these representations are more salient to readers (Binder, 1993).

The Context of Gentrification

The case of gentrification is of particular interest for two reasons. First, the news media played a central role in defining gentrification for the general public because the term itself was coined in the academy, as described further below. While there are other social processes I could have studied, I chose gentrification in part because it required an institution to disseminate and

define the term to make the transition from the academy to the vocabulary of the general public. Second, while gentrification is defined as a process of class change, race and class are highly correlated in the United States, particularly when it comes to neighborhood of residence, which suggests that gentrification likely has a racial connotation. The prior literature has begun to explore the role of race in the gentrification process, as outlined below, but we know little about how common stereotypes often reinforced by media portrayals about what racial groups are poor and which are middle-class are reflected in representations and common understandings of gentrification.

The Evolution of “Gentrification”

The term gentrification was coined in the mid-1960s by Ruth Glass (1964), a British sociologist studying the socioeconomic changes neighborhoods in London were experiencing in the 1950s (N. Smith, 1996). She used “gentrification” to describe the changes in the socioeconomic demographics of residents living in several working-class neighborhoods that were becoming predominately occupied by the gentry or middle class (Glass, 1964). The shift in the socioeconomic status of residents was paired with rising land values and the succession of businesses in favor of those catering to the middle and upper classes (Glass, 1964). These neighborhood level changes led to displacement and the working-class found themselves re- concentrated in smaller sectors of the city where they could still find affordable housing (Glass, 1964). While Glass linked the neighborhood level changes in composition to larger changes in the city, she used the term gentrification to specifically describe the process of a neighborhood shifting from predominately working-class to middle-class (Glass, 1964).

Today, this meaning continues to serve as the base definition for gentrification in the academy, which most would agree is the process by which a neighborhood’s residents change from predominately low-income to predominately middle-class. However, the term has been extended to changes that look quite different from the process that Glass (1964) described. For example, some researchers apply the term gentrification to describe new housing developments for the middle-income in previously low-income neighborhoods including state- led development of mixed-income housing (Bridge, Butler, & Lees, 2012; Gomez, 2013; Hyra, 2008; N. Smith, 2002). In addition, the term has been modified or hyphenated to describe the changes related to the residential gentrification process that Glass (1964) described and other related changes. The literature now includes the study of neighborhoods changing from predominately middle-class to predominately upper-class (super- or hyper-gentrification see Centrer (2008) and Lees (2010)), shifts in businesses from catering to low-income to middle- income residents (commercial gentrification see Maurrasse (2006)), student-led gentrification (studentification see D. Smith (2005)), and others.1

Race in the Process of Class Change

1 See Chapter 4 for a more detailed review of this. 6

Even though gentrification is defined as a process of class change, I am particularly interested in how representations of gentrification vary by both race and class because of the presumptions Americans make about class background based on race and vice versa (Charles, 2006; Gilens, 1996, 2009; Sampson, 2012; Sampson & Raudenbush, 2004). Much like assumptions about who is poor (Gans, 1995; Gilens, 1996, 2009; Katz, 1989; Soss et al., 2011), qualitative studies of gentrification have tended to focus predominately on black neighborhoods, especially from the 1990s on (Fallon, 2016). Yet studies of racial residential preferences (L. Bobo & Zubrinsky, 1996; Charles, 2006; Farley et al., 1994; Quillian, 2002) and neighborhood level stereotypes by racial composition (Quillian & Pager, 2001; Sampson, 2012; Sampson & Raudenbush, 2004) suggest that black neighborhoods should be less likely to experience gentrification, particularly if middle-class in-movers are predominately white. Recent evidence supports the idea that the racial hierarchy of the housing market found in the prior literature (L. Bobo & Zubrinsky, 1996; Charles, 2006; Farley et al., 1994; Quillian & Pager, 2001, 2001; Sampson, 2012; Sampson & Raudenbush, 2004) is replicated in the gentrification process.

Most of these recent studies found that gentrification was less likely in predominately black neighborhoods than neighborhoods with other racial demographics (Ellen & O’Regan, 2008; Galster, Quercia, Cortes, & Malega, 2003; Hwang, 2016; Hwang & Sampson, 2014; Owens, 2012; Owens & Candipan, 2018; Timberlake & Johns-Wolfe, 2016). However, the results across neighborhoods of other racial categories varied depending on the geographic scale of the study. Studies of specific cities, which have generally focused on New York City and Chicago, found that neighborhoods with more Latinos had a lower likelihood of experiencing gentrification (Hwang, 2015; Hwang & Sampson, 2014). But studies that use either national data or focus on a larger number of cities finds that Latinos were associated with an increasingly likelihood of experiencing gentrification (Ellen & O’Regan, 2008; Freeman & Cai, 2015; Hwang, 2016; Owens & Candipan, 2018). The results for Asians were similarly varied with some studies showing that with more Asians, the likelihood of gentrification increased (Freeman & Cai, 2015; Hwang, 2015, 2016), and other studies showing that more Asians decreased the likelihood of gentrification (Owens & Candipan, 2018).

Despite the lack of consistent results, these findings suggest a few consensuses in the prior literature about the relationship between race and gentrification. First, race influences when and where gentrification occurs, producing an uneven exposure to the change. Second, gentrification is increasingly occurring in non-white neighborhoods even if the rates at which gentrification occurs in those neighborhoods is lower than that in white neighborhoods (Freeman & Cai, 2015; Hwang, 2016; Owens, 2012). Finally, there is growing evidence that racial change accompanies gentrification, making non-white gentrifying neighborhoods more white (Owens, 2012; Owens & Candipan, 2018; Timberlake & Johns-Wolfe, 2016).

Why Study News Media Representations of Gentrification?

Because the term gentrification was coined in the academy, the news media plays an important role in disseminating and distributing ideas about what gentrification means, looks like, and

why readers should care about it. Through representations, the news media socially constructs a meaning of the term that both reflects and informs individual perspectives and public opinions. Although the news media does not coerce its readership into believing a certain set of views and thus supporting a certain set of policies, readers’ understanding of policy issues is informed by the media they consume, their own personal experiences with the issue, social interactions, and their personality (Eschholz et al., 2003; Gamson, 1988; Gamson & Modigliani, 1989; Hall, 1997; Hester & Gibson, 2007; Sacco, 1995). As one institution that contributes to public opinion, the news media is important to study to understand what they present and represent as a policy issue and the perspectives and debates that they present on that issue. Because of the norm of objectivity that informs the field of journalism, the news media is a place where debates on issues occur even if not all views are represented (Gamson, 1988; Gamson & Modigliani, 1989; Gans, 2004). This is one reason why the field of urban sociology has long included studies of the news media. Studying media representations for the case of gentrification is particularly important because the process could be seen as a natural market process that does not need regulation or as a destructive force that needs to be controlled. Whether voters and politicians see gentrification as the former or the latter defines whether policy responses are introduced to address actual and potential negative outcomes of the process.

News Media and Urban Change

While the study of media is less frequent overall in the urban sociology literature, the field has a strong theoretical perspective on the role that the news media plays in the process of urban change, particularly through newspapers. Building on the theory of Logan and Molotch (1987), most studies assume or find that the news media supports and promotes (re)development efforts. As applied to gentrification, however, the findings have been mixed.

First published in 1976, the theory of the growth machine has been influential on studies on the politics of urban planning and development (Logan & Molotch, 1987; Molotch, 1976). The urban growth machine builds on the theory of C. Wright Mills (1956) to describe the power dynamics of city development (Logan & Molotch, 1987; Molotch, 1976). The growth machine, which includes local businessmen who promote growth, elected officials who benefit from growth through the resources of the business community, and monopolistic business enterprises, promote and encourage urban development as a means to achieve financial profit (Jonas & Wilson, 1999; Logan & Molotch, 1987; Molotch, 1976). Newspapers are specifically connected to the process as a monopolistic business enterprise that profits from the expansion of city residents (Logan & Molotch, 1987; Molotch, 1976). With more city residents, newspapers gain more residents and are able to market that expanding readership to increase their advertising sales (Logan & Molotch, 1987; Molotch, 1976). Thus, the theory posits that newspapers encourage development by presenting development projects in a positive light (Jonas & Wilson, 1999; Logan & Molotch, 1987; Molotch, 1976).

The literature testing the theory has largely 2been studies of the politics of urban development, with more limited scholarship on the role of representation, discourse, and the news media in promoting development (Jonas & Wilson, 1999). Part of this scholarship has emerged in the gentrification literature to investigate the news media’s role as a promoter of gentrification (Brown-Saracino & Rumpf, 2011; Collins, 2018; Gin & Taylor, 2010; Lavy, Dascher, & Hagelman, 2016; Putnam, 2017; N. Smith, 1996; D. Wilson & Mueller, 2004). The studies that test this hypothesis have predominantly studied how specific development projects or gentrification in specific neighborhoods is represented in the news (Lavy et al., 2016; Lees, 1996; Putnam, 2017), but three studies offer a more systematic analysis of how newspapers present gentrification (Brown-Saracino & Rumpf, 2011, p.; Makagon, 2010; D. Wilson & Mueller, 2004). As described below, this and other evidence suggest an unclear role for newspapers in the representation of gentrification.

Makagon (2010) conducted a national level analysis of daily, weekly, and monthly newspapers and news magazines to understand the representation of artists in the gentrification process between 1985 and 2008. His analysis highlights the ways in which the news media represents pioneer gentrifiers like artists in contrast to subsequent gentrifiers (Makagon, 2010). While these depictions describe artists as the in-movers who precede gentrification, Makagon (2010) finds that the news media depicts gentrifying artists as victims of gentrification and often omits discussion of the residents displaced by artists. The results provide insight on the variation in how gentrifiers are (re)presented in the news media, but this limited focus on artists does little to explain the broader meaning and spin given to gentrification overall.

In contrast, Wilson and Mueller (2004) took a broader approach by comparing the representation of gentrifying, potentially gentrifying (e.g., located near gentrifying neighborhoods), and unlikely to gentrify neighborhoods (e.g., high poverty areas) in St. Louis, MO from the city’s largest newspaper between 1980 and 2000. They found that articles about gentrifying and potentially gentrifying neighborhoods were more likely to represent the neighborhood as dying and describe the middle-class as saving the neighborhood, which was not applied to low-income neighborhoods unlikely to gentrify even when considering low- income neighborhoods by racial composition (D. Wilson & Mueller, 2004). The findings suggest that newspapers promote gentrification, supporting evidence from studies of the representation of specific development projects (Lavy et al., 2016; N. Smith, 1996; D. Wilson & Mueller, 2004).

While these findings have been relatively consistent, the studies that have found them have focused on specific types of news coverage. For example, the article described above focused on articles about neighborhoods (D. Wilson & Mueller, 2004). Similarly, Lavy et al (2016) focus on the news coverage of a specific development. What remains unclear from these studies is whether the news media generally presents gentrification in a positive light or whether

2 A Google Scholar search for the Logan and Molotch book Urban Fortunes (1987) finds almost 5,500 citations. 9 gentrification in certain neighborhoods or through certain development projects is presented in a positive light.

These issues are addressed in Brown-Saracino and Rumpf’s (2011) study of articles from 9 newspapers in 7 large cities (New York City, Los Angeles, Chicago, Houston, Philadelphia, San Diego, and Dallas) published between 1986 and 2006. In their textual analysis of 4,518 articles and qualitative analysis of 443 articles, they found that the discourse around gentrification was more mixed than suggested by the prior literature. In particular, the frames used to describe gentrification varied depending on whether the coverage was of an early stage of gentrification, a middle stage, or an advanced stage. Critical frames were more likely in articles about advanced stage gentrification than those that were about early stages in the process when frames were more positive (Brown-Saracino & Rumpf, 2011). This finding suggests that evidence from prior studies could be skewed by a focus on neighborhoods experiencing early stage gentrification. Furthermore, Brown-Saracino and Rumpf (2011) found variation in the use of critical frames depending on the race and class background of the gentrifier and the gentrified, which suggests that the racial and class demographics of the changes studied would also contribute to how the change was represented.

The contradiction between more targeted analyses and larger studies of newspaper articles marks a continued lack of clarity on the role that newspapers play in the urban development process, particularly around gentrification. Whether newspapers promote or obstruct gentrification remains a contested question, one that requires further research. Furthermore, the focus on large metropolitan areas in the one larger-scale and more systematic analysis (Brown-Saracino & Rumpf, 2011) raises questions about how these frames vary for smaller cities and cities that faced more serious decline in the face of de-industrialization.

The Media’s Potential Influence on Policy

Much like the prior literature on the news media and urban development, studies attempting to link the news media, public opinion, and policy have produced inconsistent results (Altheide, 2000; Hallin & Mancini, 1984; Schudson, 1982). Yet, researchers generally agree that the news media plays an important role in public opinion and policy arenas by identifying what issues readers, including politicians, should be thinking about (Altheide, 2000; Andsager, 2000; Bleich et al., 2015; Briggs & Hallin, 2007; Cappella & Jamieson, 1997; Eschholz et al., 2003; Gamson, 1988; Gamson & Modigliani, 1989; Gilens, 1996; Gitlin, 2003; Hester & Gibson, 2007; Sacco, 1995; Schudson, 1982). So, although the news media’s ability to sway public opinion may be limited, coverage of an issue in the news signals that it is something people should be thinking about and an issue that politicians’ constituents might care about (Gitlin, 2003; Schudson, 1982). As discussed further below, news media coverage (a) identifies what readers should be thinking about, (b) defines the issue for readers, and (c) reflects and reinforces stereotypes and assumptions that Americans generally hold.

While the news is often described as a mirror or reflection of the world around us (Altheide, 2000; Gamson, 1988; Gans, 2004; Gilens, 1996; Hallin & Mancini, 1984), it is a selective reflection since all forms of news media experience constraints that limit how much news they can cover (Gamson & Modigliani, 1989; Gans, 2004; Gitlin, 2003; Hilgartner & Bosk, 1988). Television and radio news programs only have a certain amount of time for their programs and newspapers have space limitations (Gamson & Modigliani, 1989; Gans, 2004; Gitlin, 2003; Hilgartner & Bosk, 1988). Thus, the news media influences what readers think about by paying attention to some issues and ignoring others (Gitlin, 2003; Schudson, 1982). These constraints lead to restrictions on what the news media presents.

While ideally, the news media’s representations of an issue provide a framework for understanding what the issue is, who is involved, where and when it happened, and why it occurred (Binder, 1993; Cappella & Jamieson, 1997; Chavez, 2013; Earl et al., 2004; Hudson & Martin, 2010; Schudson, 1982), this information is often limited in two important ways due to the constraints on space and time. First, viewpoints on social issues are often presented as limited to two perspectives: one pro and one con (Gamson, 1988; Gamson & Modigliani, 1989; Hall, 1997). While social issues may elicit a much wider variety of responses than this binary representation would suggest, most social issues are presented with just two perspectives (Gamson, 1988; Gamson & Modigliani, 1989). Second, oftentimes the social and historical context of how the social issue came to be is not introduced (Entman & Rojecki, 2001). This means that issues that have emerged due to historical processes of exclusion and discrimination, for example, are often not contextualized in that history. Thus, readers receive a simplified accounting of the social issue at hand.

Finally, the news media reflects the culture of the society and time around us, including reinforcing stereotypes and assumptions Americans generally hold along the lines of both race and class (Binder, 1993; Chavez, 2013; Dávila, 2008; Earl et al., 2004; Entman & Rojecki, 2001; Gilens, 1996; Gray, 2013; Hall, 1997; Kendall, 2011; Schudson, 2002). In particular, the prior research shows that the news reinforces negative stereotypes of poor people and blacks as lazy and violent (Entman & Rojecki, 2001; Gans, 1995; Gilens, 1996, 2009; Katz, 1989; Kendall, 2011; O’Connor, 2001; Soss et al., 2011). These stereotypes reinforce common assumptions among readers aligned with these stereotypes (Binder, 1993; Chavez, 2013; Dávila, 2008; Earl et al., 2004; Entman & Rojecki, 2001; Gilens, 1996; Gray, 2013; Hall, 1997; Kendall, 2011; Schudson, 2002).

Importantly, the influence the news has on its readers is mediated by the readers themselves through the process of interpretation (Eschholz et al., 2003; Gamson, 1988; Gamson & Modigliani, 1989; Hester & Gibson, 2007; Sacco, 1995). More specifically, the news is interpreted by readers through the lens of their prior experiences (Eschholz et al., 2003; Gamson, 1988; Gamson & Modigliani, 1989; Hester & Gibson, 2007; Sacco, 1995). Readers who have less experience with the issue at hand are likely to be more influenced by representations of social issues in the news than those who have direct experiences (Hallin & Mancini, 1984; Sacco, 1995).

So even though the news media may not coerce its readership to support pro-gentrification measures as suggested by the growth machine theory (Logan & Molotch, 1987; Molotch, 1976), these studies suggest that it may still influence readers by getting them to think about gentrification. While readers who live in gentrifying or gentrified neighborhoods may not be swayed to think one way or the other by the news media’s spin or framing of the issue, readers who have no experience with gentrification could formulate an opinion on the issue based on the cases the news media presents and how it represents the process. Given the growing attempts to address the negative outcomes of the gentrification process through policy and planning practices across American cities, understanding how the news media is representing gentrification documents the representations informing the unexperienced voter and politician.

Gentrification, Inequality, and Policy

Like any process of change, there are both benefits and drawbacks to the process of gentrification. These include potential benefits for both long-term residents and cities and potential drawbacks for long-term residents. Whether policies are introduced to address the drawbacks and supported by politicians and voters is dependent on whether or not they see gentrification as a social problem that needs to be addressed (Hilgartner & Bosk, 1988).

Implications of gentrification for long-term, low-income residents. In theory, the process of gentrification could produce racially and class integrated communities in which lower-income residents gained access to better resources and amenities including schools, supermarkets, and parks (Lees, Slater, & Wyly, 2008). But continued access to these resources and amenities is contingent on long-term, low-income residents being able to stay in the community (Berrey, 2005; Gotham, 2001; Lees et al., 2008; Ocejo, 2011; Perez, 2002, 2004; Powell & Spencer, 2002; N. Smith, 1996; Walks & Maaranen, 2008; Wyly, Newman, Schafran, & Lee, 2010). While a small number of quantitative studies have found no significant evidence of displacement in gentrifying cities (Ellen & O’Regan, 2011; Freeman & Braconi, 2004), qualitative case studies of gentrification in specific neighborhoods document the prevalence of displacement of long-time, low-income residents and the businesses that serve them across a variety of forms of gentrification (Gans, 1962; Glass, 1964; Gomez, 2013; Hyra, 2008; Perez, 2002, 2004; N. Smith, 1996; Zukin, 1989).3

If we assume that some level of displacement is occurring in gentrifying neighborhoods, there are a number of policies that cities have used and can use to try to reduce displacement. These policies include protecting affordable housing, placing limits on development in gentrifying neighborhoods, funding or supplementing affordable housing development, and restricting

3 This discrepancy between quantitative and qualitative studies of displacement in gentrifying neighborhoods seems to be predominately driven by the focus on low-income, low homeownership neighborhoods among qualitative case studies (Conley, 1999). However, the literature to date has done little to untangle how differences in homeownership rates affects whether and how displacement unfolds. 12

increases in property taxes and rents in gentrifying neighborhoods. Whether local voters and politicians support these types of measures depends on whether they see gentrification as an issue that can be addressed with policy and whether they see gentrification as an issue in need of a policy response. This is informed by what local actors think gentrification “looks like” including who they think is involved in the process, where they think it is happening, what kinds of changes they believe are entailed, who they think is affected, and how they think it will affect various stakeholders.

Implications of gentrification for cities. While long-term residents face potential benefits and drawbacks from gentrification, cities are most likely to benefit from the process. The influx of a higher-income population is likely to increase revenue from taxes (Byrne, 2002; D. Smith, 2005). Furthermore, the in-movement of the middle-class is usually followed by businesses and employers, which increases the commercial tax base (Byrne, 2002; Cameron, 2003; Hyra, 2008). While cities may lose low-income voters, as seen in areas experiencing the suburbanization of poverty in response to gentrification (Garr & Kneebone, 2010; Kneebone & Berube, 2013; Soursourian, 2012), they gain groups that are typically more politically active and able to contribute financially to the city. The one potential drawback for cities is that middle-class in- movers are likely to place more demands on city agencies and resources (Peterson, 1985).

The Reporting Context

Baltimore and San Francisco newspapers are reporting on news in two distinct urban environments. Across the dimensions of race, class, the labor market, and the housing market, the cities represent a global city and a post-industrial city, two contexts in which gentrification is present, but may be represented differently by the news media. In particular, I chose Baltimore and San Francisco because I expect that race and class demographics, labor market health, and housing market conditions will influence what newspapers categorize as gentrification, the stakeholders they associate with gentrification, and the positive or negative spin they give the process. In the sections below, I describe the context of both cities on each dimension and then present hypotheses about how these demographics influence the representation of gentrification in the news media.4

Baltimore and San Francisco represent a simplified and more complex racial environment.5 Baltimore was a majority black city with a moderate white population. While the black population was relatively stable over time, the city’s white population declined by almost half between 1980 and 2014. Additionally, there was a small, but growing Latino population that increased from 1 to 5 percent. In contrast, San Francisco was relatively diverse and was majority-minority since 1990, which was driven by a large proportion of Asians (34 percent in 2014) and Latinos (15 percent). San Francisco’s black population was small in comparison with Baltimore and it declined by more than half between 1980 and 2014.

4 Detailed tables of all demographic data presented are included in Appendix Tables 2 and 3. 5 See Appendix A for detailed tables of each city’s racial and class composition between 1980 and 2014. 13

In terms of class composition, Baltimore and San Francisco represent two extremes by both income and education. By measures of income, Baltimore saw very little change in the class composition of its residents over time. Between 1980 and 2014, most Baltimore City residents were either low-income (less than $25,000) or middle-class ($50,000-99,999). Changes in educational attainment in Baltimore largely reflected the changes of the U.S. at large with more high school and college graduates over time. The majority of residents did not have a high school diploma in 1980 (52 percent), but by 2014, the majority held a high school diploma (54 percent). In contrast to Baltimore, San Francisco was higher income and higher educated and grew increasingly so. The middle-income households were most prevalent in San Francisco between 1980 and 2010 ($50,000-99,999). In fact, the middle-income was surpassed by the upper-class ($150,000 or more) in 2014. Interestingly, the low-income population (less than $25,000) stayed relatively stable between 1980 and 2014, while the lower-middle class ($25,000-49,999) declined. By measures of education, San Francisco became increasingly educated. While the city’s largest population was those with a high school diploma in 1980, most San Francisco residents either held a Bachelor’s degree or a high school diploma by 2014. Over this time, those with less than a high school diploma decreased by half and those with a graduate, professional, or doctoral degree increased by almost double.

One reason for the differences in education and income between Baltimore and San Francisco residents was differences in employment opportunities between the two cities. At the beginning of the period, Baltimore City was predominately dependent on the manufacturing industry, but manufacturing was on the decline. Instead, employment in educational and health services increased to be the predominant industry of employment in the city by almost 19 percentage points. San Francisco also had a strong educational and health services industry that had small, but steady increases in its share of city employees, but the city’s labor market was less dependent on the Eds and Meds than Baltimore City. San Francisco’s largest industry of employment was professional industries including technology, which employed slightly more city residents than the Eds and Meds (about 4 percentage points more).

Despite these patterns in class composition and industry of employment, Baltimore had a larger proportion of homeowners than San Francisco. Between 1980 and 2014, about half of Baltimore residents were homeowners and half were renters, compared with about two-thirds renters and one-third homeowners in San Francisco. This difference was driven in part by large differences in housing costs. Baltimore was an affordable city for a homebuyer with the vast majority of houses valued at between $50,000 and $499,999 in 2014. In contrast, the vast majority of housing values in San Francisco were $500,000 or higher. Furthermore, most rents were $1,500 per month or more.

These race, class, and economic conditions represent two types of American cities. Baltimore is majority black, predominately low-income and middle-class city with little employer diversity and affordable housing. In contrast, San Francisco is relatively diverse racially, predominately

middle- and upper-class with more a relatively diverse economy and extremely unaffordable housing.

How Context Might Influence Representation

This context is the back drop to the local news reports in this study. The race, class, and economic demographics of the cities informs what newspapers categorize as gentrification, the stakeholders they associate with gentrification, and the positive or negative spin they give the process. Below, I outline on how context might matter for representations of gentrification.

Categorization. The class, labor market, and housing market dynamics of the city play a central role in the kinds of changes that the news media categorizes as gentrification. These contributions are due in part to the role these play in the gentrification process itself. That is, with no middle-class, there is no gentrification; with no jobs for the middle-class, there is no middle-class return to the city; and with no relatively affordable housing somewhere in the city, there is no gentrification by the middle-class, particularly the higher educated, but lower income in-movers associated with early gentrification in many neighborhoods (Dávila, 2004; Freeman, 2006; Lees et al., 2008; Peterson, 1985; N. Smith, 1996; Zukin, 1989). These three factors affect whether and where a city experiences and has experienced gentrification. In cities like San Francisco with prior exposure to rising housing prices, growing middle- and upper-classes, and middle- and upper-class employers is likely to lead to the more prevalent use of the term gentrification by journalists and their sources to describe neighborhood change or the suggestion of neighborhood change aligned with any of these three dynamics. This suggests the prevalent use of gentrification to describe residential change and development, and commercial change and development in San Francisco newspapers. In contrast, we are likely to see less use of the term gentrification in the Baltimore articles, but with a similar application.

Association. While the demographics of the cities themselves do not explain how race and class will be associated with gentrification in newspapers, they do define the range of possible racial and class groups to be associated with the process. For example, references to the working- class seem more likely in Baltimore newspapers than San Francisco newspapers as residents of gentrifying neighborhoods due to the high and steady proportion of lower-middle-class in Baltimore in comparison to smaller and declining lower-middle-class in San Francisco. In San Francisco, we might see more references to the poor than the working-class due to the steady numbers of the poor, but the decline in the working-class could be the result of gentrification and, thus, mean more references to the working-class than to the poor. Additionally, the middle-class seem most likely to be associated with in-movers to gentrifying neighborhoods in both cities due to the class demographics and the class definitions of gentrification. However, San Francisco articles may also refer to the upper-class due to the large growth in high-wage earners during the period of study.

How race will be associated with gentrification is less clear. Based on the prior literature on the relationship between race and gentrification described above, we would expect white and Latino neighborhoods to be described most often as gentrifying and whites and Asians to be described as gentrifiers across both cities (Ellen & O’Regan, 2008; Hwang, 2015, 2016; Hwang & Sampson, 2014; Timberlake & Johns-Wolfe, 2016). However, prior case studies of gentrifying neighborhoods suggest that black neighborhoods will be described as gentrifying most often and whites described as gentrifiers (Fallon, 2016). Given stereotypes of the class composition of racial groups and the strong visual cues of change provided by racial mixing, I predict the latter: that newspapers will predominately depict black neighborhoods with white in-movers across both cities regardless of actual patterns of gentrification. In San Francisco, in-movers are also likely to be described as Asian given the high skilled immigrant labor force associated with the technology industry (Saxenian, 2002).

Spin. Race and class stereotypes are likely to contribute both directly and indirectly to whether gentrification is described as a positive or negative change by journalists and their sources. Depictions of gentrification in poor or black neighborhoods are more likely to include a positive spin given negative stereotypes of poor and black neighborhoods as being disinvested areas with high rates of crime and violence, and high poverty rates (Quillian & Pager, 2001; Sampson, 2012; Sampson & Raudenbush, 2004). In contrast, gentrification in working-class, middle-class, and white neighborhoods is more likely to have a negative spin, since the working class, middle class, and whites are positively stereotyped as hardworking Americans (Kefalas, 2003; Kendall, 2011). Gentrification in Latino and Asian neighborhoods could have a more positive or a more negative spin depending on which stereotypes of Latinos and Asians are evoked. Stereotypes of Latinos as criminals and undocumented immigrants, and Asians and Latinos as foreigners who don’t want to learn English or American culture would lead to a more positive spin on gentrification in those neighborhoods (Chavez, 2013; Dávila, 2008; C. J. Kim, 1999; N. Y. Kim, 2007; Tuan, 1998). In contrast, stereotypes of Asians and Latinos as hardworking immigrants who have assimilated into American culture would lead to a negative spin on gentrification.

Finally, the race and class depictions of in-movers to gentrifying neighborhoods are likely to affect whether gentrification is portrayed positively or negatively. For instance, depictions of white or middle-class in-movers is likely to produce a positive response to gentrification due to positive stereotypes of both groups. But, Asian or upper-class in-movers might lead to more negative responses. While both groups are associated with positive stereotypes like Asians being hardworking and the upper-class being generous, Asians are often stereotyped as unassimilable foreigners (C. J. Kim, 1999; N. Y. Kim, 2007; Tuan, 1998) and the upper-class are sometimes stereotyped as selfish and materialistic (Kendall, 2011).

Importantly, the spin has to do in part with the demographics of both long-term residents and recent in-movers. For example, articles depicting poor or black neighborhoods with middle- class or white in-movers are likely to include a more positive spin than articles about middle- class or white neighborhoods with upper-class or Asian in-movers. Similarly, Asian and Latino

in-movers would be more likely to be viewed positively if they were gentrifying a black neighborhood.

Overview of Chapters

Across the chapters that follow, I explain how the news media represented gentrification and how those representations replicated and reinforced racial and class hierarchies through the analysis of newspaper articles from four local newspapers published in Baltimore and San Francisco between 1990 and 2014 combined with Census and American Community Survey data. In Chapter 2, I introduce the cases of Baltimore and San Francisco including a economic and urban development history of the cities, the four newspapers, and the methods I used to analyze the data. This methodological introduction is followed by 3 empirical chapters. The first, Chapter 3, explains how race and class were represented in the news about gentrification with an analysis of how race and class were associated with residents of and in-movers to gentrifying neighborhoods. In Chapter 4, I document the kinds of change categorized as gentrification as compared with the term urban renewal, and how the categorization of gentrification varied depending on racial and class demographics. Finally, in Chapter 5, I analyze the spin on gentrification as a helpful or harmful change including whether spin varied by racial and class demographics.

Chapter 2: The Cases

As outlined in Chapter I, this study addresses the question: How does the news media represent gentrification? To answer this, I used newspaper articles from four local newspapers from two cities: Baltimore, Maryland and San Francisco, California. As a cultural institution, newspapers provides insight into how the term gentrification is used and understood on a day-to-day basis. The news reflects how the general public defines and understands gentrification, while also providing new information about where gentrification is occurring, how it is unfolding, who it is affecting, and who is driving the change. In this chapter, I explain the two types of cases I focus on in this dissertation: the newspapers and the cities.

I chose Baltimore, Maryland and San Francisco, California to explain how race and class hierarchies are reinforced and represented in the news media on gentrification for three reasons, which I expand upon below. First, the cities have different racial and class demographics that allow me to investigate whether representations of race and class in gentrification vary in cities with distinct racial and class demographics. Second, the cities have had very different levels of exposure to gentrification. Finally, the history of both cities reflects common narratives of urban development across the U.S.

In the rest of this chapter, I first explain why I chose to look at newspapers and introduce the papers I selected for this study. I then explain why Baltimore and San Francisco are useful cases for this study. Finally, I summarize the relevant historical and study period context to situate the findings I present in the chapters that follow.

Studying News Media Through Newspapers

This study investigates representations of a social process in the news to understand how racial and class hierarchies influence and are reinforced through the media. The news media is one institution that regularly contributes to the social construction of meaning (Gamson, 1988; Gamson, Croteau, Hoynes, & Sasson, 1992; Gamson & Modigliani, 1989; Gitlin, 2003; Hall, 1997; Schudson, 1989). Through text, images, and audio, the news media (re)presents the social issues of the world around us including defining the key actors, situating the issue in a time or place, and identifying the debates on the issue (Hilgartner & Bosk, 1988). Put simply, the news media represents and frames the issues, adding to readers’ and viewers’ understanding of those issues (Eschholz et al., 2003; Gamson, 1988; Gamson & Modigliani, 1989; Hester & Gibson, 2007; Sacco, 1995). The social issues the news media covers signals to readers and viewers that these are issues they should be thinking about whether they agree with the media’s frames or not (Gamson, 1988; Gamson & Modigliani, 1989).1 For the case of gentrification, the news media has been particularly important because the term was defined in the academy (Lees et al., 2008). So while the term gained usage amongst academics, it was not

1 See Chapter I for a more detailed explanation of this process. 18

a part of everyday vocabulary. Using the term gentrification in social conversations in the late 1960s after the term was coined (Glass, 1964) would have led to questions about what exactly one was referring to. The news media has been a central means of dissemination of the term, moving it from a part of a specialized language to a part of everyday vocabulary.

While the news media includes television, radio, news magazines, newspapers, and websites, I specifically chose newspapers as the main data source for this study because they offer a consistent and accessible data source on how the media, and thus their readership, understood gentrification for the full period of study: 1990 to 2014 (Earl et al., 2004). Newspapers are frequently used sources in research even outside of research in mass communications and journalism (Earl et al., 2004). While newspaper readership declined by about 10 percent between 2000 and 2016 (Barthel, 2017), newspapers still play an important role in news media overall. News reports in newspapers often set the news agenda for other outlets (e.g., television) (Golan, 2006; Maier, 2010). In fact, there is significant overlap in content between newspapers, television, radio, and online content, a concept called “intermedia agenda setting” (Golan, 2006; Messner & Distaso, 2008).

The Newspapers

The newspapers included in this study represent the mainstream, local press. As gentrification is a neighborhood-based process, I chose to focus on local newspapers. Furthermore, I selected mainstream newspapers that had the largest circulation in each city to better understand how gentrification is represented and depicted to a mainstream readership. Thus, I include articles from four newspapers that represent the most circulated papers in Baltimore and San Francisco: the Baltimore Sun, the Baltimore City Paper, the San Francisco Chronicle, and the San Francisco Examiner.

The Baltimore papers. Owned by Times-Shamrock Communications and Tronc during the period of study, the Baltimore Sun was the most circulated newspaper in the city with 145,810 print and digital circulations (Alliance for Audited Media, 2014b). The Baltimore City Paper was originally an independent newspaper, but was acquired by Times-Shamrock Communications in 1987 and then the Baltimore Sun Media Group in 2014 (Meehan, 2014). The City Paper was the second most circulated newspaper in the Baltimore area with a circulation of 50,025 (Alliance for Audited Media, 2014a).

The San Francisco papers. The San Francisco Chronicle was owned by Hearst Communications during the period of study. As the most circulated newspaper in the city, it had 206,868 print and digital circulation (Alliance for Audited Media, 2014c). Second in circulation, the San Francisco Examiner had a circulation of 155,011 (The San Francisco Examiner, 2015). The Examiner was owned by Hearst Communications and the Black Press Group during the period of study.

Readership. Across all 4 newspapers, readers are predominately educated and affluent, which means that they are likely to be both politically active and less directly affected by gentrification. Readers’ direct experiences with gentrification in both cities is most likely as being gentrifiers. The data described in this section came from publicly available reports, which varied in the level of detail provided and the measures of class background. The Sun’s readership had a median household income of $72,921 and 74 percent were homeowners (“The Baltimore Sun | Baltimore Sun Media Group,” 2015). The City Paper’s readership had a similar profile with 33 percent having an annual income of $75,000 or higher, and 34 percent holding a college degree (Baltimore City Paper, 2014). Thirty-seven percent of the Chronicle’s readership had a household income of $100,000 or more and 52 percent had a college degree (Hearst Corporation, 2017). Similarly, 75 percent of the Examiner’s readership had a household income of $50,000 or more and 70 percent were college educated (The San Francisco Examiner, 2015).

The Articles

I selected the articles included from each newspaper based on the following criteria. First, the article had to have been published between 1990 and 2014. Second, the article had to have used one of the search terms shown in Table 12. And third, the article had to be about Baltimore City or San Francisco.3 This selection process resulted in a total of 2,223 articles that came from all sections of the newspapers. This search criteria is not likely to capture all neighborhood change for two reasons. First, not all neighborhood change will be reported on in the newspaper. Second, other, less frequently used terms were likely used to describe neighborhood change that are not included as search terms. Despite these potential omissions, the final dataset helps to understand how gentrification is used in comparison to other terms that could be used to describe similar changes and allows me to explain how neighborhood change is (re)presented when it is reported on by the news media.

2 The search terms came from frequently used terms to describe changes related to gentrification in the academic literature (deductive). However, as I saw additional terms in newspaper articles (e.g., rejuvenated), I searched to determine whether there was a critical mass of articles that suggested that a search term should be added (inductive). 3 Articles about any other part of the Bay Area or the Baltimore metropolitan area were excluded from the analyses. 20

Table 1: Search Terms and Total Number of Articles

Search Terms Number of Articles

Gentrification, gentrifying, gentrified, gentrify 950 Urban renewal 826 Neighborhood/community revitalization 251 Neighborhood/community improvement 114 Neighborhood/community redevelopment 62 Neighborhood change 20

Total articles 2,223

SOURCE: Author's calculations using a selection of newspaper articles published in the Baltimore Sun , Baltimore City Paper , San Francisco Chronicle , and San Francisco Examiner between 1990 and 2014.

These articles included 950 that use the term gentrification or a derivative of the term. The final set of articles is predominately news articles, but also includes reviews of restaurants and neighborhoods, editorials, and letters to the editor. Importantly, while each article used one of the search terms, the search term was not necessarily the main focus of the article.4

Overall, most of the articles came from the top circulated newspapers: the Sun and the Chronicle. This supports prior findings that gentrification was referred to more frequently in major newspapers (Brown-Saracino & Rumpf, 2011).

Data Analyses

For the findings presented here, I transformed the newspaper articles into three types of data. First, with the help of a team of undergraduate researchers, I compiled and analyzed objective information about each article including the date of publication, the author, the section of the newspaper in which it appeared, the kind of change described by the search term, and the neighborhood described by the search term. These data allow me to answer questions about categorization including when the term gentrification is used to describe neighborhood change and how that varies by the race and class composition of a neighborhood.

Second, I used MaxQDA, a qualitative data analysis program, to conduct text analysis for race and class search terms (shown in Table 2) in each article that uses the term gentrification. This process involved providing the software with a list of search terms, removing any references that were not references to race or class, and tagging the remaining results with the race or

4 Appendix Table 1 provides details on the subject matter covered in articles that used the term gentrification. 21 class descriptor. These analyses provided data on when and how race and class were referenced in the articles.

Table 2: Race and Class Text Analysis Terms

Race/Ethnicity Category Search Terms Asian Asia Chinese India Japan Korea Vietnam Filipino Philippines Black Black African Caribbean Jamaica “West Indian” “West Indies” Latino Hispanic Latino Dominican Mexican Mexico “Puerto Rican” “Puerto Rico” "El Salvador" "El Salvadorian" “Central America” Guatemala Nicaragua Biracial Biracial “mixed race” multiracial Native American “Native American” “American Indian” White White Europe French France German Irish Ireland Italian Italy wasp Caucasian Polish Poland Greek Greece Unclear Diversity multicultural minorities “people of color”

Class Category Search Terms Low-income Low-income “low income” lower-income “lower income” poor poverty welfare homeless “affordable housing” “service industry” “Section 8” SRO Working-class Working-class “working class” blue-collar “blue collar” manufacturing Middle-class Middle-class “middle class” middle-income “middle income” upper- middle-class “upper middle class” college college-educated “college educated” professional white-collar “white collar” yuppie buppie homeowner “home owner” homebuyer “home buyer” homeownership “home ownership” “market rate” “highly educated” Upper-class Upper-class “upper class” upper-income “upper income” rich affluent luxury wealth elite Mixed-income Mixed-income “mixed income”

Finally, I used MaxQDA to conduct qualitative coding on each article that used the term gentrification. This coding included codes for the stakeholders described in the process, the race and class demographics of the stakeholders, the subject matter of the article, benefits of gentrification, concerns about gentrification, and actual and suggested policy solutions to the negative impacts. The results of this coding provide information about how race and class are associated with gentrification and the spin on gentrification. Detailed descriptions of the coding schemes leveraged in the analyses are included in each empirical chapter.

The chapters that follow analyze these three forms of data, along with Census data, to explain the representation of gentrification in local news media in Baltimore and San Francisco between 1990 and 2014. I conducted all quantitative analyses using Stata and identified representative and illustrative qualitative cases to highlight as examples using MaxQDA.

The Cities

Baltimore and San Francisco represent contrasting cases in many ways, as outline in Chapter I. They vary on racial and class composition, as well as labor and housing market conditions. These differences allow me to isolate how representations of gentrification vary due to local differences. In particular, I can identify whether differences in racial and class composition influence what race and class groups are associated with gentrification, what kinds of change are categorized as gentrification, and how gentrification is spun.

In the context of American cities overall, Baltimore represents a post-industrial city. Faced with a large economic loss due to the decline of manufacturing, the city has bounced back, but not thrived in the modern economy. In contrast, San Francisco has seen accelerated growth, boosting its economy to becoming a global city.

As described in the sections below, Baltimore and San Francisco today are contrasting cities, but they come from a similar history as port cities with strong shipbuilding economies.

A Similar Start: the 1940s through the 1970s

Today, Baltimore and San Francisco represent contrasting cities. However, their historical trajectory prior to the 1980s was remarkably similar. Like many central cities throughout the United States, Baltimore and San Francisco experienced a boom in the manufacturing economy around World War II, a migration of blacks from the South in search of better jobs, and white and middle-class flight with the suburbanization of manufacturing jobs and housing development in the suburbs. The extreme differences between the cities in terms of class composition, labor markets, and housing costs arise from different outcomes beginning in the 1980s.

The Manufacturing Heyday. The 1940s marked a period of economic boom for cities across the United States (W. J. Wilson, 1987). The manufacturing industry was at its height and was predominately located in central cities (W. J. Wilson, 1987). With the onset of World War II, factories in Baltimore and San Francisco began producing materials for the war due to the high number of industrial manufacturing employers and their shipbuilding industries (Dillon, 2011; Pietila, 2010; Solnit & Schwartzenberg, 2002).

Between the demand for war related goods and the loss of many manufacturing workers to the armed forces, there was a need for more workers in both cities (T. L. Smith, 1966). Southern blacks responded to the opportunity for better paying jobs and a chance to leave the structural and systemic racism of the South, moving North and West to cities including Baltimore and San Francisco in droves (Brahinsky, 2014a; Causa Justa, n.d.; Day & Abraham, 1993; Dillon, 2011, 2014; Godfrey, 1988; Hartman, 2002; C. Jackson & Jones, 2012; McDougall, 1993; Pietila, 2010; T. L. Smith, 1966; Tracy, 2014). In fact, the Great Migration established the black population in San Francisco, which was less than 1 percent of the city in 1940 and increased by 700 percent by 1945 (Brooks, 2009; Day & Abraham, 1993; Dillon, 2014; Godfrey, 1988; Tracy, 2014).

Similarly, in Baltimore, racial change was driven by the Migration, which almost doubled the black population between 1910 and 1940 (T. L. Smith, 1966).

At the same time, San Francisco became a port of entry for Asian and Latin American immigrants (Godfrey, 1988). Already a destination location for Chinese and Mexican immigrants, San Francisco saw a large increase in Mexican immigrants starting in the 1920s due to the lack of restrictions on their in-movement under the 1924 Immigration Act and the Bracero Program for Mexican workers in 1942 (Causa Justa, n.d.).

Suburbanization, White Flight, and Disinvestment. As early as the 1930s, manufacturers began to move to the suburbs to find additional space across the country, leaving city centers with large losses of employers (Mollenkopf, 1983). This loss included the decline in the shipbuilding industries in both Baltimore and San Francisco (Dillon, 2011; Rosen & Sullivan, 2012; G. R. Wagner, 1995). As the second largest industrial region on the East Coast, Baltimore was hit particularly hard losing 18,000 manufacturing jobs between 1950 and 1960 and 82 employers between 1955 and 1965 (Levine, 1987; Merrifield, 1993; Pietila, 2010). The suburbanization of manufacturing came later to San Francisco in the 1960s and early 1970s, giving the city some opportunity to prepare for the changes ahead (Day & Abraham, 1993; Hartman, 2002; Mollenkopf, 1983; Wetzel, 2001). But even with these preparations, San Francisco lost $313 million in 1974 with the close of its largest industrial employer, a shipyard (Dillon, 2011; Rosen & Sullivan, 2012).

Like cities across the U.S., Baltimore and San Francisco faced the loss of working-class and middle-class whites during this period who were increasingly moving to the suburbs due to the relocation of manufacturing employers and the newly available federally backed home mortgage loans that made it possible for middle-class whites to buy homes (Cohen, 2001; Freund, 2006; Hackworth, 2007; K. T. Jackson, 1985; Mollenkopf, 1983; Orser, 1991; G. R. Wagner, 1995; W. J. Wilson, 1987; Wright, 1981). This white flight was encouraged by the racial conflict that came with the Civil Rights Movement, particularly in Baltimore (McDougall, 1993; Pietila, 2010; G. R. Wagner, 1995; W. J. Wilson, 1987). With whites leaving the city, racial segregation unfolded in both cities through two city implemented policies. Cities used segregated public housing (McDougall, 1993; Orser, 1991; Tracy, 2014) and urban renewal (Gomez, 2013; Hartman, 2002; Mollenkopf, 1983) to reconcentrate blacks into specific areas of the city. In many cases, these displacement or “Negro removal” projects were used to remove communities from valuable central city land that was often redeveloped for office space of luxury housing (Day & Abraham, 1993; Dillon, 2011, 2014; Gomez, 2013; Hartman, 2002; C. Jackson & Jones, 2012; Levine, 1987; Mirabal, 2009; Mollenkopf, 1983; Pietila, 2010; Solnit & Schwartzenberg, 2002; Tracy, 2014; R. Walker, 2006). While blacks faced increasing segregation through city policies during this time, Asians in San Francisco became more integrated with the remaining whites (Brooks, 2009).

Along with the white and middle-class flight came population loss (Bradbury, Downs, & Small, 1982; Cohen, 2001). Initially, this freed up housing for blacks and immigrants who were

concentrated in overcrowded areas of the city (Mollenkopf, 1983). But eventually, population loss created issues of housing vacancy, marking the start of inner city decline and disinvestment (Cohen, 2001).

Redevelopment as Economic Development. The decline in manufacturing marked the emergence of a new economy: service (Hackworth, 2007; Levine, 1987; Mollenkopf, 1983; Moretti, 2012; W. J. Wilson, 1987). Faced with a loss of manufacturing and shipbuilding, both Baltimore and San Francisco turned to redevelopment plans to prepare for the new growing economy of service (Hackworth, 2007; Hartman, 2002).

Due to the early foresight of the mayor, city officials, and local business leaders, San Francisco began redevelopment plans for the service economy early on. In fact, many of the urban renewal projects of the 1950s were focused on expanding office space in the downtown area a la Manhattan to support the new economy (Casique, 2013; Causa Justa, n.d.; Graham & Guy, 2002; Hartman, 2002; Hu, 2012; Mollenkopf, 1983; Robinson, 1995; Solnit & Schwartzenberg, 2002; R. Walker, 2006). Redevelopment projects included developing more efficient transportation systems through highway construction and a commuter railway called the Bay Area Rapid Transit (BART), building a convention center, and spatially reorganizing the downtown area to remove undesirable residential communities including blacks, Chinese, and artists (Casique, 2013; Day & Abraham, 1993; Dillon, 2011, 2014; Hartman, 2002; C. Jackson & Jones, 2012; Mirabal, 2009; Mollenkopf, 1983; Solnit & Schwartzenberg, 2002; Tracy, 2014; R. Walker, 2006). The shift to the service economy was particularly aided by the development of BART, which allowed suburban residents to commute to work in the city (Hartman, 2002; Robinson, 1995; Rosen & Sullivan, 2012).

The Baltimore City government was similarly focused on downtown development. Beginning with a smaller scale project to boost investors’ confidence in downtown development projects in the 1960s, the city built the Charles Center, which housed offices, apartments, and retail shops (Levine). The success of the Charles Center development and the acceleration in the decline of the industrial area around the waterfront led to a larger-scale revitalization in the 1970s into a shoreline promenade with offices, retail, and entertainment called the Inner Harbor (Harvey, 2000; Levine, 1987; Merrifield, 1993; G. R. Wagner, 1995). The project aimed to create a business-friendly environment and attract financial services, tourism, and hospitality to the city center (Harvey, 2000; Levine, 1987; Merrifield, 1993).

Both cities also used business-friendly policies to attract new employers (Hartman, 2002; Levine, 1987). These strategies had some success in attracting businesses to the downtown areas, but most of these jobs went to higher-skilled and higher-educated residents of the surrounding suburbs, which did little to address the growing employment needs of former manufacturing and shipbuilding employees in the cities (Hartman, 2002; Levine, 1987; Robinson, 1995; Rosen & Sullivan, 2012). This disconnect between the employee needs of service sector employers and the skills of city residents meant that both cities faced growing

poverty rates during the 1970s, particularly among those previously employed in manufacturing (Day & Abraham, 1993; Dillon, 2011; Levine, 1987; Wetzel, 2001).

Despite these declines, early gentrification emerged in select neighborhoods in both cities. In Baltimore, early changes were predominately in neighborhoods around the Inner Harbor, which was encouraged by the city’s urban homesteading program that sold vacant housing for $1 (Cohen, 2001; Levine, 1987; Merrifield, 1993; G. R. Wagner, 1995). Early gentrification in San Francisco was also connected to redevelopment efforts. Artists evicted from neighborhoods targeted for urban renewal, moved to low-priced neighborhoods as gentrifiers (Casique, 2013; Wetzel, 2001). But other areas of San Francisco also experienced gentrification as the LGBTQ community, bohemians, and hippies began to move into a handful predominately low-income communities (Godfrey, 1988; Solnit & Schwartzenberg, 2002).

Diverging Trajectories: the 1980s through the 2010s

Despite similar investments in development, the cities ended up on divergent paths (Storper, Kemeny, Makarem, & Osman, 2015). While Baltimore’s Inner Harbor development was touted as a national success (Chapin, 2004; Kelly & Lewis, 1992; Levine, 1987), the rest of the city was in decline as unemployment and poverty increased and white flight was followed by black middle-class flight to the suburbs (Levine, 1987). By 1980, Baltimore was ranked the 5th neediest city in the nation (Levine, 1987). The city’s economy was increasingly dependent on educational and medical institutions as their main employers and catered to their development demands to ensure their continued stay in the city (Gomez, 2013). In contrast, San Francisco was courting a new industry and by the late 1980s saw the growth of businesses in a newer service economy: technology. While San Francisco was also experiencing white and middle- class flight, urban professionals and high-skilled immigrants replaced those who fled (Godfrey, 1988; Storper et al., 2015).

This study focuses on the period that marks the divergent trajectories of Baltimore and San Francisco beginning in 1990 and ending in 2014. While there were several isolated cases of residential gentrification in both cities prior to this period, 1990 marks the beginning of San Francisco’s path to super-gentrification or the increase in market-rate housing to the point that middle-class renters can no longer afford to stay in their neighborhood (Centner, 2008; Lees, 2010).

A City Striving for Revival: Baltimore. While Baltimore began the 1980s as the “Cinderella City” and a model for downtown redevelopment (Chapin, 2004; Kelly & Lewis, 1992; Levine, 1987), white and middle-class flight continued simultaneously (Cohen, 2001; Levine, 1987). Downtown neighborhoods were undergoing a renaissance, while the rest of the city faced a rise in the concentration of poor blacks (Cohen, 2001; Levine, 1987). In addition, manufacturing employers continued to vacate, leaving in their wake increasing rates of unemployment and vacant properties (Levine, 1987; G. R. Wagner, 1995). By the 1990s, the city was facing major issues with abandoned housing, vacant lots, homelessness, unemployment, poverty, and

26 population loss (Cohen, 2001; Harvey, 2000). The response to these issues came primarily through state-led and institutionally driven redevelopment efforts.

The state-led efforts focused on three distinct strategies. First, the city continued development in the downtown area including new sports facilities, high-end retail developments, tourist destinations, and additional office space, some of which repurposed land previously occupied by industrial employers (Chapin, 2004; Harvey, 2000; Levine, 1987). The goals of these projects were to attract further investment in the nearby commercial and residential areas and to stimulate the economy, but the investments largely failed to affect the surrounding neighborhoods (Chapin, 2004; Levine, 1987).

Second, the city used funding from the Department of Housing and Urban Development’s (HUD) HOPE VI program to remove and redevelop high-rise public housing developments throughout the city (Rosenblatt, 2011). Orchestrated between the 1990s and early 2000s, the new developments produced state-led gentrification (Bridge et al., 2012; Hackworth, 2007; Hyra, 2008) by removing more than 2,000 families from public housing and replacing them with mixed-income communities (Hackworth, 2007; Rosenblatt, 2011).

Finally, the city aimed to attract the “creative class” (R. Florida, 2014) to a designated arts district area in the early 2000s (Ponzini & Rossi, 2010; Rich, 2009). The district included parts of three declining neighborhoods near Penn Station, a prime location for commuters to Washington, D.C. (Ponzini & Rossi, 2010; Rich, 2009). Whether this designation affects the housing prices and demographics of the surrounding neighborhoods remains to be seen.

As educational and medical institutions (Eds and Meds) became the top employers in Baltimore, they gained political leverage with the City due to fears that they might relocate to the suburbs (Gomez, 2013; Hackworth, 2007). This leverage was used in part to gain approval for and investments in redevelopment projects for their surrounding areas (Gomez, 2013; Hackworth, 2007; Rich, 2009). In fact, between 1990 and 2014, Johns Hopkins Hospital, Johns Hopkins University, Maryland Institute College of the Arts, University of Baltimore, and University of Maryland all engaged in redevelopment activities in their surrounding neighborhoods. However, none of the redevelopment activities have been as extensive and invasive in the surrounding community as those taken on by Johns Hopkins Hospital (JHH) and University (JHU) during this period. JHU took on the redevelopment of commercial and residential spaces located near campus to address concerns with undergraduate safety in the surrounding neighborhood (Gomez, 2013). But the largest project was the development of a biotechnology park developed and executed by the city on behalf of JHH interests (Gomez, 2013). The 2001 plan for the project outlined the clearance of 88 acres including the demolition of 1,500 houses and relocation of 2,400 people in order to build a new school and a state of the art facility for biotechnology firms to relocate to the city (Gomez, 2013; Stone, 2013).

Both the state-led and institutionally driven redevelopment projects did little to address the city’s problems of unemployment, poverty, and disinvestment even with the city’s efforts to attract new employers (Gomez, 2013). In fact, many of the projects detailed above involved reconcentrating poverty to already poor areas of the city and encouraging residential gentrification (Gomez, 2013).

The Emerging Wealthy City: San Francisco. While the tech industry had originally settled in Silicon Valley, firms were beginning to move to San Francisco. They were lured away from the more suburban Silicon Valley by the high concentration of venture capital investors (R. L. Florida & Kenney, 1988; Graham & Guy, 2002; Storper et al., 2015; Wetzel, 2001; Zook, 2002, 2005) and the ability to use live-work spaces for lower costs to start their businesses (Casique, 2013; Solnit & Schwartzenberg, 2002). In fact, California’s venture capital industry was known for investing their money locally (R. L. Florida & Kenney, 1988). Between 1995 and 2000, 32 percent of investment dollars went to dot.com companies in San Francisco, followed by Boston with 8 percent (Solnit & Schwartzenberg, 2002). Locating in the city gave tech companies easy access to a large pool of investors, while paying less rent than charged for commercial space in Silicon Valley (Casique, 2013; Solnit & Schwartzenberg, 2002). By the early 1990s, San Francisco was the leading global center of the technology industry, and by the end of the 1990s, the tech industry was the city’s second largest industry of employment (Casique, 2013; Wetzel, 2001).

The high demand led to more investment in office construction and live-work spaces by developers, which the planning department pushed through quickly in order to encourage the continuing concentration of businesses in the city (Casique, 2013; Graham & Guy, 2002; Hartman, 2002; Mirabal, 2009; Solnit & Schwartzenberg, 2002; Wetzel, 2001). This increase in office construction began as early as 1980 with more than 30 million square feet of new commercial space built between 1980 and 1986 to accommodate employers in tech, as well as professional, business, and financial services (Graham & Guy, 2002).

In addition to becoming the center for the tech industry employers, San Francisco was also becoming the home to their employees. These new residents included employees of Silicon Valley who were choosing to live in an urban environment and commute to work, as well as employees of the new tech firms locating in the city (Casique, 2013; Graham & Guy, 2002; Hartman, 2002; Solnit & Schwartzenberg, 2002; R. Walker, 2006). The gentrification that ensued in the 1990s was marked by high levels of displacement and an increasing use of eviction to vacate properties of long-term residents (Casique, 2013; Graham & Guy, 2002; Hartman, 2002; Mirabal, 2009; Tracy, 2014; Wetzel, 2001). Between 1999 and 2000, 2,761 households were evicted city wide (Wetzel, 2001)). In addition, long-time residents and businesses also faced de facto eviction through dramatic rent increases, strong-arm lockouts, and renovation activities to the building that affected their quality of life (Casique, 2013; Desmond, 2012).

Between the conversion of rentals to owned units and developers’ focus on office space and live-work units, the city had an overall decline in affordable housing starting in the 1990s

(Casique, 2013; Graham & Guy, 2002; Wetzel, 2001). Additionally, areas previously zoned for blue-collar industries declined with the conversion of industrial spaces to live-work lofts and office buildings, reducing the city’s ability to recruit blue-collar employers (Casique, 2013; Hartman, 2002; Solnit & Schwartzenberg, 2002; Wetzel, 2001). With fewer opportunities for affordable housing and working-class jobs, low-income and working-class residents were increasingly moving out of the city (Hartman, 2002; Solnit & Schwartzenberg, 2002; Yee, 1999).

In the early 2000s, the tech industry experienced a bust (Tracy, 2014; R. Walker, 2006; Wetzel, 2001; Zook, 2005). While this temporarily decreased pressure on the housing market, the tech industry made a dramatic return by the mid-2000s (Tracy, 2014). San Francisco saw growth in small tech businesses, but also became home to offices for some of the largest tech companies in the country including Twitter, Google, and Facebook (Tracy, 2014). Many of these companies moved into Enterprise Zones due to the offer of tax breaks that saved the millions of revenue in payroll taxes (Tracy, 2014).

While the first tech boom displaced the working-class in many central neighborhoods, the second tech boom increased prices and competition for housing to the point that even middle- class renters were struggling to stay in the city (Centner, 2008). Low-income, working-class, and middle-class renters left for more affordable options (Brahinsky, 2014b; Casique, 2013; Causa Justa, n.d.; Graham & Guy, 2002; Tracy, 2014) and evictions escalated (Brahinsky, 2014b; Causa Justa, n.d.; Tracy, 2014). Today, virtually all neighborhoods in the city have been touched by gentrification, even those previously undesirable due to high concentrations of poverty and crime (Brahinsky, 2014a; Dillon, 2014).

Conclusion

The divergent trajectories and contrasting demographics of Baltimore and San Francisco provide an opportunity to look for variation in how social hierarchies affect the representation of gentrification. Similarities between cities with such distinct compositions and histories will suggest potential universalities in American news media representations of gentrification, while differences will suggest how local context influences those representations. In particular, studying cities with racial and class variation allows for a broader understanding of how race and class hierarchies are replicated and reinforced in news media representations. As shown in the chapters that follow, race and class demographics, labor and housing market contexts, and the historical legacy of disinvestment and development all contribute to the news media’s representations of gentrification because they are the foundation on which gentrification is occurring. Gentrification changes the class demographics. It is spurred by the labor and housing market context. And it is only possible with the presence of disinvestment and the support of development efforts. The contemporary and historical contexts outlined here show up in reporting through how and when journalists and their sources use the word “gentrification.” This context helps readers understand what “gentrification” means, how it unfolds, if it’s a beneficial or detrimental change, and whether we should do something about it.

The power of the city cases in this particular study is that they provide contrasting cases that allow up to understand how representations of gentrification vary in demographically different cities that have been affected by gentrification in different ways and across different time frames. Given that gentrification has moved beyond the global cities, we need to understand more about gentrification in moderate and small cities. Yet, understanding gentrification in a global city context provides a sense of where things might be headed, particularly in cities where gentrification has escalated to affect the middle-class.

Chapter 3: Who is Gentrified? Who is Gentrifying?: Race and Class Associations

In this chapter, I explain how the news media represents race and class in the gentrification process. While race and class are referenced in a variety of different contexts, I find that the news media associates race and class with gentrification by describing the race and class backgrounds of residents of gentrifying neighborhoods and in-movers to those neighborhoods. Through association, newspaper articles directly link a race or class group to central actors in the gentrification process. The racial and class groups most frequently associated with stakeholders in the gentrification process are likely to influence readers’ assumptions about where gentrification occurs and who is most often involved, particularly for readers who have not had firsthand experience with gentrification (Eschholz et al., 2003; Gamson, 1988; Gamson & Modigliani, 1989; Sacco, 1995). Assumptions about the kinds of neighborhoods gentrification affects and the kinds of people moving into gentrifying neighborhoods are likely to influence the response to gentrification since whether it is seen as beneficial or detrimental change is influenced by racial assumptions about the process.

I find that gentrification was associated with race and class in ways that suggest common assumptions about where and how gentrification occurs, but also reflects particular local demographics. Black and poor residents were predominately associated with gentrifying neighborhoods across articles from both cities, as well as white and middle-class in-movers. However, articles from Baltimore also frequently associated working-class and white ethnic residents with gentrifying neighborhoods, reflecting the stable working-class population in the city and stable white ethnic enclaves that had been previously untouched by gentrification. Similarly, San Francisco articles often associated Latino and diverse residents with gentrifying neighborhoods, as well as upper-class in-movers, reflecting the prevalence of racially diverse neighborhoods in the city and the largest and growing class group in the city, the upper-class.

These findings suggest readers’ responses to gentrification might vary depending on the neighborhood and change that is depicted in a story. While determining which stereotypes are evoked in readers is beyond the scope of this particular study, the prior literature suggests that different racial and class depictions of residents of gentrifying neighborhoods and recent in- movers are likely to evoke different stereotypes in readers. Residents like blacks and the poor who are negatively stereotype. Similarly, the groups depicted as in-movers can evoke positive or negative responses to the change depending on racial and class stereotypes of the residents of the gentrifying neighborhood and the in-moving group. The influence these media portrayals may have on public opinion is particularly true for readers who are not exposed to gentrification firsthand (Eschholz et al., 2003; Gamson, 1988; Gamson & Modigliani, 1989; Sacco, 1995), which is likely true of many readers given their predominately middle- and upper- middle-class class background.1

1 See Chapter 2 for more information on readers. 31

Associations and Stereotypes

How race and class are associated with the gentrification process matters because Americans hold strong negative and positive stereotypes of racial and class groups (L. D. Bobo, Charles, Krysan, & Simmons, 2012; L. Bobo & Zubrinsky, 1996; Charles, 2006; Massey, 2007; Quillian & Pager, 2001; Sampson, 2012; Sampson & Raudenbush, 2004). These stereotypes can influence the assumptions that readers make about whether the neighborhoods affected by gentrification should be protected from the change and whether in-movers would be beneficial or detrimental to the communities affected. In this section, I briefly review how the stereotypes Americans hold about racial and class groups might influence perceptions about gentrification.

Most of the literature on neighborhoods specifically focuses on race, stereotypes, and neighborhoods (L. Bobo & Zubrinsky, 1996; Charles, 2006; Quillian & Pager, 2001; Sampson, 2012; Sampson & Raudenbush, 2004). Class stereotypes are likely to operate in similar ways by applying stereotypes of groups to the characteristics of a neighborhood, making some neighborhoods more attractive than others based solely on demographic characteristics. For example, we know that blacks are stereotyped as lazy and violent (L. D. Bobo et al., 2012; Gilens, 2009; Waters, 2009), which has translated to stereotypes about black neighborhoods as high in poverty and crime (L. D. Bobo et al., 2012; L. Bobo & Zubrinsky, 1996; Quillian & Pager, 2001; Sampson, 2012; Sampson & Raudenbush, 2004). Similarly, we might expect that poor neighborhoods would be negatively stereotyped as disinvested and neglected based on negative stereotypes about the poor (Gans, 1995; Katz, 1989; Kefalas, 2003; Kendall, 2011; Piven & Cloward, 1971). Thus, depictions of gentrification in black and poor neighborhoods is likely to receive a more positive response from readers due to the assumptions that these neighborhoods are less positive environments.

While blacks and the poor are generally stereotyped more negatively, whites, the working- class, and the middle-class tend to be stereotyped more positively. All three groups are generally seen as hard working, true Americans (L. D. Bobo et al., 2012; Kefalas, 2003; Kendall, 2011). Thus, gentrification in white and working-class neighborhoods is likely to be viewed as negative by readers due to assumptions that the individuals in these neighborhoods have worked hard to get where they are. Similarly, gentrification by white and middle-class in- movers is likely to elicit a positive response due to positive stereotypes about these groups’ work ethics and political involvement.

Finally, mixed reactions are most likely in regards to Latinos, Asians, and the upper-class due to the mixed stereotypes Americans generally hold of these groups. Latinos and Asians are both often stereotyped as foreigners, which comes with both positive and negative stereotypes (Chavez, 2013; Dávila, 2008; C. J. Kim, 1999; N. Y. Kim, 2007; Tuan, 1998). On the positive side, we often associate immigrants with hard work and strong values around family and education (Chavez, 2013). On the negative side, Latinos and Asians are often assumed to not assimilate to American culture (Chavez, 2013; C. J. Kim, 1999; N. Y. Kim, 2007; Tuan, 1998). Similarly, the

32 upper class are both positively stereotyped as individuals we should admire for their wealth and prestige, and negatively stereotyped for their reckless spending (Kendall, 2011). With these groups, the influence of their association with gentrification on readers is much harder to predict. For example, gentrification by the upper-class could be viewed positively due to admiration of their prestige, but could also be viewed negatively, particularly if these individuals are seen as undeserving of their wealth and less hard working than the people living in the gentrifying neighborhood. For Latinos and Asians, the response is likely to be influenced by whether they are depicted as in-movers and what neighborhoods they are depicted as moving into. For instance, the depiction of an Asian in-mover to a white neighborhood might be more likely to activate negative stereotypes about Asians than the depiction of an Asian in- mover to a black neighborhood due to the common stereotypes about the receiving neighborhood.

While none of these connections can be tested directly with the data in this study, these connections motivate the analysis below. In fact, findings from prior studies show that the association of specific racial and class groups with social problems like poverty lead to stereotypes of those racial and class groups being associated with the social problem (Gans, 1995; Gilens, 1996, 2009; Kendall, 2011).

Analyzing Newspaper Articles for Race and Class Associations

In this chapter, I analyze the 950 articles that use the term gentrification or one of its derivatives for references to race and class. Using MaxQDA, a qualitative data analysis software package, I conducted a text analysis to identify what race and class groups were mentioned, and conducted qualitative coding to identify what race and class groups were associated specifically with stakeholders in the gentrification process. As described further below, I analyzed results from both of these analyses in Stata, a statistical package, to identify overarching trends in the data by site.

For the text analysis, I used the extended lexical search tool in MaxQDA to find a list of key search terms that suggest a specific race or class group. Shown in Table 1, this included the names of countries of origin, racial and ethnic categories, and socio-economic and professional descriptors. I reviewed all results of the lexical searches and eliminated any references that were not applicable. For example, a search for “Asia” would also capture the term “Caucasian,” which was used to refer to white, not Asian. Additionally, search terms like “white” and “black” were frequently used to refer to colors such as the color of paint on a wall or the color of a piece of clothing. Similarly, the word “rich” was sometimes used to describe a decadent dessert. None of these uses of the search terms were included in the analyses presented here.

Table 1: Race and Class Text Analysis Terms

Race/Ethnicity Category Search Terms Asian Asia Chinese India Japan Korea Vietnam Filipino Philippines

Black Black African Caribbean Jamaica “West Indian” “West Indies” Latino Hispanic Latino Dominican Mexican Mexico “Puerto Rican” “Puerto Rico” "El Salvador" "El Salvadorian" “Central America” Guatemala Nicaragua Biracial Biracial “mixed race” multiracial Native American “Native American” “American Indian” White White Europe French France German Irish Ireland Italian Italy wasp Caucasian Polish Poland Greek Greece Unclear Diversity multicultural minorities “people of color”

In addition to the text analysis, I also qualitatively coded each article in MaxQDA to explain how race and class were associated with the gentrification process and when that occurred. The coding scheme I used identified when a stakeholder was associated with the gentrification process, whether their race and class were described, and, if so, what race and class description was included. This included codes for businesses, community organizations, recent in-movers, neighborhood residents, and other stakeholders including real estate agents, developers, and politicians.1 In this chapter, I focus on neighborhood resident and recent in-movers as the race and class depictions of these groups have implications for where readers think gentrification is occurring (or likely to occur), who is affected, and who is contributing to neighborhood change. In addition to coding for how race and class were associated with the stakeholders involved in gentrification, I also coded for the broader subject matter of the article to understand in what context race and class were associated with the gentrification process.

Finally, I converted my coding scheme to document variables in MaxQDA in order to export frequency counts and the presence of absence of the codes shown in Table 2 in each article for further analysis. In Stata, I created the descriptive statistics described below. In the findings sections of this chapter, I present the results of both the quantitative and qualitative analyses through descriptive statistics that summarize how race and class were associated with the gentrification process and qualitative examples that demonstrate how that association occurred.

1 See Appendix Table A for the full description of codes. 34

The Racial and Class Context

As discussed in Chapter II, Baltimore and San Francisco had distinct racial and class compositions over the period of study. While we should not expect the racial and class demographics of the cities to align perfectly with the demographics of representations of gentrification, understanding the racial and class demographics of neighborhoods in the cities overall provides useful context for identifying when certain racial and class groups may be over or underrepresented in reporting. A misalignment between actual racial and class demographics and representations of race and class in gentrifying neighborhoods does not mean that newspapers are misreporting. However, misalignment does suggest that some racial and class demographics may be overrepresented due to overreporting about gentrification in certain neighborhoods.

Figures 1 and 2 show the majority racial composition of census tracts in Baltimore (1) and San Francisco (2) between 1990 and 2014 based on data from the U.S. decennial Census and the American Community Survey. In Baltimore, most census tracts were majority black (between 57 and 66 percent). The other prevalent racial composition was majority white, which was 43 percent of all tracts in 1990, but decreased to 25 percent in 2014.

Figure 1: Tract Majority Racial Composition Baltimore

100 90 80 70 60 50 40 30 20 10 0 1990 2000 2010 2014 Majority white Majority black No majority

Source: 1980, 1990, and 2000 U.S. Census, and 2008-2012 and 2012-2016 American Community Survey data.

In San Francisco, most tracts were either majority white, had no racial majority, or were majority Asian over the period of study. The percent of majority white tracts decreased over 35 time, so that by 2014, they were equal to the percent of tracts that had no racial majority (38 percent). The percent of majority Asian tracts tripled during this period, ending at 22 percent in 2014. Finally, the small proportion of majority black and Latino tracts declined by about 80 percentage points each between 1990 and 2014.

Figure 2: Tract Majority Racial Composition San Francisco

100 90 80 70 60 50 40 30 20 10 0 1990 2000 2010 2014 Majority white Majority black Majority Asian Majority Latino No majority

Source: 1980, 1990, and 2000 U.S. Census, and 2008-2012 and 2012-2016 American Community Survey data.

Figures 3 and 4 show the proportion of census tracts with low, moderate, and high levels of poverty in each city. In Baltimore, poverty levels have been relatively stable over time as shown in Figure 3. Most tracts have been low poverty, followed by moderate poverty, and finally high poverty. Moderate poverty tracts had the most change over time with an increase from 27 percent to 39 percent of all tracts. This increase was associated with decreases of both high poverty and low poverty tracts.

Figure 3: Tract Level Poverty Baltimore

100 90 80 70 60 50 40 30 20 10 0 1990 2000 2010 2014

Low poverty Moderate poverty High poverty

Source: 1980, 1990, and 2000 U.S. Census, and 2008-2012 and 2012-2016 American Community Survey data.

Note: High poverty is defined as 40 percent or higher, moderate as 20-39.9 percent, and low as 0-19.9 percent.

Poverty levels have been similarly stable in San Francisco. However, the vast majority of San Francisco tracts have been low poverty, as shown in Figure 4. In fact, low poverty tracts have been 84 to 94 percent of all tracts in San Francisco between 1990 and 2014.

Figure 4: Tract Level Poverty San Francisco

100 90 80 70 60 50 40 30 20 10 0 1990 2000 2010 2014

Low poverty Moderate poverty High poverty

Source: 1980, 1990, and 2000 U.S. Census, and 2008-2012 and 2012-2016 American Community Survey data.

Note: High poverty is defined as 40 percent or higher, moderate as 20-39.9 percent, and low as 0-19.9 percent.

As suggested above, I will use these race and class characteristics to contextualize the analyses below that explain how race and class were associated with gentrification in newspaper articles.

References to Race and Class

References to class were more frequent overall and more frequent as descriptions of key stakeholders in the gentrification process across data from both sites. The text analysis found class terms in 52 percent of Baltimore articles and 56 percent of San Francisco articles, but racial terms in only 33 percent and 44 percent of Baltimore and San Francisco articles respectively. However, not all of these references to race and class included descriptions of stakeholders in the gentrification process. While about 97 percent of the articles included a stakeholder of interest, only 28 percent of stakeholders in the Baltimore data and 37 percent of stakeholders in the San Francisco articles were described racially. In contrast, 72 percent of all stakeholders in Baltimore articles and 70 percent in San Francisco articles were described by class.

Importantly, racial and class descriptions did not necessarily overlap when specified for stakeholders. Of the 725 articles that describe a stakeholder with racial or class descriptors, 38 only 239 (33 percent) included both racial and class descriptions. When considering specific stakeholder groups, the percentage is even lower. For example, only 27 percent of neighborhood residents and 17 percent of recent in-movers are described by both racial and class descriptors. The analyses presented below thus discuss how race and class are associated with the process separately.

The rest of this chapter focuses on how race and class were associated with gentrification through the depictions of residents of gentrifying neighborhoods and recent in-movers to those neighborhoods. I focus specifically on these two groups because they are most likely to define what readers think gentrification looks like in the world around them. Frequent depictions of neighborhoods of certain racial and class configurations with in-movers of certain racial and class backgrounds are likely to influence assumptions about where gentrification occurs, who it affects, and who is contributing to neighborhood change, particularly for readers who do not live in gentrifying neighborhoods. The association of specific racial and class groups with gentrification connects the process itself to long-standing racial and class-based stereotypes of the deserving and undeserving poor (Gans, 1995; Gilens, 1996, 2009; Katz, 1989) that can influence whether readers view gentrification as a positive or negative change in neighborhoods of different racial and class configurations.

Associating Race with Gentrification

While class is directly linked to the term gentrification through its definition, race and its relationship to gentrification is not clearly defined. While much of the recent gentrification literature has focused on black neighborhoods (Fallon, 2016), recent quantitative studies suggest that gentrification is actually less prevalent in black neighborhoods than white neighborhoods (Ellen & O’Regan, 2008; Hwang & Sampson, 2014; Owens & Candipan, 2018; Timberlake & Johns-Wolfe, 2016). Researchers are beginning to reconcile how selecting qualitative case studies may have skewed what we know about the gentrification process, but we still know little about how race is linked to gentrification in everyday life. In this section, I analyze how race is associated to gentrification in newspaper articles.

I find that across the articles from Baltimore and San Francisco, residents of gentrifying neighborhoods were more likely to be described racially than recent in-movers. When neighborhood residents were mentioned, 16 percent of Baltimore articles and 24 percent of San Francisco articles included a racial description. In contrast, 11 percent of Baltimore articles and 12 percent of San Francisco articles included racial descriptions for recent in-movers. The racial dynamics associated with the process predominately depicted black gentrifying neighborhoods with white in-movers in both sites, similar to the gentrification literature. However, articles from Baltimore also depicted white ethnic gentrifying neighborhoods and Latino recent in-movers, while articles from San Francisco depicted Latino and diverse gentrifying neighborhoods and Asian in-movers, reflecting differences in the racial demographics of both cities as described further below.

Black Neighborhoods and White In-Movers

When they were described racially, neighborhood residents were most likely to be described as black in articles from both cities. As shown in Figure 5, 42 percent of residents described in Baltimore articles and 35 percent of residents described in San Francisco articles were described as black. For example, a 2013 Baltimore City Paper article noted that, “The neighborhoods that make up [the new art district]…are among the first traditionally African- American neighborhoods to see such an influx of money, and many are worried that bringing in artists means bringing in white people (Woods, 2013). Similarly, a 1993 San Francisco Chronicle article described the “mixed blessing” of gentrification a poor, predominately black neighborhood: “‘It's going to change a hell of a lot,’ said Aunita Rochelle, a black woman who has lived in the area for 22 years. ‘This area used to be a real black community. It's not now. It's changed. And now it's really going to change’” (T. Walker, 1993a). Through descriptions of the gentrifying neighborhoods and of neighborhood residents, these articles explicitly associate gentrification with black neighborhoods.

Figure 5: Racial Descriptions of Residents by City

0 Baltimore San Francisco

white white ethnic black latino asian diverse

SOURCE: Author's calculations using a selection of newspaper articles published in the Baltimore Sun, Baltimore City Paper, San Francisco Chronicle, and San Francisco Examiner between 1990 and 2014.

Recent in-movers were also described similarly in articles from both cities. As shown in Figure 6, 41 percent of racial descriptions of in-movers in Baltimore articles and 46 percent in San Francisco articles were descriptions of white in-movers. For example, a 2005 Baltimore Sun article documents the tensions between long-term residents of a historically white, working- class neighborhood, and higher income in-movers: “For many years, [the neighborhood] was 40

virtually all white and hostile to integration. So, it is no surprise that some residents are resisting the new newcomers whose main difference is their income – not their skin color” (Reddy, 2005). In-movers to the neighborhood, like long-term residents there, were white, although of higher-income. Similarly, in a 1998 Chronicle article, a long-time business owner in a gentrifying neighborhood noted that, “’now the artists have moved away,’ Solorzano said. ‘Now, you’re starting to see a lot more white people, and you can’t find a parking spot’” (Levy, 1998b).

Figure 6: Racial Descriptions of Recent In-Movers by City

50 45 40 35 30 25 20 15 10 5 0 Baltimore San Francisco

white black latino asian diverse

SOURCE: Author's calculations using a selection of newspaper articles published in the Baltimore Sun, Baltimore City Paper, San Francisco Chronicle, and San Francisco Examiner between 1990 and 2014.

Thus, despite the marked difference in racial composition in Baltimore and San Francisco, the predominate image of residents of gentrifying neighborhoods and gentrifiers of those neighborhoods were the same. This commonality is particularly striking given how few black neighborhoods (and black residents for that matter) remain in San Francisco.

The Influence of Local Racial Differences

While the data show similar results for the most frequently used racial descriptor, other frequently used racial descriptors of residents and recent in-movers reflect the differences in the racial demographics of the two cities.

Residents. As shown in Figure 5, residents of gentrifying neighborhoods were much more likely to be described as white or as an ethnic white in the Baltimore data than the San Francisco 41 data.2 In fact, racial descriptions of whiteness (including both white and white ethnic) were almost as frequent as descriptions of black (41 percent). The prevalence of descriptions of white ethnics is a reflection of the continued presence of white ethnic enclaves in Baltimore City including Greek, Italian, and Polish neighborhoods. For example, a 1997 article from the Baltimore Sun reported how a previously working-class, white ethnic neighborhood had changed over time, note that the neighborhood “no longer is the impregnable white bastion it was then. The tightly-knit blocks of people of Polish, Italian, German or Czech descent are becoming a memory” (Pietila, 1997). Previously an area of white ethnic residents, the neighborhood was facing changes.

In comparison, the San Francisco articles were least likely to describe residents of gentrifying neighborhoods as white or white ethnics. Latinos was the second most frequently racial association with residents of gentrifying neighborhoods (24 percent). One 2013 article from the San Francisco Chronicle described the art of a long-time resident of a historically Latino neighborhood: “she has taken her memories and experiences and created ‘Homes for the Homies’…’The homies represent the Latinas; they remind me of my friends. I make the boxes because I love my city. The places here are big parts of my life, and things are changing,’ De Losa said” (Phillips, 2013). The Latino description was followed by diverse (17 percent) and Asian (13 percent). Ironically, the most frequently mentioned Latino neighborhood, the Mission, was in fact not majority Latino during the period of study.

While the results for the Baltimore data aligned with the racial composition of the city during the period of study, the San Francisco data reflected the opposite of what we might expect given the racial composition, which was majority white and Asian. This potential misalignment was in fact a reflection of racial composition of areas experiencing loud debates over gentrification. As Earl et al (2004) describe, news coverage is more likely to loud protest spectacles, which was the case in two neighborhoods that were frequently covered using the term gentrification, one a historically Latino and one historically black. Furthermore, given the extremely high socio-economic status of many San Francisco residents, it is likely that majority white and Asian neighborhoods are already predominately middle- or upper-middle class. Thus, gentrification by definition would not occur there.

In-Movers. In fact, the racial descriptions of recent in-movers in San Francisco aligns more closely with what one might expect given the race and class demographics of the city, while those of Baltimore do not. In the San Francisco data, recent in-movers were frequently described as Asian (24 percent). This aligns with the class demographics of the city’s growing Asian population. For instance, a 2008 San Francisco Chronicle article described the growing racial diversity in one gentrifying neighborhood due to the in-movement of whites and Asians: “Collins [a long-term resident] said…‘I like the new faces. A couple of years ago, you didn’t see a white woman or an Asian walking down Third Street. Now you do’” (McCormick, 2008). Racial change in this neighborhood was due in part to whites and Asians moving in.

2 References to white ethnics are counted separately from generic references to whites. 42

The Baltimore articles frequently described recent in-movers as Latino (28 percent). This racial descriptor is particularly interesting because while Latinos were a small, but growing population in Baltimore between 1990 and 2014, they were not a middle-income or wealthy group. Coverage of Latino in-movers to gentrifying neighborhoods is actually capturing a new ethnic enclave of Latino immigrants in a gentrifying neighborhood. In fact, many of the articles that describe Latinos as recent in-movers covers the clash between middle-class gentrifiers and these new low-income neighborhood residents. For example, a 2004 Baltimore Sun article depicts the tension around the growing Latino population in one gentrifying neighborhood near the waterfront: “Community advocates have taken notice of the throng [of workers], who they say are being exploited by employers not paying fair wages and taking advantage of immigrants from Latin America with limited knowledge of English and workplace rights. Neighborhood residents have voiced concerns, too…[complaining] to the city that the men are an ‘eyesore’” (Brewington, 2004). While these day laborers are certainly not gentrifiers, they contribute to the assumptions readers are likely to make about gentrification due to the stark contrast depicted between these Latino in-movers and the middle-class white in-movers occupying other parts of the neighborhood.

Associating Class with Gentrification

Class is inherent in the use of the term gentrification given its definition as the process by which neighborhoods change from predominately low-income to predominately middle-class. Yet, the term itself almost never defined in the newspaper articles analyzed here. The lack of an explicit definition of the term means that readers who are less familiar with the denotation of the term are likely to be influenced by the class dynamics associated with gentrification in the articles they read. While the articles analyzed here had a high proportion that defined the class background of stakeholders, class associations were not consistent across all stakeholder groups. In fact, long-term residents were described by class background over 77 percent of the time in data from both cities, but recent in-movers were only described by class 17 percent of the time in Baltimore articles and 19 percent of the time in San Francisco articles. Even though the class demographics of the in-movers can be assumed based on what the word gentrification means, the lack of explicit definitions in these articles makes the class dynamics unclear. Furthermore, the higher rate of association of the process with poor and working-class stakeholders through the depictions of residents of gentrifying neighborhoods is likely to make readers, who tend to be middle- and upper-middle-class, assume that gentrification is not a relevant issue for them. As explained in the sections below, class was generally associated with the gentrification process in ways that replicated the definition of the term: largely poor neighborhoods experiencing an influx of the middle-class. However, two key differences emerged that aligned with the local class context: gentrifying working-class neighborhoods in Baltimore and upper-class gentrifiers in San Francisco.

Poor Neighborhoods with Middle-Class In-Movers

In both the Baltimore and San Francisco data, there were two common class representations: Most residents of gentrifying neighborhoods were depicted as poor and most in-movers to gentrifying neighborhoods were depicted as middle-class. In fact, when residents were mentioned, 34 percent were described as poor in Baltimore articles and 48 percent in San Francisco articles, as shown in Figure 7. For recent in-movers, 79 percent were described as middle-class in Baltimore articles and 49 percent in San Francisco articles, as shown in Figure 8. These prevalent depictions reinforce the definition of the term gentrification itself as a process.

Figure 7: Class Descriptions of Residents by Site

0 Baltimore San Francisco

poor working-class middle-class upper-class

SOURCE: Author's calculations using a selection of newspaper articles published in the Baltimore Sun, Baltimore City Paper, San Francisco Chronicle, and San Francisco Examiner between 1990 and 2014.

For instance, a 2013 Baltimore City Paper article described the changes in neighborhood residents of the area surrounding a local market and the effects of those changes on the businesses: “The biggest change, however, was that on a recent weekday lunch hour the market was remarkably empty. It used to bustle with neighborhood people…I keenly felt the lack of the most colorful neighborhood denizens, the unemployed and unemployable, frequently short on teeth but long on hustle, camped out at Nick’s. I was mystified—where was everybody?” (Gienow, 2013). As the author describes, the neighborhood was previously home to the poor (”the unemployed and unemployable”) who were no longer frequenting the local market. Depictions of poor residents of gentrifying neighborhoods in San Francisco also often described whether poverty was visible. Given the city’s large homeless population, this included depictions of visible poverty through homelessness as well as the decline of the working poor. For example, a 1991 Chronicle article documented how the increased housing costs in the city and decrease in single room occupancy hotels have affected the rate of 44 homelessness: “But the poorest migrants, and natives too, were much less visible as recently as 15 years ago, mostly because there were many more cheap places to live then, lodgings often characterized as ‘flophouses’ that catered to poor, single men, homeless experts say…Since 1975, about 40 percent of the city's single room occupancy hotel rooms have disappeared” (McLeod, 1991). The changes in housing costs were contributing to rising rates of homelessness in the city. In fact, the article goes on to describe how the loss of low skill jobs reduced employment opportunities that would have helped keep some of these men housed as well.

Figure 8: Class Descriptions of Recent In-Movers by Site

0 Baltimore San Francisco

poor working-class middle-class upper-class

SOURCE: Author's calculations using a selection of newspaper articles published in the Baltimore Sun, Baltimore City Paper, San Francisco Chronicle, and San Francisco Examiner between 1990 and 2014.

These images of poverty and disinvestment surrounding residents of gentrifying neighborhoods were often juxtaposed with images of middle-class in-movers. For example, a 2010 Baltimore City Paper article described the role of homebuyers in the gentrification of one neighborhood: “In the 1960s, middle-class residents fled city neighborhoods…leading to blight and urban decay. Over the years, multiple groups and organizations have tried to revitalize the area…Most notable…is Adam Meister, whose Buy-a-Block Project urged prospective homeowners to buy up vacant homes on city blocks, renovate them, and reclaim the neighborhood. ‘More responsible people live on the block now,’ Meister says of the street he invested in” (Bright, 2010). The article goes on to describe these homebuyers as central to cleaning up the neighborhood. Representations of middle-class in-movers were also tied to new developments touted as exciting investments in downtown neighborhoods in both cities. For instance, a 1998 Chronicle article described the construction of a fitness club, hotel, and 45 condos in the downtown area that targeted middle-class in-movers to the city: “Brown's vision of a swinging 24- hour Downtown South comes as more and more young professionals and frequent visitors seek to live amid the excitement and glamour of an urban setting” (Levy, 1998a). This new development was in fact catering to the middle-class professionals seeking to move into San Francisco.

Class Association and Local Demographics

While the most residents of gentrifying neighborhoods and recent in-movers were described similarly as low-income and middle-class across the two cities, there were two key differences in the depictions by city that reflect differences in the class demographics of the two sites. Residents of gentrifying neighborhoods in Baltimore were frequently described as working-class and in-movers to gentrifying neighborhoods in San Francisco were frequently described as upper-class. As described further below, this reflects differences in the class composition of the cities, as well as the exposure to gentrification in each city prior to the study period.

Working-Class Residents. While 34 percent of residents in gentrifying neighborhoods were described as poor in Baltimore articles, 39 percent were described as working-class (see Figure 7). In contrast, 29 percent of residents were described as working-class in San Francisco articles, compared with 48 percent described as poor. The larger representation of the working-class in the Baltimore articles reflects in part a larger working-class population overall. While San Francisco’s lower-middle-class population declined from 26 percent in 1980 to 13 percent in 2014, Baltimore’s remained relatively stable starting at 27 percent in 1980 and ending at 24 percent in 2014.3 The other contributing factor to the larger representation of working-class neighborhoods in Baltimore is the more limited prior exposure to gentrification. Because San Francisco experienced gentrification in select neighborhoods beginning as early as the 1960s (Alejandrino, 2000; Casique, 2013; Godfrey, 1988; Hartman, 2002; Mirabal, 2009; Nyborg, 2008; Solnit & Schwartzenberg, 2002), most of the city’s working-class neighborhoods were touched by gentrification by at least the early 2000s. In contrast, gentrification in the 2000s in Baltimore was mainly occurring in working-class neighborhoods (Koenig, 2004; Merrifield, 1993). We see one such depiction in a 1990 Baltimore Sun article about the role of development in gentrification in a working-class, waterfront neighborhood: “Ida May Raynor, 83, has never heard of a concierge. In working-class Canton, where she was born and raised, the factory workers never had such servants to buy their groceries or get their cars fixed” (Jacobson, 1990). The article juxtaposed the long-term, working-class factory workers who previously composed the majority of residents in the area with the wealth of recent in-movers who lived in luxury condos with concierges and owned boats.

Super-Gentrification. In the San Francisco articles, the upper-class was mentioned just as frequently as the middle-class as recent in-movers to gentrifying neighborhoods (49 percent each). In contrast, only 15 percent of recent in-movers were described as upper-class in the

3 See Chapter 2 for more details. 46

Baltimore data (see Figure 8). As described in Chapter 2, part of this difference is due to the large increase in the affluent in San Francisco from 13 percent in 1990 to 28 percent in 2014. By 2014, San Francisco’s largest income group was the upper-income. In contrast, Baltimore’s upper-income went from 5 percent to 8 percent over the same period of time. With this large and growing proportion of affluent residents, gentrification in San Francisco was also changing to affect the middle-class as even higher income in-movers moved to city neighborhoods (Centner, 2008). Thus, newspapers depicted gentrification that affected and involved its readership. For example, a 1999 Chronicle article described the backlash to the in-movement of “wealthy dot-com entrepreneurs” to neighborhoods across the city: “The cultural fault line nowadays is a nonviolent backlash against the influx of wealthy dot-com entrepreneurs…Almost anything that can be blamed on these affluent newcomers is -- long lines at the movies, parking problems” (Weiss, 1999). Like this example, most of these depictions of upper-class in-movers focused on the employees in the tech industry.

Conclusion

Regardless of the perceptions and assumptions readers hold, the news media explicitly associates gentrification with specific racial and class groups through the description of residents of and recent in-movers to gentrifying neighborhoods. The predominant depictions in both Baltimore and San Francisco were of poor and black gentrifying neighborhoods with white and middle-class in-movers. However, local differences in racial and class demographics led to other distinct representations. In particular, Baltimore newspapers frequently depicted ethnic white and working-class gentrifying neighborhoods and Latino in-movers. Similarly, the San Francisco articles frequently depicted Latino and diverse gentrifying neighborhoods and upper- class in-movers. These differences reflect distinct persistent and changing city demographics.

While this study cannot directly explain how these images affect readers’ perceptions and assumptions about gentrification, the prior literature suggests that frequent depictions of specific racial and class groups with a social problem leads stereotypes associated with those groups to be applied to that social problem (Gans, 1995; Gilens, 1996, 2009; Soss et al., 2011). Thus, the negative and positive stereotypes that readers hold about the groups predominately depicted as gentrifiers and the gentrified are likely to influence their read of gentrification as a social issue. I shed light on this issue in Chapter 5 through analyses of how the articles spin whether gentrification is a positive or negative change depending on their racial and class descriptions of gentrifying neighborhoods.

In the next chapter, I investigate whether these race and class associations are linking specified race and class groups to the same kind of neighborhood change. That is, I answer whether gentrification was described as a similar type of change in articles about poor and black gentrifying neighborhoods as in articles about working-class, white ethnic, Latino, and diverse neighborhoods.

Chapter 4: Gentrification or Some Other Neighborhood Change: Categorization

Constructing a social problem involves defining the who, what, when, why, and how (Hilgartner & Bosk, 1988). While the prior chapter looked at who, I address the “what” of gentrification in this chapter. What exactly do newspapers represent as gentrification? What kinds of neighborhood changes are categorized as gentrification? And how does that vary depending on the demographics of the neighborhood labeled gentrifying?

While the term gentrification has had a relatively consistent definition as the process by which a neighborhood changes from predominately low-income to predominately middle-class in the academy, we know less about how the term has been applied in everyday life (Lees Representing). In this chapter, I compare the use of gentrification to urban renewal to explain how the term has been used to categorize neighborhood upgrading, which includes the physical improvement of a neighborhood and the increase in the socioeconomic status of neighborhood residents. Because we know that race and class influence how labels are applied to describe people, places, and phenomenon (Gilens, 1996, 2009; Hall, 1997), I analyze how the race and class demographics of gentrifying neighborhoods are associated with the kinds of upgrading categorized as gentrification.

Overall, I found that residential and commercial development and change associated with “natural” market processes of supply and demand were more likely to be categorized as gentrification, while state-led development projects and new build development were more likely to be categorized as urban renewal. While this finding reflects in part the historic use of the term urban renewal to describe development led by cities and funded by the federal government (Hirsch, 1993), it also reflects the use of the term gentrification to describe free market processes. Processes that are often protected under neoliberalism to maintain a “free” market arena (Hackworth, 2007). This link between gentrification and the free market suggests that policy solutions to address the negative effects of gentrification or to slow the process may be slow to be introduced and viewed as problematic or unnecessary because they would inhibit the free market.

The analyses by race and class show that the gentrification is socially constructed in the news media in ways that reflects historic patterns of disinvestment and current patterns of uneven investment by race and class, particularly in the San Francisco articles due to the long period of exposure to gentrification and the escalation of gentrification over the period of study. Thus, I found that black and poor neighborhoods, which have had fewer investments in commercial space historically, were less likely to have commercial development or change categorized as gentrification, while commercial development or change in working-class neighborhoods in Baltimore was more likely to be categorized as gentrification. Similarly, the use of gentrification in the San Francisco data reflected differences in how neighborhood investment was unfolding along race and class lines across the city. Gentrification was used more often to categorize residential development and change in diverse neighborhoods involving developers, real estate

agents, and higher income in-movers because that was the predominate means by which upgrading was occurring. Similarly, new development and state-led development in black and poor neighborhoods were more likely to be categorized as gentrification, reflecting the use of state-led development to upgrade black and poor neighborhoods in San Francisco through such projects as HOPE VI and HOPE SF.

These findings demonstrate that how the news media constructs gentrification reflects the uneven and unequal patterns of development that have been a part of urban development for much longer than the process of gentrification (Smith). While these representations are unlikely to contribute to the continuation of uneven development directly, they could influence how readers view gentrification with the possibility that the representations suggest that gentrification is a natural process that is a normal outcome of a free housing market.

The Back Story on Gentrification and Urban Renewal

As explained in Chapter 1, when a word, term, or phrase is used to describe a certain event, action, phenomenon, or process consistently, it creates an association between that word, term, or phrase, and that event, action, phenomenon, or process (Gamson, 1988; Hall, 1997; Hilgartner & Bosk, 1988; Lamont, Beljean, & Clair, 2014; Zerubavel, 1993, 1996). In this chapter, I aim to explain what kinds of events, action, and phenomenon are associated with gentrification, a process I call categorization, and how that compares with urban renewal. In this section, I provide background on both terms as context for the analyses to come.

The Category of “Urban Renewal”

“Urban renewal” has a history that is closely tied to state-led development planning. In fact, the term was introduced through federal legislation in the mid-1950s (Hirsch, 1993). The original legislation for the policies around urban renewal was the Housing Act of 1949, which made legal the use of eminent domain and provided subsidies for cities to clear “slums” (Hartman, 2002; Hirsch, 1993). The policy specifically targeted blight in slums and referred to slum clearance and redevelopment (Hirsch, 1993). The Housing Act of 1954 replaced that language with “urban renewal” and expanded the qualifying projects to include broader redevelopment plans, allowing for larger projects to reorganize existing communities to make way for centralized downtown areas (Hirsch, 1993). However, the legislation was predominately used to relocate black and poor communities from valuable real estate in downtown areas, leading to the nickname of “Negro removal” (Hartman, 2002; Hirsch, 1993; Kusmer & Trotter, 2009; Sugrue, 1996).

The Category of “Gentrification”

While the scholarship on the use of the term gentrification in everyday life is relatively limited (Lees, 1996), the prior literature is helpful for understanding how the term has been used within the academy (Brubaker & Cooper, 2000). Coined by the sociologist Ruth Glass (1964),

“gentrification” was initially used to describe residential changes from working-class residents to middle-class in inner-city neighborhoods. While there are debates about whether displacement should be a part of the definition of gentrification and how gentrification unfolds (Brown-Saracino, 2010, p.; Lees et al., 2008), there is general agreement that the term applies to the process by which a neighborhood changes from predominately low-income to predominately middle-income residents, which includes an increase in housing costs. However, the term has also been expanded in its application to cover a variety of neighborhood changes by the addition of adjectives that specify the type of gentrification a neighborhood is experiencing (Brown-Saracino, 2010; Lees et al., 2008).

These types of gentrification are arguably all a part of the gentrification process despite the lexical delineations made in the literature. In fact, “pioneer gentrification” is often used to refer to the early in-movers to gentrifying neighborhoods who are often higher in class standing through education, but not much more affluent in terms of income, including bohemians, artists, and (sometimes) hipsters (Dávila, 2004; Freeman, 2006; Lees et al., 2008; Peterson, 1985; N. Smith, 1996; Zukin, 1989). Researchers describe the commercial changes that come with changes in businesses catering to middle-class clientele rather than low-income as “commercial gentrification” (Hyra, 2008; Maurrasse, 2006; Ocejo, 2011; Zukin, 1989). Studies of gentrification that has come with new development catering to higher income residents that may not directly displace lower-income residents call this “new-build gentrification” (Davidson & Lees, 2010; Shaw, 2002; N. Smith, 1996). When development is orchestrated and implemented by the government, such as HOPE VI, it is called “state-led gentrification” (Bridge et al., 2012; Hyra, 2008). Studies of gentrification by college students in neighborhoods surrounding college campuses refer to “studentification” (D. Smith, 2005). Gentrification driven by commercial development catering to tourists is called “tourist gentrification” (Gotham, 2010). And finally, the escalation of gentrification from change from middle-class to upper-class residents is called “super-” or “hyper-gentrification” (Centner, 2008; Lees, 2010).

These terms mark the expansion of the use of gentrification in the academic literature beyond simply the process of a neighborhood’s residential composition changing. However, we know little about how this compares to the use of the term in the common vernacular. Because the academic literature is largely inaccessible to non-academic audiences, the news media is a particularly important institution in defining what kind of neighborhood change is categorized as “gentrification.”

What Might We Expect?

Based on the wide application of gentrification in the academic literature, the term could be applied just as widely to describe more than just residential change. However, it is unclear both how many of the gentrification hyphenated terms outlined above will be categorized as “gentrification” in the news coverage. In contrast, the history of the term urban renewal makes it likely that the term will be more often applied to development led by the government.

In terms of the influence of race and class composition, it seems likely that the use of the term gentrification will vary by the demographic composition of gentrifying neighborhoods due to patterns of uneven and unequal development (N. Smith, 2010). That is, the type of change that is categorized as gentrification will reflect the types of upgrading seen in the neighborhood regardless of racial and class demographics.

Data and Methods

This chapter draws on the full corpus of articles collected that describe some form of neighborhood change including the search terms gentrification and its derivatives as well as the following search terms: urban renewal, neighborhood or community revitalization, neighborhood or community redevelopment, neighborhood or community improvement, and neighborhood change. As described in Chapter 2, this includes 2,223 articles. Most of the analyses in this chapter focus on the two mostly frequently used search terms: gentrification (950 articles) and urban renewal (826 articles).

The data presented in this chapter includes information compiled from the newspaper articles by myself and a team of undergraduate researchers. We read each article and entered information into an Excel spreadsheet including the variables analyzed in this chapter, the type of change described in the article: residential change or development, commercial change or development, new development, state-led development, and amenities. Residential change or development includes the description of changes in a neighborhood’s demographics and the development of new residential buildings including apartment buildings, lofts, and single-family homes. Similarly, commercial change or development includes the description of changes in who is using commercial spaces and the development of new commercial spaces. New development includes any new construction of development, which was always used with residential or commercial change or development. State-led development captured development primarily financed and implemented by a city, state, or federal government agency. Finally, amenities captured beautification or improvement projects including bike lanes, crosswalks, sidewalks, parks, planting trees, gardens, libraries, recreation or community centers, and providing security. We coded any change that did not fall into one of these five categories as other change. Each article could describe one or all of these changes. For example, an article might describe the approval of the construction of an apartment building in a gentrifying neighborhood. This article would be coded as new development and residential change or development.

To analyze the data, I compiled all of the spreadsheets using Stata, a statistical analysis software package, reviewed and resolved any duplicate records, and cleaned the variable values. Additionally, I merged in data from qualitative coding in MaxQDA, a qualitative data analysis software program, that identified the race and class background of neighborhood residents described in articles using the term gentrification when mentioned. This information indicates how race and class have been associated with gentrifying neighborhoods within the

same article. I present the results of these analyses below with descriptive statistics and illustrative qualitative examples.

The Categorization of Neighborhood Change

During the period of study, Baltimore and San Francisco were experiencing different levels of exposure to neighborhood upgrading, which strongly influenced whether and to what extent neighborhood change as categorized as gentrification or urban renewal in newspaper articles. I found that the use of the term gentrification and how it was applied reflected the kinds of change the cities were experiencing and how those changing were unfolding. In Baltimore, neighborhood upgrading was often driven by the City’s Planning Department, which led to more frequent use of the term urban renewal than gentrification. In contrast, San Francisco neighborhoods were often experiencing change driven by real estate agents, developers, and wealthy in-movers, which led to the more frequent use of gentrification. Thus, while the terms gentrification and urban renewal could describe similar changes and were even used to describe the same redevelopment projects, gentrification was applied in distinct ways.

Across both cities, most neighborhood upgrading was categorized as gentrification or urban renewal as shown in Figure 1. The most frequently used term was urban renewal in the Baltimore articles (48 percent) and gentrification in the San Francisco articles (74 percent). This difference reflects how neighborhood upgrading was unfolding in the cities. Most of the upgrading in Baltimore was driven by the Planning Department, thus a higher use of the term urban renewal than in San Francisco where most upgrading was driven by the housing market, which made the use of gentrification more likely.

Figure 1: Frequency of Terms by Site

100 90 80 70 60 50 40 30 20 10 0 Baltimore San Francisco gentrification urban renewal revitalization improvement redevelopment change

SOURCE: Author's calculations using a selection of newspaper articles published in the Baltimore Sun, Baltimore City Paper, San Francisco Chronicle, and San Francisco Examiner between 1990 and 2014.

Despite these differences, the term gentrification was used similarly across the two cities. When neighborhood upgrading was categorized as gentrification, it was predominately used to describe residential and commercial development or change, as shown in Figure 2. While new development, state-led development, and the development of amenities were also described as gentrification, each of these categorizations were used in about a quarter of the articles or less.

Figure 2: Type of Change Described as Gentrification by Site

100 90 80 70 60 50 40 30 20 10 0 residential commercial new state-led amenities other change change change development change

Baltimore San Francisco

SOURCE: Author's calculations using a selection of newspaper articles published in the Baltimore Sun, Baltimore City Paper, San Francisco Chronicle, and San Francisco Examiner between 1990 and 2014.

The term urban renewal was used more often to categorize state-led development and new development than the term gentrification. Figure 3 compares the types of neighborhood upgrading categorized as gentrification with those categorized as urban renewal. In both sites, gentrification was used more frequently used to categorize residential change or development than urban renewal. In contrast, urban renewal was more likely to be used to categorize state- led development and new development. The pattern was particularly stark in the San Francisco articles where only 4 percent used the term to describe a state-led development compared with 42 percent of articles using the term urban renewal.

Figure 3: Type of Change by Search Term and Site

100 90 80 70 60 50 Percent 40 30 20 10 0 amenities amenities other change other change other state-led change state-led change state-led new development new development residential change residential change residential commercial change commercial change commercial Baltimore San Francisco

gentrification urban renewal

SOURCE: Author's calculations using a selection of newspaper articles published in the Baltimore Sun, Baltimore City Paper, San Francisco Chronicle, and San Francisco Examiner between 1990 and 2014.

As these findings suggest, the use of the phrase urban renewal was frequently associated with development involving the city government. For example, a 2000 Baltimore Sun article described the city’s role in acquiring properties for an expansion of the Johns Hopkins medical campus: “The proposed legislation, scheduled to be introduced when the City Council returns from summer recess Monday, would amend the urban renewal plan for the Middle East [neighborhood] area just north of the medical campus, which includes the hospital and schools of medicine, nursing and public health…giving the city condemnation powers over the properties” (Siegel, 2000). The City was actively involved in this development project for Hopkins through acquiring land, orchestrating the relocation of residents and businesses, and subsidizing the project. Similarly, a 2008 San Francisco Chronicle article describes the City’s role in demolition and rebuilding of a public housing development: “The San Francisco Housing Authority, which is funded by the U.S. Department of Housing and Development, owns 53 public housing developments…Eight of those developments - comprised of 2,500 units - are so decrepit they need to be rebuilt” (Knight, 2008). Similar to the Baltimore example, the SFHA was orchestrating a large-scale redevelopment project, which the article referred to as urban renewal.

Varied Categorization by Race

To further explore variations in the kinds of change categorized as gentrification, I analyzed the type of change described by the racial description of neighborhood residents. The patterns of categorization by race reflect in large part the realities of uneven development and differences in zoning in neighborhoods by race, as described further below. This reflection of uneveness surfaces through the use of gentrification to categorize commercial development and change in white ethnic neighborhoods of Baltimore and residential development or change and state-led and new development across diverse and black neighborhoods in San Francisco.

Baltimore

Categorization as gentrification varied little in the Baltimore data by neighborhood race with the exception of commercial development or change, as shown in Figure 4. Gentrification was most frequently used to categorize commercial development or change when neighborhood residents were described as white ethnics (59 percent). This finding is likely driven by differences in the presence and type of businesses present in black, white, and white ethnic neighborhoods. Black neighborhoods tended to have fewer commercial spaces overall, and so commercial change was less likely to appear in news reporting in general. White neighborhoods may have had similar amounts of commercial space to white ethnic neighborhoods; however, those businesses were less likely to connect culturally with the fabric of the community as with the white ethnic businesses that were primarily the focus of reporting on commercial gentrification in white ethnic neighborhoods. In fact, white ethnic restaurants were frequently mentioned in articles as spaces that preserved the community’s history and identity, which is likely why there was more coverage of their closure.

Figure 4: Type of Change Described as Gentrification by Residents' Race Baltimore

100 90 80 70 60 50 40 30 20 10 0 residential change commercial change new development state-led change

black white white ethnic undefined

SOURCE: Author's calculations using a selection of newspaper articles published in the Baltimore Sun and Baltimore City Paper between 1990 and 2014.

For example, a 2013 Baltimore Sun article covered changes that residents and businesses were experiencing in a white ethnic neighborhood near downtown: “[T]he latest Little Italy eatery to close…joins other familiar eateries…that have closed in recent years” (Wells & Marbella, 2013). The restaurants that dominated the neighborhood’s commercial businesses in the past were not surviving changes in the neighborhood and surrounding areas. In fact, the article notes that most “have been nearly swallowed up by gentrification or other forces” including the development of neighboring downtown areas (Wells & Marbella, 2013).

San Francisco

In contrast with Baltimore, there was more variation in the types of change described as gentrification by race in the San Francisco data. These findings reflect differences in how development and change were unfolding in the city’s landscape, which varied by the race and class composition of the neighborhoods affected. In particular, changes in the few predominately black communities remaining in the city were driven by state-led development (Brahinsky, 2014a; Dillon, 2011, 2014), while predominately white, Latino, and diverse neighborhoods were experiencing change driven by the processes of residential gentrification including developers, businesses, and higher-income in-movers.

As shown in Figure 5, the term gentrification was most frequently used to categorize residential development or change when neighborhood residents were described as diverse (78 percent). 57

For example, a 1994 Chronicle article described how a gentrifying neighborhood’s “Exotic mix of cultures” was attracting gentrifiers: “Once a haven for junkies and the down and out, the area…has emerged as one of the most vibrant and diverse quarters of the city…It is multiethnic and arts-oriented, providing quality, affordable food and entertainment to crowds that crave a savory mix out of life” (Levy, 1994). The diverse mix of residents was a draw for “kinetic young crowds” moving to the area, which created residential change (Levy, 1994).

Figure 5: Type of Change Described as Gentrification by Residents' Race San Francisco

100 90 80 70 60 50 40 30 20 10 0 residential change commercial change new development state-led change

asian black latino white diverse undefined

SOURCE: Author's calculations using a selection of newspaper articles published in the San Francisco Chronicle and the San Francisco Examiner between 1990 and 2014.

Gentrification was used to categorize both new development and state-led development more frequently when neighborhood residents were described as black. Many of these articles were around state-led redevelopment projects in one of the few remaining historically black neighborhoods in the city. For example, a 1997 Chronicle article described the concerns that community members had about a City proposal for “a 75,000-seat stadium, a 30-screen movie theater and acres of retail outlets” (Levy, 1997). As the article goes onto to describe, the city was working actively to get community support behind the project: “Residents in the predominantly black neighborhood have heard promises of bright futures before -- but say few have ever been kept…The mayor and other city officials say this project is different” (Levy, 1997). Thus, unlike gentrification in diverse neighborhoods of San Francisco, black neighborhoods were more likely to face state-led and new development projects rather than forms of the classic model of residential gentrification.

These racial differences in the use of the term gentrification are in fact the result of differences in how and where development occurs based on race. Because gentrification has taken on a wide social meaning, as demonstrated by the analysis above, it has been used to categorize neighborhood upgrading in ways that captures racial differences in where and how upgrading occurs. This reflection of reality is also true for measures of class, as explained below.

Varied Categorization by Class

Similar variations in categorization emerged by class composition, particularly in the San Francisco data. Like differences by race, these variations corresponded with the uneven form in which neighborhood upgrading manifested in the cities’ neighborhoods over the period of study. Thus, I found differences in categorization for working-class neighborhoods in Baltimore and poor neighborhoods in San Francisco. While the differences were generally less distinct than those seen for racial composition, they support the finding that the categorization of a type of neighborhood upgrading as gentrification varies because of differences in how upgrading occurs.

Baltimore

As with race, the type of changes categorized as gentrification were generally similar regardless of the class descriptions of neighborhood residents. As shown in Figure 6, the only variations that emerged were when residents were described as working-class. Gentrification was more likely to be used to categorize commercial development or change and new development when residents were described as working-class. While these differences were smaller than the racial analysis, these differences reflect the same patterns of uneven development in neighborhoods by class during the period of study. As discussed in Chapter 2, Baltimore was experiencing dramatic investment in working-class neighborhoods around the downtown waterfront including investments in tourism and larger commercial developments during the period of study. Given the prior use of these spaces for manufacturing, many of these developments were new build, rather than renovation or re-purposing. While these types of developments did occur in other areas of the city, they were less frequent in poor and middle-class communities.

Figure 6: Type of Change Described as Gentrification by Residents' Class Baltimore

100 90 80 70 60 50 40 30 20 10 0 residential change commercial change new development state-led change

poor working-class middle-class undefined

SOURCE: Author's calculations using a selection of newspaper articles published in the Baltimore Sun and Baltimore City Paper between 1990 and 2014.

One example of this is a 2008 Baltimore Sun article that described redevelopment in a working- class neighborhood: “For most of the 45 years that Colleen Rosenbach has lived in Locust Point, her neighbor was a hulking grain elevator…Now, that silo is being turned into upscale condominiums…Struever Bros. proposed a 15-story residential tower, along with office, apartment and condominium buildings” (Kiehl, 2008). Projects that replaced or re-purposed formerly manufacturing buildings were common in this part of Baltimore City during the period of time as developers expanded their investments around the waterfront harbor area.

San Francisco

Slight differences in categorization by class emerged in the San Francisco articles predominately when neighborhood residents were described as poor and upgrading changes categorized as gentrification were commercial development or change, new development, or state-led development. As shown in Figure 7, gentrification was least likely to be applied to categorize commercial development or change when neighborhood residents were described as poor. In contrast, gentrification was more likely to be used to categorize new development and state- led development when residents were described as poor.

Figure 7: Type of Change Described as Gentrification by Residents' Class San Francisco

100 90 80 70 60 50 40 30 20 10 0 residential change commercial change new development state-led change

poor working-class middle-class undefined

SOURCE: Author's calculations using a selection of newspaper articles published in the San Francisco Chronicle and the San Francisco Examiner between 1990 and 2014.

While the differences described here are slight, they reflect differences in the patterns of development and zoning in the city by class composition. Poor neighborhoods were less likely to have commercially zoned spaces and were more likely to be experiencing change through city financed and executed development during the period of study. The predominance of state-led development was due to the lack of interest in poor neighborhoods among privately funded developers due to small or no returns to investment.

For example, a 1993 Chronicle article documented the redevelopment of a housing project building led by the City: “When the San Francisco Housing Authority bulldozes the blighted Hayes Valley Housing Projects and replaces them with townhouses, 290 families will have to move temporarily - and more than 170 will never get to come back” (T. Walker, 1993b). This public housing redevelopment project was funded and implemented by the City to replace low- income housing with a mixed-income development, a project that would not happen in a middle-income community due to the segregation of public housing to low-income neighborhoods.

While the differences that emerged by class were small across both cities, they reinforce that the term gentrification is used to categorize upgrading in the form that it is happening on the ground. Thus, neighborhoods that are not experiencing upgrading through commercial development and change are less likely to have the term applied to categorize commercial 61

development and change. Similarly, areas that are experiencing state-led development were more likely to have the term gentrification used to describe that change.

Implications of Categorization

The use of the term gentrification to categorize neighborhood upgrading was generally applied to residential and commercial development and change across data from both cities. In contrast, urban renewal more frequently used to categorize new development and state-led development. While the use of gentrification was similar across in the Baltimore and San Francisco data overall, there were variations that emerged based on the description of the gentrifying neighborhood. In Baltimore, gentrification was used more often to categorize commercial development and change in white ethnic and working-class neighborhoods. Similarly, in San Francisco, gentrification was used more often to categorize residential development and change in diverse neighborhoods and new development and state-led change in black and poor neighborhoods, but least likely to be used to categorize commercial development or change in poor neighborhoods. Importantly, there was more variation in categorization along both race and class dimensions in San Francisco because the city experienced a dramatic escalation of gentrification over the period of study and the city’s exposure to gentrification began earlier than in Baltimore. That is, the term gentrification appears to be liberally applied to describe many forms of upgrading in the San Francisco data because gentrification has a longer history and has been more severe.

Although the differences were largest based on racial descriptions of gentrifying neighborhoods, both the race and class findings reflect the realities of how development and neighborhood upgrading were unfolding in the cities along dimensions of race and class. In particular, the findings highlight (1) how past uses influence present use patterns through zoning and (2) how race- and class-based preferences for neighborhood of residence affects how gentrification unfolds. To the former point, the use of gentrification to categorize commercial development or change was focused on neighborhoods with more commercial zoning where businesses could change and more commercial development could occur. Working-class and white neighborhoods had more commercially zoned spaces than poor and black neighborhoods, thus gentrification was used more often to categorize commercial development and change in working-class and white neighborhoods. To the latter, gentrification was used more frequently to categorize new development and state-led development in black and poor neighborhoods of San Francisco because gentrification was unfolding through state-led development plans in those areas. While housing prices sky rocketed across the city during the period of study, much of the price escalation was occurring outside of the few remaining high poverty and predominately black neighborhoods in the city. Poor and black neighborhoods were experiencing upgrading through state intervention like

HOPE VI1 rather than residential gentrification where developers, real estate agents, and higher-income homebuyers were choosing to invest in those neighborhoods. These findings reflect the realities of the housing market, which dictates investment based on potential profit.

These differences in turn explain variations in the use of gentrification and urban renewal. While the same development project could be categorized as gentrification and urban renewal, gentrification was used more frequently to categorize residential and commercial development and change that was implemented by developers and higher income in-movers. The term thus encompassed neighborhood changes that were less subject to processes of community approval. That is, gentrification was often used to describe changes that are “natural” and driven by market forces of supply and demand. Development projects that were categorized as urban renewal were subject to approval and regulations by both city agencies and, oftentimes, the communities affected. Thus, the categorization of neighborhood upgrading as gentrification indicates a course of change without constraint.

While the categorization of neighborhood upgrading as gentrification might indicate a need for government intervention, it seems more likely that the term itself is indicating a process that cannot be controlled, a hypothesis I will explore further in the conclusion chapter. We know little about whether politicians and voters think it’s possible to control gentrification with policy, but these findings suggest that gentrification may be seen as a process whose course cannot be stopped.

1 HOPE VI is a federal housing development program sponsored by the Department of Housing and Urban Development that provides Public Housing Authorities funding to demolish dilapidated public housing buildings and rebuild them as mixed-income housing. 63

Chapter 5: Gentrification as Improvement, Gentrification as Harm: Spin

Objectivity is a central tenet of journalism (Gamson, 1988; Gamson & Modigliani, 1989; Gans, 2004; Gilens, 1996; Gitlin, 2003; Hallin & Mancini, 1984). While the tenet means that journalists should not take a clear side on an issue, in practice it means reporting on a pro and con side of an issue to present a “balanced” perspective (Gamson, 1988; Gans, 2004). Despite the goals of objectivity and balance, we know that journalists end up providing a certain “spin” on an issue that defines whether it should be seen in a positive or negative light (Gamson, 1988; Gamson & Modigliani, 1989; Gilens, 1996; Gitlin, 2003; Hallin & Mancini, 1984). In this chapter, I analyze the spin in articles about gentrification and how that varies by the race and class composition of gentrifying neighborhoods.

Understanding the spin on gentrification matters because there are negative implications for long-time residents and long-standing businesses in gentrifying neighborhoods without policy protections. Due to the housing market’s response to investment in a neighborhood by developers and homebuyers, long-time residents and long-standing businesses can experience increased rents that can result in displacement. While homeowners are more protected than renters, they can still experience financial burdens that lead them to leave the neighborhood due to increased property taxes. Finally, long-standing businesses can experience increased competition and a decline in their customer base as new businesses move into the neighborhood and long-time residents move to other parts of the neighborhood or to other neighborhoods. Even when gentrification occurs in previously undeveloped or unused areas through new development, it has implications for surrounding neighborhoods including increased property values and rents due to proximity to investment. While they may not be able to stop gentrification, cities have policy tools that can be used to protect long-time residents and long-standing businesses to ensure that as change occurs in gentrifying neighborhoods and neighborhoods near gentrification that displacement is not the end result. Whether these tools are put in place depends on whether gentrification is viewed as an improvement to a neighborhood or as a harm.

In this chapter, I analyze how gentrification is valued in 667 articles about residential change, residential development, or property prices. In particular, I look at what concerns and benefits of gentrification are depicted, who those concerns and benefits affect, and how the spin on gentrification varies depending on the description of race and class demographics of gentrifying neighborhoods. I find that gentrification is given a positive spin overall in Baltimore and a negative spin in San Francisco, but that this spin varies in ways that align with common race and class stereotypes. Gentrification in black and poor neighborhoods had a more positive spin in articles from both cities, reinforcing negative stereotypes of black and poor neighborhoods as high in crime, poverty, and disinvestment. In contrast, gentrification in culturally diverse neighborhoods including white ethnic neighborhoods in Baltimore and Latino and diverse neighborhoods in San Francisco, and working-class neighborhoods in both cities was presented

64 with a negative spin, reinforcing positive stereotypes about white immigrants, diversity, and hardworking Americans.

Spin and Its Implications

The idea of “spin” is central to the literature on media studies and the study of media in urban sociology, although often called by different names. I use the term spin here because the alternative is an analysis of “bias.” Because journalism is founded on the principle of objectivity, scholars frequently look for how the media is biased and towards whom. For example, the urban growth machine theory posits that newspapers are biased towards the interests of developers and, thus, present pro-development perspectives (Jonas & Wilson, 1999; Logan & Molotch, 1987; Molotch, 1976). However, the idea of bias assumes a systematic and intentional slant to an issue. Using the concept of spin removes these assumptions and focuses instead on identifying whose perspectives are introduced as the sides of a debate and how much coverage each side gets.

Thus, spin is a measure of whether coverage of an issue is predominately positive or negative. The direction of the spin depends on which perspective on the issue gets more coverage within an article and across the articles on a topic. However, spin can also be neutral if there is equal coverage of both sides of the issue. Importantly, spin is influenced by the social hierarchies in which we live, including systems of racial and class-based hierarchies.

The news media is influenced by the society around it (Altheide, 2000; Gamson & Modigliani, 1989; Gans, 2004; Gilens, 1996; Hallin & Mancini, 1984). In fact, the prior literature finds that the news media reproduces and reinforces stereotypes around race and class (Gans, 1995; Gilens, 2009; Hall, 1997; Katz, 1989; Kendall, 2011; Soss et al., 2011). Thus, we see news coverage that replicates negative stereotypes of blacks and the poor as lazy for example (Gilens, 1996, 2009; Hall, 1997; Kendall, 2011). In contrast, groups that are positively stereotyped like the working-class, middle-class, and whites are depicted as hardworking Americans in the news media (Kendall, 2011; Lipsitz, 2006).

What Might We Expect?

Based on the prior literature, we would expect that when groups that are negatively stereotyped are described as residents of gentrifying neighborhoods that gentrification will be given a positive spin with more benefits described than concerns. This hypothesis applies to black and poor neighborhoods, which are consistently stereotyped negatively (L. Bobo & Zubrinsky, 1996; Farley et al., 1994; Gans, 1995; Gilens, 2009; Katz, 1989; Kendall, 2011; Soss et al., 2011). In contrast, when groups that are positively stereotyped are depicted as residents of gentrifying neighborhoods, gentrification will be given a negative spin with more concerns described than benefits. These groups include the working-class and whites (Kendall, 2011; Lipsitz, 2006).

What is unclear from the prior literature is what we should expect for groups with mixed stereotypes. For example, Asians are stereotyped as the model minority, but also as foreigners and invaders in white neighborhoods (Brooks, 2009; C. J. Kim, 1999; N. Y. Kim, 2007; Lung- Amam, 2017; Tuan, 1998). Similarly, Latinos are stereotyped positively as hard-working immigrants, but also negatively as criminals (Chavez, 2013). In these cases, whether the spin on gentrification is positive or negative may depend on other factors beyond the race of the residents of the gentrifying neighborhood. For example, the race of gentrifiers to the neighborhood are likely to influence spin in these cases, particularly if the gentrifiers are less likely to be negatively stereotyped than the Asian and Latino residents.

Finally, we know little about racially mixed neighborhoods and how they are stereotyped by Americans or how they are portrayed in media coverage. While they could be looked at as an utopian ideal, they could also be seen as neighborhoods that lack character or identity.

Measuring Spin

I measure spin as positive or negative depending on whether gentrification is depicted as a beneficial or harmful change. To test my hypotheses, I used MaxQDA, a qualitative data analysis software program, to manually code for the benefits of gentrification and concerns about gentrification in 667 articles1 that use the term gentrification or a derivative of that term. I specifically selected articles that described residential development, residential change, or property values2 to capture articles that were most likely to be about the changes associated with residential gentrification.

After conducting a preliminary review of the data, I developed an inductive coding scheme that captures three forms of information. First, I categorized passages as positive or negative statements about gentrification using codes for concerns about and benefits of gentrification. Second, I identified the specific reasons why gentrification was described as positive or negative (if explained) and coded for that reason. Finally, I coded for whom gentrification was a positive or negative including the city overall, the gentrifying neighborhood, long-term residents of the neighborhood, recent in-movers to the neighborhood, businesses, or developers. These codes were layered onto each coded passage and were not mutually exclusive. Thus, passages could be coded for multiple concerns, multiple benefits, and both concerns and benefits. The coded passages include both statements written by journalists and quotations from their sources. I provide more detail about the coding scheme in the findings section below and in a codebook in Appendix Table B.

1 This includes 253 articles from the Baltimore Sun and Baltimore City Paper and 414 articles from the San Francisco Chronicle and the San Francisco Examiner. 2 I identified these topics by hand coding for the context of each article’s broader context in MaxQDA. 66

The sections that follow present the results of the qualitative coding I conducted in MaxQDA both quantitatively and qualitatively. I exported counts of the codes applied to each article for further analysis in Stata, which I used to create summary statistics.

In general, there were three types of statements that I coded as spins on gentrification. The first were explicit statements of the benefits and concerns about the changes that were happening. For example, I coded the following passage for two neighborhood level benefits, declines in crime and neighborhood climate:

There is a reality that when artists move into a community, they tend to move to communities that are very cheap and are often perceived as being very dangerous, because they're willing to put up with the dangerous to get the cheap. And then what happens is that they tend to stabilize the neighborhood, make it often less dangerous than it was before they got there, because they tend to call the police or whatever more often. And then other people start to say, "Hey, we can move there because it's cool." (Hill, 2009)

The article explicitly described gentrification as improving neighborhoods by changing the actual and perceived crime in the community, which I coded as the neighborhood benefit of declines in crime. In addition, it described artists as making a neighborhood “cool,” which I coded as creating a positive neighborhood climate.

Concerns often similarly reflected explicit statements about how gentrification would or was affecting the community. For example, I coded the following passage for concerns about displacement of long-time neighborhood residents, increasing rents for long-time residents, business loss in the neighborhood, and cultural loss of the neighborhood.

Alonso watched horrified as rising rents in the city's booming dot-com economy began displacing her artist friends and the working class. Her favorite haunts closed, and her neighborhood -- the Mission District -- transformed, in her eyes, into a yuppie haven. (V. Wagner, 2001)

The passage first refers to the fate of long-time neighborhood residents: displacement in the face of rising rents. Thus, I coded for concerns about increasing rents and displacement for long-time residents. The next sentence describes the source’s favorite business closing, which I coded as business loss for the neighborhood. Finally, there is the description of the neighborhood transforming into a “yuppie haven,” which I coded as cultural loss. As shown in these two examples, passages often included more than one benefit or concern, which required multiple codes to capture the details. In fact, some passages included both benefits and concerns even within quotes from the same sources.

The second type of statements I coded were descriptions of neighborhoods that suggested that the changes occurring were positive or negative. For instance, I coded the following passage as the neighborhood benefit of beautification:

People who live in Baltimore have known of these dynamics for a long time. Politicians and urban planners have studied it. The esteemed urban writer Neal Pierce came to town last year, 30 to 40 years after the great suburban migration started, and concluded: “…the city boasts a glittering chain of waterfront projects” (Rodricks, 1992)

The description of development as a “glittering chain of waterfront projects” suggests an aesthetic improvement in the look of the area. Thus, I coded this passage as a neighborhood level benefit of beautification. Similarly, I coded the following passage for other neighborhood benefits because of the references to blight:

I drove down Third Avenue, around the Le Conte Avenue loop, down a couple of residential streets in the area, and through an industrial warehouse zone. It was blighted. It is apparently an old problem that began long before the Great Recession. For example, on Le Conte Avenue I saw a motel that has a sign that advertises color televisions in their rooms. It means that the building has not been renovated for at least 40 years. Additionally, Third Street has several vacant retail spaces that are blighted. This was caused by the ghost town effect that I referred to in my first paragraph. After profit streams are established, the blighted properties will become much easier to renovate. (Mallory, 2010)

The passage uses the word “blighted” three times to describe the neighborhood and the commercial spaces. The use of the word blight to describe property and spaces, along with the reference to the neighborhood as a “ghost town,” both portrayed the current state of the neighborhood in a negative light, suggesting that redevelopment or gentrification would be a positive change for the neighborhood. Because the kind of change that would result from redevelopment is unclear, I coded this passage as “other benefits” for the neighborhood.

Finally, there were often general statements that the changes associated with gentrification were positive or negative change. In some cases, these were vague statements of support or dissent with the changes. For instance, I double coded the following passage as a general statement of both benefits and concerns:

But for Bell, [her art installation] “White Light, Black Birds” was also an activist statement against gentrification. “The responses from the community were not all what I thought they’d be,” Bell says; many residents told her they supported gentrification projects, for a variety of reasons. (Woods, 2011)

The community’s response of support for gentrification was a general statement of benefits. Because the source did not specify what residents liked about the changes, this statement

68 indicated a general assumption that there were positive outcomes associated with the process. Similarly, the source described her art installation project as a statement against gentrification, which does not specify what her concerns were.

In the analyses below, I measure spin in an article by subtracting the number of concerns that were raised from the number of benefits. A positive number means there were more benefits than concerns raised, while a negative number means there were more concerns raised than benefits. This figure aggregates data across the three types of statements to document the overall spin, which I also calculate for the stakeholder groups of long-time residents, neighborhoods, and the city. Importantly, most of the articles presented a spin on gentrification. Only 7 percent of Baltimore articles and 3 percent of San Francisco articles mentioned neither benefits nor concerns.

The Overall Spin

Across the articles, those from Baltimore newspapers presented a largely positive spin on gentrification. While the articles raised concerns about what would happen to long-time residents of gentrifying neighborhoods, most of the discussion focused on the potential positive economic outcomes for neighborhoods and the city. In contrast, the San Francisco data presented a negative spin, stressing the potential negative social outcomes for neighborhood residents and neighborhoods. These variations in spin reflect differences in exposure to gentrification and the economic conditions of the cities. Baltimore was in need of growth in the middle-class tax base and still had a large problem with abandoned housing and high concentrations of poverty in neighborhoods throughout the city. But San Francisco had already amassed a middle-class tax base that was now being displaced from the city by even wealthier in-movers and had very few neighborhoods left untouched by gentrification.

About half of the articles from both cities mentioned both benefits and concerns about gentrification. However, over one-fourth of the Baltimore articles mentioned benefits, but no concerns. In contrast, over one-third of the San Francisco articles described concerns about gentrification, but no benefits.

This more positive spin in Baltimore articles and more negative spin in San Francisco article is reflected in the average spin figures presented in Figure 1. As shown in the first set of bars, the average Baltimore article included a little over 2 more benefits than concerns, presenting a positive spin overall. In contrast, the average San Francisco article included almost 1.5 more concerns than benefits.

Figure 1: Spin by Stakeholder and City

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SOURCE: Author's calculations using a selection of newspaper articles published in the Baltimore Sun, Baltimore City Paper, the San Francisco Chronicle, and the San Francisco Examiner between 1990 and 2014.

NOTE: "Overall" includes benefits and concerns for the city, neighborhood, long-time residents, businesses, developers, and recent in-movers, as well as generic statements that were positive or negative about gentrification.

There were, however, variations in spin depending on whether concerns or benefits were about long-time residents, gentrifying neighborhoods, or the city as large. Both Baltimore and San Francisco articles were more likely to have a negative spin about gentrification for long-time residents of gentrifying neighborhoods. The spin for Baltimore was less negative (about 1 more concern mentioned than benefits) than San Francisco (2 more concerns than benefits). In fact, most concerns expressed in articles from both cities were about long-time residents. In both cities, these concerns were predominately about social issues, which, as shown in Table 1, included issues of displacement and loss of community.

Table 1: Detailed Benefits and Concerns Coding Scheme

Benefits Concerns Long-Time Long-Time City Residents Neighborhoods Residents Neighborhoods Economic More tax base Jobs Investment in the Business loss Business loss Profitability of community Lack of affordable selling home More businesses housing

Increased homeownership costs Increased rents Unaffordable new businesses Physical Reduced vacant New affordable Beautification of NA NA housing housing buildings and spaces Political NA NA Involved residents NA NA Social Growing Mixed-income Declines in crime Displacement Cultural loss population community Neighborhood Loss of community Loss of diversity Safer area climate Racial change Other Any other benefit Any other concern General positive statements General negative statements

In contrast, articles from both cities presented a more positive spin on gentrification for neighborhoods. The Baltimore articles had a more positive spin with over 2 benefits more than concerns on average, while the San Francisco articles had less than one more benefit than concerns on average. These benefits were predominately economic in Baltimore articles, including more investment and resources in the community and more businesses. In the San Francisco articles, benefits for neighborhoods tended to focus on social benefits, such as declines in crime and improvements in the neighborhood climate.

Finally, like the overall spin, the spin for the city was the opposite in Baltimore and San Francisco articles. Baltimore articles presented more benefits for the city with a little over one benefit more than concerns on average, while the San Francisco articles presented slightly more concerns than benefits (0.6). The benefits described in the Baltimore articles were predominately economic and mainly focused on the potential growth in the tax base. In contrast, the San Francisco articles mainly focused on the loss of affordable housing in the city.

Gentrification Spin and Race

While the overall spin was largely positive for Baltimore articles and negative for San Francisco articles, two variations emerged by the racial description of neighborhood residents in data from both cities. First, the spin was more positive in articles from both cities when residents were described as black. Second, when residents were described as part of a culturally diverse group, the spin was more negative. While the racial demographics of the two cities were distinct during the period of study, articles presented the potential loss of “culture” in ethnic and diverse neighborhoods due to gentrification as more concerning than the potential loss in black neighborhoods.

Gentrification Helps Black Neighborhoods

In articles from both cities, the spin on gentrification was more positive when residents were described as black. Depictions of neighborhoods with black residents represented the areas as blighted, high in crime, and in decline with little investment in resources and the physical infrastructure of the neighborhood. Whether these representations were accurate or not, the spin presented a narrative that black neighborhoods are likely to benefit from the changes that come with gentrification despite the concerns about displacement of long-time residents.

Figure 2 shows the spin in articles that describe residents of gentrifying neighborhoods as black and those that do not by city including the overall spin, the spin for long-time residents, and the spin for the neighborhood at large. While there was no difference in the overall spin for Baltimore articles, the spin on gentrification’s potential effects for long-time residents and gentrifying neighborhoods in articles depicting black residents presented gentrification as a process that could be helpful for black neighborhoods.

Figure 2: Spin for Black and Non-Black Neighborhoods by Type and City

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The largest difference between Baltimore articles that described black residents and those that did not was the spin about the effect of gentrification on neighborhoods, which was more positive when residents were described as black. Benefits for gentrifying neighborhoods were predominately economic in these articles, including financial investments in the community and more businesses locating in the neighborhood. For example, a 2004 Baltimore Sun article described plans for a “dying industrial strip” in a predominately black neighborhood including, “$173 million, to be bankrolled by outside investors, in a bid to redevelop the impoverished African-American enclave” (Pietila, 2004b). As described here, gentrification in this black neighborhood would revitalize a “dying” and “impoverished” neighborhood through outside investors, suggesting that investments from within the community were not happening. Similarly, a 2013 City Paper article described the role of outside investors in “spruce-up projects” because “in a community that has been this distressed, people need to see change fast” (Woods, 2013). This article also described outside (rather than inside) investments to clean up a “distressed” neighborhood.

In the San Francisco articles, overall spin was less negative in articles that described residents as black than articles that did not. Although there was slightly more concern about the effects of gentrification on long-time residents in black neighborhoods than non-black neighborhoods, articles that described residents as black described more benefits for the neighborhood than articles that described residents as non-black. According to these articles, black neighborhoods would benefit socially from gentrification due to declines in crime and improvements in the neighborhood climate. For example, a 2012 Examiner article described an influx of hipsters to a predominately black neighborhood: “Where once corner stores and check cashing venues were the norm, now you’ll find trendy wine bars, sidewalk cafes, and hip restaurants…Call it what you will, there’s no denying the neighborhood has become a little bit safer, a lot more hip, and definitely more crowded” (“Which San Francisco taquerias best reflect their neighborhoods?,” 2012). With more hipsters and trendy businesses, the areas was seen as safer and more “hip,” producing social benefits for the neighborhood.

Gentrification Hurts Cultural Diversity

Where the spin on gentrification in black neighborhoods presented it as a more favorable change, the spin on gentrification in neighborhoods that represented cultural diversity was negative. These neighborhoods included white ethnic neighborhoods in Baltimore, and Latino and diverse3 neighborhoods in San Francisco. Across the articles from both cities, these neighborhoods were depicted as losing community and culture through gentrification.

Baltimore articles that described residents of gentrifying neighborhoods as white ethnics (e.g., Polish, Greek, Italian) had more a negative spin on gentrification across all measures in comparison with articles about non-white ethnic neighborhoods. As shown in Figure 3, articles

3 Diverse neighborhoods were described as areas with people of color, racial minorities, or diverse residents. 73

that described white ethnics as residents had more concerns than benefits overall and for the neighborhood, compared with more benefits in articles describing non-white ethnics. Similarly, there were more concerns for long-time residents when articles described residents as white ethnics than when described as non-white ethnics.

Figure 3: Spin for White Ethnic and Non-White Ethnic Neighborhoods by Type Baltimore

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Concerns were predominately about social losses for residents and the neighborhoods through the displacement of long-time residents and the loss of community for the neighborhood at- large. For example, a 2007 City Paper article described the changes to a previously white ethnic neighborhood experiencing an influx of middle-class renters and homeowners. The article described the sense of community diminishing and changing with the new in-movers, which was due in part to the displacement of long-time residents: “Other old-timers disappeared over time, as well. ‘Most of them have pretty much died, and a lot of others have been forced out of the neighborhood by high rents or, if they were owners, by higher taxes — or they were forced out just by the feel of it…The newcomers kind of bleached out the neighborhood’” (V. Smith, 2007). The loss of long-time residents including through death, displacement due to rising

74 housing costs, and voluntary moves by residents unhappy with the changes affected the neighborhood, “bleaching” it of character.

In the San Francisco data, the spin on gentrification in neighborhoods described as culturally diverse was more negative than neighborhoods that were not diverse. These neighborhoods I’m referring to as culturally diverse include neighborhoods described as diverse, but also Latino neighborhoods, which include neighborhoods that were racially diverse rather than majority Latino during the period of study. As shown in Figure 4, articles that depicted residents as diverse or Latino had a more negative overall spin and spin for long-time residents than articles that depicted non-Latino/diverse neighborhoods. This difference included more social concerns for long-time residents and more economic concerns for the neighborhoods in general.

Figure 4: Spin for Latino, Diverse, and Non-Latino/Diverse Neighborhoods by Type San Francisco

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For example, a 2014 Chronicle article described concerns around displacement and increased housing costs for long-time residents in a historically Latino neighborhood: “Latino families are being replaced by highly educated white and Asian tech workers willing to pay $3,500 or more a month in rent” (Fimrite, 2014). The focus in this article was on concerns about displacement of 75 long-time residents due to increasing costs and wealthy in-movers who could afford the higher costs.

Summary

Across both Baltimore and San Francisco articles, the spin on gentrification was more positive when residents of gentrifying neighborhoods were described as black and more negative when residents of gentrifying neighborhoods were described as culturally diverse. Even though articles across both sites recognized concerns about the potential displacement of long-time residents, other social and economic benefits were identified as reasons why gentrification in black neighborhoods would be a positive change. In contrast, the spin for white ethnic neighborhoods in Baltimore and Latino and diverse neighborhoods in San Francisco focused on the loss of culture and community. The articles essentially argue that neighborhoods deemed to be centers of culture, history, and community should be preserved, but reserve that argument for white ethnic, Latino, and diverse neighborhoods.

Gentrification Spin and Class

While there were some differences in the overall spin by class description of neighborhood residents in the Baltimore and San Francisco data, there were two similarities. First, there were more concerns about the effects of gentrification on long-time residents when residents were depicted as poor or working-class. Second, there were more benefits described for neighborhoods when residents were depicted as poor. These similarities resulted in slightly different overall spins by the class description of residents with Baltimore articles presenting slightly less positive overall spin for poor neighborhoods and San Francisco articles presenting more negative overall spin for articles depicting the working-class. In the sections below, I describe the similar trends, as well as the resulting overall spin.

Gentrification Harms Lower-Income Residents

Displacement was a major concern about gentrification, particularly for the lower-income long- time residents most likely to be affected. As shown in Figure 5, articles that described residents of gentrifying neighborhoods as poor or working-class were more likely to discuss concerns about the effects of gentrification for long-time residents than articles that did not describe residents as poor or working-class. While there were more concerns for the working-class than the poor across both cities, concerns for the poor outnumbered benefits more than for non- poor or working-class neighborhoods. These articles focused predominately on social concerns including displacement and loss of community. For example, a 2004 Baltimore Sun article raised concerns about displacement for the working-class: “hordes of professionals have steadily elbowed out established blue-collar families over the past two decades, turning modest brick homes into expensive showpieces” (Pietila, 2004a). With higher-income in-movers, “blue- collar families” were forced to move. Similarly, a 1993 Chronicle article described plans to rebuild a public housing development: “290 families will have to move temporarily — and more

76 than 170 will never get to come back…And unlike the existing buildings for low-income residents…the new development will have only 60 percent of its units set aside for such families” (T. Walker, 1993b). The lack of replacement housing for these poor families to return to was of particular concern in this article. In fact, across the articles from both cities, displacement was consistently raised as a concern for poor and working-class long-time residents.

Figure 5: Spin for Long-Time Residents by Residents' Class and City

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Gentrification Helps Poor Neighborhoods

Despite this worry for poor long-time residents, articles also gave gentrification a positive spin for poor neighborhoods, sending the message that even though gentrification could hurt poor long-time residents, it could also improve the neighborhood. Figure 6 shows the spin for neighborhoods by the class description of neighborhood residents for articles from both cities. As seen by the first two columns in the graph, articles that described neighborhood residents as poor included a more positive spin on the effects for neighborhoods. While the difference for the Baltimore articles was slight, the results were dramatic for San Francisco articles.

Figure 6: Spin for Neighborhoods by Residents' Class and City

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Baltimore San Francisco

These benefits were predominately described as economic in the Baltimore articles including investment in the neighborhood and more businesses. For example, a 1992 Baltimore Sun article described how a restoration project for a church could lead to future investments: “Now that the $3.7 million restoration has been completed, it is heartening to report that the result is nothing short of spectacular. ‘I think we are going to be an anchor for the whole Druid Hill Avenue corridor,’ says Urban League president Roger I. Lyons” (Pietila, 1992). As the source suggested, the investment in the church was an important step in attracting additional investments to the neighborhood.

In San Francisco articles, the benefits were primarily social including declines in crime and improvements to the neighborhood climate. For instance, a source in a 1994 Chronicle article described the positive changes to the neighborhood’s atmosphere that came with gentrification: “’All these things going on makes for a richer place,’ he said. ‘There is a real mix of people who get along, and I like that’” (King, 1994). Gentrification, as described here, made the neighborhood more diverse and thus created a “richer” neighborhood climate.

Overall Spin for Poor and Working-Class Neighborhoods

The differences in magnitude of concerns for poor and working-class long-time residents and benefits for poor neighborhoods produced distinct patterns in the overall spin between the Baltimore and San Francisco articles. While the Baltimore articles presented gentrification as 78 positive overall, the spin was less positive for poor neighborhoods, as shown in Figure 7. In contrast, the San Francisco articles had an overall negative spin that was more negative when neighborhoods were described as working-class. Thus, the overall spin was likely to raise more questions about gentrification in poor neighborhoods in Baltimore and working-class neighborhoods in San Francisco.

Figure 7: Overall Spin by Residents' Class and City

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Summary and Implications

Overall, the spin on gentrification represented it as a value-added for Baltimore and a destructive force for San Francisco. These differences reflect the economic circumstances of the cities. As described in Chapter 2, Baltimore experienced a decline in middle-class residents and manufacturing businesses over the course of the 1980s and 1990s that left the city in much need of a tax base. The recent, but slow, return of the middle-class, new businesses, and the expansion and renewed investment of existing businesses in their surrounding neighborhoods was seen as a necessity for the city’s future. The changes that have occurred in Baltimore have been relatively slow and occurred in specific neighborhoods. Today, many areas of the city continue to have high rates of vacant housing and lack investment in the physical, social, and 79 economic needs of their residents. Thus, while concerns are acknowledged, the valuation of gentrification is predominately focused on benefits due to the city’s economic, physical, and social needs.

In contrast, San Francisco had experienced gentrification in arguably every area of the city by the end of the period of study. While high poverty areas were largely stagnant prior to the period of study, the redevelopment of these areas by the city marked some of the last neighborhoods untouched by gentrification. Today, the city is subject to super- or hyper- gentrification (Centner, 2008; Lees, 2010) as the middle-class is being displaced by the upper- class due to continually increasing rents and housing values. With a growing number of residents facing displacement and many leaving the city all together for Oakland and other cities in the East Bay, the spin on gentrification is negative due to the impact the changes are having on the city as a whole.

Despite these differences in overall spin and the dramatic differences in race and class compositions of the two cities, there were remarkably similar patterns of spin by race and class. Regardless of city, black and poor neighborhoods were generally represented as disinvested and blighted and, thus, the spin on gentrification presented it as a beneficial or less harmful change. Neighborhoods that were working-class or more culturally diverse (e.g., white ethnic, diverse, and Latino neighborhoods) were represented as losing community and culture through gentrification, thus presenting a negative spin of gentrification as harmful to those neighborhoods. Both culturally diverse and working-class neighborhoods actually reflect a preference for the mainstream in distinct ways. White ethnic neighborhoods in Baltimore, and Latino and diverse neighborhoods in San Francisco reflect neighborhoods with white majorities that have some culturally non-WASP element, such as a moderate sized Latino population or a large Greek population. In contrast, working-class neighborhoods reflect the middle-class of a bygone era: the manufacturing economy. While culturally diverse neighborhoods reflect what Americans think their neighborhoods should look like (Havekes, Bader, & Krysan, 2016; Lewis, Emerson, & Klineberg, 2011), working-class neighborhoods reflects what middle-class neighborhoods used to look like. The positive spin of both reflects a longing and nostalgia for these neighborhoods.

The distinction between desirable and undesirable neighborhoods was more acute for race than class overall. Concerns were essentially equal for poor and working-class long-time residents in data from both cities. However, the spin for black neighborhoods was consistently more positive, particularly in contrast to culturally diverse neighborhoods. The one exception was a similar level of acknowledgment that gentrification would be harmful for long-time residents regardless of race. Ironically, this equal spin on concerns for long-time residents overlooks differences in housing tenure that were likely to make gentrification more harmful in black neighborhoods than predominately white neighborhoods (Conley, 1999).

The differences in spin by both race and class reflected descriptions of the gentrifying neighborhoods. Poor and black neighborhoods were described as disinvested, blighted, and

80 high in crime, while working-class and culturally diverse neighborhoods were described as family oriented, community centered, and important as historical and cultural landmarks. While these descriptions are partially true, we know that the news media tends to exaggerate the association of racial demographics with these characteristics. For example, in coverage of issues like crime and poverty, blacks are overrepresented as criminals and welfare recipients (Gilens, 1996, 2009; Hall, 1997; Katz, 1989; Sacco, 1995). In the case of gentrification, the representation of poor and black neighborhoods as high in crime, disinvestment, and blight reinforces negative stereotypes about black and poor neighborhoods (Quillian & Pager, 2001; Sampson & Raudenbush, 2004), confirming readers’ impressions that gentrification is likely needed in those neighborhoods. If readers were informed by the newspapers’ spin, they would be more likely to support gentrification in black and poor neighborhoods and protections from gentrification in working-class and culturally diverse neighborhoods.

Chapter 6: Summary and Implications

Race and class have fundamentally shaped how American cities look today through segregation, policy, and (dis)investment (Faber, 2018; Hartman, 2002; Rugh & Massey, 2010; Sampson, 2012; Sugrue, 1996). Yet we know less about how the patterns of investment and decline that vary by race and class composition have influenced understandings of other forms of development and neighborhood change. This study seeks to address this gap by explaining how the news media represents gentrification and how those representations varies by the racial and class demographics of gentrifying neighborhoods. The findings (1) document the common understandings of gentrification, (2) explain how the news media replicates and reinforces race and class hierarchies through the representation of gentrification, and (3) illustrate how race and class hierarchies continue to contribute to inequalities in neighborhood change.

As described in the sections below, the findings contribute to culture and urban sociology by documenting the process through which race and class hierarchies are replicated in newspaper reporting including how newspaper reporting reflects the uneven patterns of (re)development. In the case of gentrification, this process potentially reinforces patterns of racial and class segregation and unequal policies to protect cities’ long-time residents from increases housing costs and displacement from city living.

Summary of Findings and Theoretical Contributions

While much of the prior literature reports on gentrification occurring based on an academic definition and measure of the term, we actually know very little about what “gentrification” means in everyday life. The findings of this study contribute to this gap in the literature by documenting how gentrification is defined in news reporting. Importantly, very few newspaper articles in the study explicitly defined the term. Instead, by depicting changes in a neighborhood described as gentrifying, the articles linked certain types of change in specified neighborhoods to the process of gentrification, as described further below. Because of historical patterns of investment and disinvestment based on neighborhoods’ race and class compositions (Gans, 1962; Hartman, 2002; Hirsch, 1993; Rothstein, 2017; Sugrue, 1996), the news media’s representations were different depending on the race and class composition of the gentrifying neighborhood. Thus, differences between the representations of gentrification by the race and class composition of gentrifying neighborhoods cannot solely be explained by the race and class composition itself.

How the News Represents Gentrification, Race, and Class

The news media represents gentrification, race, and class through three mechanisms that are both influenced by and reflect the racial and class hierarchies of our society at large. As shown in Figure 1, the process is embedded in reporting and produces the artifact of the article or news report. Through reporting, a change in a neighborhood is categorized as gentrification or

some other type of change, race and class are associated with stakeholders involved in the neighborhood change, and the neighborhood change is spun as a positive, negative, or mixed change for involved stakeholders. Importantly, these three mechanisms are influenced by the race and class demographics of gentrifying neighborhoods and the position of those demographics in the larger social hierarchy. That is, reporting on black gentrifying neighborhoods is influenced by the stereotypes and assumptions we hold about black neighborhoods through the statements of the journalist and their sources, as well as the interpretation and reaction by the reader.

Figure 1: The Process of Representation

Categorizing

Through categorizing types of neighborhood change as gentrification, articles define when the term gentrification should be used. Race and class demographics influence categorization because of the uneven development and investment in city neighborhoods based on their race and class compositions (N. Smith, 2010). Poor and black neighborhoods experience less investment by developers and homebuyers than working-class and predominately white neighborhoods due in part to concerns about a lack of returns through housing values. In fact, most investment in poor and black neighborhoods comes from the government and some nonprofit developers rather than private, for-private developers. These differences in investment by race and class are reflected in differences in the kinds of change categorized as gentrification. While gentrification is used to categorize residential and commercial 83

development and change overall, this categorization is more frequent when neighborhoods are described as white ethnic or working-class in Baltimore articles, and when described as white, Latino, or diverse in San Francisco articles. In fact, when black or poor neighborhoods are described as gentrifying, it is predominately referring to new and state-led development, particularly in San Francisco articles. The differences in the kinds of change categorized as gentrification across the two cities reflect the race and class dynamics of urban development. White ethnic and working-class neighborhoods in Baltimore, and white, Latino, and diverse neighborhoods in San Francisco are experiencing more investment through developers, middle- class in-movers, and businesses than other neighborhoods.

Associating

The news media directly connects race and class to gentrification by associating the process with stakeholders of specified race and class backgrounds. Particularly important to imparting an idea of what gentrification looks like are the descriptions of neighborhood residents and recent in-movers. Association did not occur in every article, but when it did, racial association was less frequent than class association. Racially, gentrification was predominately associated with black residents and white in-movers across both sites. However, white ethnic residents were frequently mentioned in the Baltimore articles, and Latino residents and Asian in-movers in the San Francisco articles. These associations are likely to influence readers’ opinions about gentrification based on the stereotypes they hold about people and neighborhoods with these racial and class characteristics.

Spinning

Finally, journalists and their sources directly connected these associations with stereotypes by race and class demographics through the process of spinning in which they describe gentrification as a beneficial, harmful, or mixed change. Spin varied by the race and class composition of gentrifying neighborhoods with more positive spins on gentrification when gentrifying neighborhoods were described as poor or black and more negative spin when described as white ethnic in Baltimore articles, and Latino or diverse in San Francisco articles. These spins reflect and reinforce negative stereotypes about black and poor neighborhoods and positive stereotypes about working-class and predominately white, but culturally diverse neighborhoods. Working-class and diverse neighborhoods will lose their culture and community through gentrification, while poor and black neighborhoods will gain resources and improved housing facilities.

Examples

To illustrate how categorization, association, and spin operate in a news article, I describe two examples below. Importantly, not all articles implemented each of these four mechanisms. In fact, only categorization happened in every article. About 32 percent of the articles associated race with key stakeholders and 70 percent for class. Finally, 96 percent of articles that covered

84 gentrification more directly included a spin about gentrification as a positive, negative, or mixed type of change.

The differences in how these mechanisms apply for race and class demographics is clearly illustrated in a 2003 Baltimore Sun article. The article described the approval of plans to develop townhouses in two Baltimore City neighborhoods. One of the neighborhoods targeted with this developed was described as “in the midst of rapid gentrification,” which included this development project to replace a “warehouse and coin laundry complex” (Pietila, 2003). The article, thus, categorized both residential development through the townhouse development plans and commercial change through the loss of commercial space as gentrification. There were two key stakeholders identified in the process, the developer and the planning commission, but a competing developer was also interviewed for the story. The article also briefly mentioned another development happening in the neighborhood: “One block north, a 173-unit subsidized apartment complex has evicted its tenants. After a major facelift, it plans to reopen, aiming its units for professionals at the nearby Johns Hopkins medical campus” (Pietila, 2003). This paragraph associated gentrification with the class dynamics of change from low-income to middle-class by describing the prior development as a “subsidized apartment complex” and the target tenants as “professionals” (Pietila, 2003). Describing the new apartment building as a “major facelift” also suggested a benefit of the rehabilitation project, a positive spin on the change (B 2003-12-19 BS developer gets city). Finally, the article specified that “No one showed up to oppose Massey’s project,” which signaled that there hadn’t been a negative response to the development project from neighborhood residents (Pietila, 2003).

The second example, a 2000 San Francisco Chronicle article, included all three mechanisms. The article detailed the changes occurring in a gentrifying neighborhood that began in the 1970s: “The gentrification of what was a light industrial area began about 20 years ago because the weather was balmy and warehouse space was cheap. In the late 1970s, buildings routinely changed hands for less than $100,000. By 1994, however, two-unit buildings were selling upward of $525,000…[The neighborhood] became a schizoid mix of cultures — poor African Americans and Filipinos living in welfare hotels next door to newly rich computer geeks driving Jaguars and BMWs” (Zane, 2000). In these two paragraphs alone, there was both categorization and association. Gentrification was categorized as a process of residential change with homeowners buying properties and new groups of in-movers coming in. Race and class were also associated with gentrification through the specific racial and class descriptions of the neighborhoods prior residents, poor blacks and Filipinos, and recent in-movers, newly rich tech workers. This passage also describes the neighborhood’s more recent demographic as “a schizoid mix of cultures,” a euphemism for diversity.

As the article goes on, it addressed concerns and benefits of gentrification in the neighborhood. For example, “Like many longtime residents, she worries about artists, designers and other creative people being driven out (or bought out) by rocketing rents…’[The neighborhood] is really changing. It’s going into its new dot-come life,’ she said. ‘It’s gotten to the point where if you don’t own property, you’re going to have to leave’…The price tag on a vacant lot on the

85 south side of the park is a cool $5 million, and dozens of new condos are being built, adding to traffic and parking problems” (Zane, 2000). The article primarily described concerns for the neighborhood and long-time residents including displacement of long-time residents and renters, increased housing costs, and traffic and parking congestion. But it continued by pointing out some of the benefits: “On the brighter side, after 15 years of nagging by [long-time residents], the city has begun a major face-lift of the oval strip of greenery…’We’re finally getting lights and new park furniture,’ Levy said…’Having more kids in the playground is really nice’” (Zane, 2000). The benefits described here are mainly amenities and safety. In fact, the spin on gentrification was negative with the exception of the passage quoted above. Subsequent quotes from long-time residents and business owners in the area were mainly focused on the loss of community, cultural changes that came with new residents, parking issues, increased rents, and displacement.

As shown in these two examples, articles varied in both how many of the four mechanisms were deployed and how extensively each mechanism was addressed. Importantly, these mechanisms only capture signaling that is done directly through words. Without information about how readers are interpreting the language used in the articles, it is unclear how other biases and assumptions may be triggered through these articles. Despite these limitations, the insight documenting these mechanisms provides still advances our understanding of how the process of framing unfolds through the news media.

Implications of Representation for Public Opinion and Policy

While the prior literature has yet to resolve whether and how the news media influences policy, the prior research does find that representations influence both public opinion and policy responses (Gans, 1995; Gilens, 1996, 2009; Katz, 1989; O’Connor, 2001; Soss et al., 2011). What a social problem means and who a social problem is understood to affect influences whether a policy solution is necessary and what kind of policy should address the problem (Gans, 1995; Gilens, 1996, 2009; Katz, 1989; O’Connor, 2001; Soss et al., 2011). The influence that meaning has on public opinion and policy makes the study of the process of representation essential. Whether gentrification is commonly understood as a natural process, a destructive force, or a rejuvenating change and who is understood to be affected has implications for whether there is a response to the negative outcomes and what that response looks like.

My findings suggest that policy responses to gentrification are likely to vary by city and neighborhood for two reasons. First, patterns of both disinvestment and redevelopment vary by neighborhoods racial and class compositions. Thus, as suggested by the findings on categorization, gentrification is unfolding in different ways in neighborhoods of different race and class demographics. Whether a neighborhood is experiencing a market driven process of investment and development or a government driven development project can frame whether a policy intervention seems appropriate. Second, the variations in spin of gentrification found in this study suggest that race and class influence how neighborhoods are interpreted and whether they are seen as needing change. While I documented this influence in the spin of

86 gentrification presented in articles, voters and politicians are using similar assumptions, stereotypes, and interpretations when they consider whether or not gentrification is a policy problem in a specific neighborhood.

Unequal responses to the potential negative effects of gentrification, particularly displacement and increased housing costs, could reinforce inequality and segregation. If cities use policies to protect residents of predominately and majority white and working-class neighborhoods from negative effects of gentrification, while simultaneously subjecting residents of majority black and poor neighborhoods to the negative effects, they will be promoting the exodus of black and poor residents from city neighborhoods while allowing residents of predominately white and working-class neighborhoods to stay in place. These changes are likely to reconcentrate poor and black populations in new places, a process we already see underway in the suburbanization of poverty (Garr & Kneebone, 2010; Kneebone & Berube, 2013; Soursourian, 2012).

Based on evidence from the newspaper articles analyzed here, the policy response to gentrification does already appear to be unequal. State-led action including city-wide and neighborhood specific policies to promote and discourage development were mentioned in a small subset of the articles that mentioned gentrification.1 For predominately black or poor neighborhoods, these initiatives promoted neighborhood change primarily through residential redevelopment projects that would increase the availability of market-rate housing in areas previously dominated by public housing, such as HOPE VI. In contrast, state-led actions for predominately white or working-class neighborhoods tended to support efforts to slow development; protect long-term residents and businesses from rent and property tax increases, displacement, and eviction; and control the types of changes that the neighborhood would experience by limiting the development of loft apartments or the influx of big box stores. While the articles in this study only capture state-led action that was directly associated with gentrification, these differences provide preliminary insight on the unequal policy response to gentrification.

In this case, unequal policies serve to reinforce preexisting inequalities. Residents of poor and black neighborhoods are more likely to be renters and more likely to be poor than residents of white and working-class neighborhoods. These class differences make them more vulnerable to the negative effects of gentrification, particularly increased rents and displacement. The encouragement of gentrification in neighborhoods with more vulnerable residents, which I argue is one consequence of media representations, ensures more displacement and a reconcentration of poverty in other areas. Furthermore, the protection of groups that tend to be more socio-economically privileged, another consequence of media representations, gives them the right and the means to stay as the city becomes a more expensive place to live.

1 This included 3 percent of the Baltimore articles and 7 percent of the San Francisco articles. 87

Finally, the limited discussion of how policy can address gentrification including both actual policies2 and potential policies3 in the newspaper articles demonstrates two things. First, it shows that gentrification was often represented as a process that cannot be controlled by policy. Second, it shows that that there is a limited understanding of how policies contribute to the gentrification process. Thus, one potential implication of the role the news media plays through representations of gentrification is that voters and politicians may think little about how government can contribute to and prevent gentrification from occurring.

Future research should seek to explain public opinion of gentrification and how it aligns with the news media representations documented here. In particular, how do public opinions reflect the race and class inequities found in the news media representations in this study?

Study Implications for Cultural and Urban Sociology

Theoretically, this study has implications for studies of cultural and urban sociology. While the subfields have long had overlapping scholarship, much of this literature has focused on individual behavior and decision-making (Anderson, 1990, 1999; Du Bois, 1899; Harding, 2010; W. J. Wilson, 1997). What has been less studied is how representation affects urban spaces, a topic mainly advanced by urban growth machine theorists (Jonas & Wilson, 1999; Logan & Molotch, 1987; Molotch, 1976). Representation matters for urban sociology because how urban issues are understood by voters and politicians informs whether these issues are seen as problems and whether policy is seen as a reasonable solution to those problems. Policy is central to the development and redevelopment of urban space through the work of Planning Departments, Public Housing Authorities, and City Councils. Furthermore, urban planning and development have always been tools to address social issues. Whether to prevent racial conflict by zoning segregation between blacks and whites or to address health conditions in poor neighborhoods by improving living conditions, the development of lived space has served a purpose in modern society. How social issues are defined, who they are assumed to affect, and whether they are assumed to affect different social groups in different ways matters for how urban planning and development are implemented. To understand how, why, and where (re)development occurs, we need to better understand representations, particularly the representations of the social issues (re)development is expected to address.

We see evidence of this across the history of urban development in the United States. Neighborhoods were described as “blight” for urban renewal, which was often used to target black and poor neighborhoods on valuable real estate (Hartman, 2002; Hirsch, 1993; Sugrue, 1996). The Federal Housing Authority (FHA) encouraged banks to avoid mortgage loans in neighborhoods deemed to be “high risk,” which were often majority black neighborhoods (Faber, 2018; Rothstein, 2017). In fact, the patterns of racial segregation and the stagnation of black-white segregation in the United States suggests that there are other patterns in how

2 These were discussed in 3 percent of Baltimore articles and 7 percent of San Francisco articles. 3 These were discussed in 8 percent of Baltimore articles and 11 percent of San Francisco articles. 88

neighborhoods are represented in planning in development that can help to explain racial and class inequalities.

While I focused on the news media as one cultural institution in this study, understanding how biased representations inform urban planning and development means expanding this type of research to uncover how racism and classism are embedded in modern-day policy (Bonilla- Silva, 2006; Omi & Winant, 2014). These are the policies on which American cities as we know them today were (re)developed in ways that perpetuate segregation and unequal access to resources and opportunities. Negative representations of the homes and communities of the disenfranchised include images of abandoned, community-less spaces where the few remaining residents are uninvested. These assumptions make it easy to repossess the land with eviction and eminent domain for “better” purposes, while further isolating and segregating those who have from those who have not. Future research should seek to further document and expose how cultural and political institutions perpetuate these inequalities that the Civil Rights Act of 1968 and the Fair Housing Act Amendments sought to terminate.

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Appendix A: Race and Class Demographics Over Time

101

Appendix Table 1: Demographic Characteristics: Baltimore

1980 1990 2000 2010 2014

Total population 786,775 736,014 651,154 620,644 621,000

Race/ethnicity White, non-Hispanic 43.4 38.6 31.0 28.0 27.7 Black, non-Hispanic 54.4 58.9 64.0 63.2 62.4 Hispanic/Latino 1.0 1.0 1.7 4.1 4.8 Asian, non-Hispanic 0.9 1.0 1.5 2.4 2.5 Other, non-Hispanic 0.3 0.4 1.8 2.3 2.6

Household income Less than $25,000 33.5 30.3 31.2 32.3 31.4 $25,000-49,999 26.9 25.0 25.6 24.6 23.8 $50,000-99,999 39.6 30.7 27.9 26.8 26.8 $100,000-149,999 NA 9.2 9.5 9.6 10.2 $150,000 or more NA 4.8 5.8 6.7 7.9

Educational attainment Less than a high school diploma 51.6 39.3 31.6 20.4 16.5 High school diploma or equivalent 37.1 45.2 49.2 53.5 53.7 Bachelor's degree 11.3 8.5 10.4 14.0 15.7 Master's or professional degree NA 7.0 7.6 10.3 12.0 Ph.D. NA NA 1.1 1.8 2.1

Industry of employment Manufacturing 18.8 12.3 7.8 5.3 4.6 Education and health services 19.9 21.1 26.8 30.4 31.6

Home values Less than $50,000 NA 17.0 14.1 6.5 7.9 $50,000-149,999 NA 60.0 69.6 35.9 41.1 $150,000-499,999 NA 21.7 14.6 51.9 46.0 $500,000-999,999 NA 1.4 1.4 4.6 4.2 $1,000,000 or more NA NA 0.3 1.0 0.8

Rents Less than $600 NA 63.9 41.5 22.0 21.0 $600-999 NA 20.4 39.6 33.9 32.7 $1,000-1,499 NA 15.7 15.4 30.6 31.7 $1,500 or more NA NA 3.5 13.5 14.6

Source: 1980, 1990, and 2000 U.S. Census, and 2008-2012 and 2012-2016 American Community Survey data.

Note: All dollar amounts are CPI adjusted to 2014 dollars. 102

Appendix Table 2: Demographic Characteristics: San Francisco

1980 1990 2000 2010 2014

Total population 678,974 723,959 776,733 807,755 850,282

Race/ethnicity White, non-Hispanic 52.3 46.6 43.6 41.8 41.2 Black, non-Hispanic 12.5 10.5 7.6 5.7 5.1 Hispanic/Latino 12.3 13.9 14.1 15.1 15.3 Asian, non-Hispanic 21.4 28.4 30.7 33.2 33.5 Other, non-Hispanic 1.5 0.6 4.0 4.2 4.9

Household income Less than $25,000 25.6 19.8 16.9 20.3 19.2 $25,000-49,999 26.0 20.8 15.5 15.7 13.4 $50,000-99,999 48.4 32.3 27.7 24.0 22.5 $100,000-149,999 NA 14.5 17.1 16.3 16.4 $150,000 or more NA 12.6 22.9 23.7 28.4

Educational attainment Less than a high school diploma 26.0 22.0 18.8 14.1 12.6 High school diploma or equivalent 45.7 43.0 36.2 33.9 32.6 Bachelor's degree 28.2 22.1 28.6 31.7 32.9 Master's or professional degree NA 13.0 14.7 17.8 19.2 Ph.D. NA NA 1.7 2.4 2.7

Industry of employment Manufacturing 10.3 9.2 6.6 5.9 5.4 Education and health services 14.8 14.9 16.2 19.9 18.4 Professional 23.0 27.3 19.3 20.0 22.8

Home values Less than $50,000 NA 1.5 2.1 0.9 1.4 $50,000-149,999 NA 3.6 3.2 1.8 1.3 $150,000-499,999 NA 42.3 31.0 13.8 11.0 $500,000-999,999 NA 52.6 44.4 55.7 50.4 $1,000,000 or more NA NA 19.2 27.9 35.9

Rents Less than $600 NA 75.8 14.9 13.4 13.3 $600-999 NA 13.1 18.6 14.1 12.6 $1,000-1,499 NA 11.0 27.3 22.8 19.6 $1,500 or more NA NA 39.1 49.8 54.5

Source: 1980, 1990, and 2000 U.S. Census, and 2008-2012 and 2012-2016 American Community Survey data.

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Appendix B: Coding for Association

Main Codes Each of the following was applied whenever a stakeholder was mentioned. These codes were always double coded with a race and class subcode, as outlined in the next table.

Code Explanation Notes Businesses Captures relevant business actors Double code with a race and class code. In-movers New residents of the neighborhood. Double code with a race and Includes description of “recent” and class code. “new”, as well as any people who have moved in 3 or less years at the time the article was written. Community Includes nonprofits, advocates, organizers, Double code with a race and organizations and other community organizations class code. Residents Captures all non-recent residents including Double code with a race and older residents of the neighborhood. class code. Includes descriptions of “old”, “long standing”, and “raised”, as well as anyone who has lived in the neighborhood for more than 3 years. Also use to capture historical references to neighborhood composition. Other Captures any actors not captured in the Double code with a race and codes including developers, politicians, class code. police, social workers, etc.

Subcodes Each time a stakeholder was mentioned, I coded for both a main code (as defined above) and the relevant race and class subcodes from the table below.

Code Subcodes Explanation Notes Race Captures whether there Double code with a was a description of the main code and a class stakeholder’s race and, if code. so, what racial category was described. Asian Mention of race as Asian or country of origin in Asia. Black Mention of race as black.

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Code Subcodes Explanation Notes Latino Mention of race as Latino/Hispanic or country of origin in Central or South America or Spanish speaking Caribbean. White Mention of race as white. White ethnic group Mention of white ethnic group such as Italian or Italian American. Other Mention of some other racial group. Undefined No mention of race. Class Captures whether there Double code with a was a description of the main code and a race stakeholder’s class and, if code. so, what class category was described. Poor/low-income Reference to “poor” or “low-income”. Working-class Reference to “working- class” or “blue-collar”. Middle-class Reference to “middle- class”, “college-educated”, or “homeowner”. Upper-class Reference to “upper-class”, “affluent”, “upscale”, or “refined”. Undefined No mention of class included.

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Appendix C: Coding for Concerns and Benefits

Code Subcodes Explanation Notes Benefits of change Discussion of the positive Only use this code for outcomes of changes for generally positive the community. statement about gentrification. For the city: More tax base Mention of the growing tax base that comes with the middle-class moving to the city. Growing city Mention of an increase in population the city population overall. Reduced vacancy Mention of reductions in vacant housing or land as a result of the changes. Other Any other specific benefit that is a city-level benefit. For the neighborhood at-large: Involved residents Mention of more involved These benefits are not residents including specific to long-term politically involved, residents or recent in- involved in community movers. organizing, and other ways. Basically the suggestion that new residents are more invested in the community. More businesses Mention of more businesses in the neighborhood being a positive change. Basic services Mention of an increase in basic services including trash removal, street cleaning, snow removal, etc. Investment in the Mention of investment community coming with changes to the community including both from new residents but also

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developers, real estate agents, or businesses. Neighborhood Mention of improvements climate in the neighborhood climate. Could include mentions of the area being more lively. Declines in crime Mention of declines in crime coming with the changes. Beautification Mention of physical improvements to buildings, gardens, parks, etc. that beautify the neighborhood. Other Any other specific benefit mentioned that benefit the neighborhood at-large. For long-term residents: Profitability Mention of profits that long-term residents and businesses gain selling. Mixed-income Mention of mixed-income community communities as a benefit to the changes. Jobs Mention of jobs as a benefit to the changes. New affordable Mention of new affordable housing housing developments accompanying changes. Safer area Mention of crime and This might be due to safety improvements for moving to another long-term residents. neighborhood. Other Any other specific benefit that is for long-term residents. For recent in-movers: Trendy businesses Mention of new businesses catering to new residents. Profitability Mention of increases of housing values for new residents. Other Any other specific benefit that is for recent in-movers. 107

For developers Any benefits for developers. For businesses Any benefits for businesses. Other benefits Any other specific benefits that don’t fit into the other codes above. Concerns with change Discussion of the negative Only use this code for outcomes of changes for generally negative the community. statement about gentrification. For the city: Affordable housing Mention of there being less lost affordable housing in the city at large due to changes. Other Any other concerns mentioned for the city. For the neighborhood at-large: Cultural loss Mention of loss of culture including historical loss and loss of diversity. Lack of affordable Mention of the lack of housing affordable housing in the neighborhood. Loss of diversity Mention of concerns about Difference between diversity being lost as a this and “racial result of changes. change” is that it will be called “diversity” explicitly. Racial change Mention of concerns about Use this code when racial change as a result of race is explicitly changes. described as changing, not just diversity being lost. Business loss Mention of loss of businesses in the neighborhood that are not attributed to loss for long- term residents specifically. Other Any other concerns mentioned for the neighborhood at large. For long-term residents:

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Loss of community Mention of the loss of community that happens due to changes. Increased property Mention of increases to taxes property taxes. Increased rents Mention of increases to rents. Displacement Mentions of the displacement of long-term residents of the neighborhood. Unaffordable new Mention of new businesses businesses being unaffordable to long- term residents. Business loss Mention of long-standing businesses closing. Other Any other concerns mentioned that are about long-term residents specifically. For recent in-movers: Displacement Mention of the displacement of recent in- movers. Increased rents Mention of increases in rents affecting recent in- movers. Other Any other concerns mentioned that are about recent in-movers. For developers Any concerns about changes for developers. For businesses Any concerns about changes for businesses. Other Any other concerns that concerns aren’t captured there that are specific.

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