Weather) Girls Just “Wanna Have Fun”?

University of Nevada, Reno

Do (Weather) Girls Just “Wanna Have Fun”?:

A Survey of Broadcast Meteorologist Stereotypes and Experiences

A dissertation submitted in partial fulfillment of the requirements

for the degree of Doctor of Philosophy in Geography

Nyssa Perryman Rayne

Dr. Paul F. Starrs / Dissertation Advisor

December, 2020

NYSSA PERRYMAN RAYNE

December, 2020 i

ABSTRACT

The historical caricature of the “weather girl” comes from the original women

(primarily actresses and entertainers) who broke into the field of broadcast meteorology in the mid-1950s, with little in the way of educational or experiential background in meteorology or climatology. Instead, these women were hired to increase station ratings as a gimmick, and, as a result, cemented the ditzy, blonde, sexy, often unintelligent “weather girl” stereotype that persists in the field today. This dissertation delves into the historical context of the “weather girl” stereotype, exploring the present-day ramifications of this cultural caricature through an analysis of popular media, in addition to two distinct surveys of current broadcast meteorologists. Our research finds that movies and TV shows further reinforce the negative attributes of the “weather girl” stereotype, portraying these women as unintelligent and overtly sexualized, and thus adding to the sexism and perceived lack of trust and credibility more generally afforded women in our patriarchal society. Additionally, our survey findings show that the “weather girl” stereotype serves as a negative lens through which women and men weathercasters still view women broadcast meteorologists, further driving deep-set weathercaster beliefs that women unfairly

“get ahead” in the field by using their beauty rather than their brains. This sexist view not only shapes the perception of weathercasters, but also contributes to significantly more critical, negative feedback and harassment—most of which references attributes of the

“weather girl” stereotype—for women broadcast meteorologists from viewers and station management alike. Finally, our survey of Black women weathercasters indicates that the

“weather girl” stereotype is nuanced and perceived differently by women from different ii

race/ethnicities. In part, this difference in perception is rooted to the idea—held by women of all race/ethnicities—that the “weather girl” is a white woman, with blonde hair and/or blue eyes, a nuance that emerges from the responses of Black women weathercasters in particular; however, additional data are needed to definitively determine if (and how) the “weather girl” stereotype impacts Black and Latina women weathercasters.

iii

ACKNOWLEDGEMENTS

First and foremost, I want to thank my forever-love, my inspiraaaaation, my moon and stars, Sandra, without whom this dissertation wouldn’t have been possible. Thanks for teaching me to “NEVER GIVE UP, NEVER SURRENDER,” even after 11 years

(lolsob). I love you more than ALL the words in this document could ever express.

I also couldn’t have done this dissertation without the unwavering support of my legend- ary advisor, Dr. Paul F. Starrs. Words can’t express how much you mean to me, and how lucky I am to have experienced your amazing mentorship! Thank you so much for carry- ing me over the finish line (kicking and screaming and crying lol). To my committee —

Dr. Tamara Wall, Dr. KJ Ormerod, Dr. Adam Kirn, Dr. Doug Boyle, and Dr. Stephanie

McAfee: thanks for your continual patience during these “unprecedented times” – I seriously appreciate each and every one of you so much.

Thanks also to my kids — Marshall, Luke, Eleven, and Casandra (without whom I probably would have finished much sooner – but seriously, sorry for all the nights Big Mama had to work), my parents (for supporting me, even in disbelief towards the end), my Ma- dre Ellen (a.k.a. the family matriarch), and my wonderful, loving Swindles (Mike,

Mckenzie, and Michele – y’all are the BEST). Also, thank you to Montana (soon to be

Dr. Eck), as well as Dr. Dianna Francisco + Dan for prepping with me, and Anya +

Alexis, for getting me the mental health tools I desperately needed to finish. There are so, so many other people that helped me get to this point – you know who you are and I’m so grateful for your love and support. I’m also super thankful for SOFITUKKER and the iv

FreakFam for providing a daily phenomenal dissertation-writing soundtrack + dance party during the COVID-19 pandemic.

Finally, I would be remiss not to thank each and every participant in both of my studies – thank you so much for everything you do, from keeping us safe to educating us on weather and climate, even while being trolled constantly by your audience. Thank you for sharing your experiences, even the horrific truths, and trusting me with your stories.

This dissertation would not be possible without each one of you!

And as I write this, I’m not even sure I’ll actually be able to defend and submit it – but, if by the faith of my Grandma Lorane I do, I want to give one final shout-out to Black woman in STEM. I dedicate this dissertation to YOU! Let this be a sign that you’re doing great and you belong here (AND don’t let anyone convince you otherwise.)

TABLE OF CONTENTS

ABSTRACT ...... i

ACKNOWLEDGEMENTS ...... iii

TABLE OF CONTENTS ...... v

LIST OF TABLES ...... viii

LIST OF FIGURES ...... x

Chapter 1: Introduction ...... 1

1.1 Overview and Objectives ...... 1

1.2 Overview and Origin of the “Weather Girl” Stereotype ...... 2

1.4 #NotAWeatherGirl: Ongoing Controversies in the Weathercasting Field ...... 4

1.5 Research Purpose, Questions, and Hypotheses ...... 5

References ...... 9

Chapter 2: “Weather Girls” on the Big Screen: Stereotypes, Sex Appeal, and

Science ...... 11

2.1 Introduction ...... 12

2.2 A Brief History of Women in Broadcast Meteorology ...... 13

2.3 Methods ...... 19

2.4 Analysis ...... 21

2.5 Discussion and Conclusions ...... 30

Acknowledgements ...... 33

References ...... 34 vi

Chapter 3: You Go, (Weather) Girl! -or- #Notaweathergirl: Understanding

Weathercaster Perception of the “Weather Girl” Stereotype ...... 39

Abstract ...... 40

3.1 Introduction ...... 41

3.2 Literature and Media Review ...... 41

3.3 Methods ...... 51

3.4 Results and Analysis ...... 57

3.5 Summary and Conclusions ...... 91

References ...... 94

Chapter 4: “Weather Girls” and Whiteness: A Qualitative Survey Analysis ...... 100

4.1 Introduction and Background ...... 101

4.2 Methodology ...... 112

4.3 Results and Discussion ...... 119

4.4 Summary and Conclusions ...... 136

References ...... 140

Chapter 5: Summary and Conclusions ...... 144

APPENDIX A: Perryman, N., & Theiss, S. (2014). “Weather Girls” on the Big

Screen: Stereotypes, Sex Appeal, and Science, Bulletin of the American

Meteorological Society, 95(3), 347-356 ...... 147

APPENDIX B: 2018: Year of the (Weather?) Woman — Discussion of email responses to Perryman and Theiss (2014) ...... 157

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APPENDIX C: Full survey used for Chapter 3 study...... 158

APPENDIX D: Full survey used for Chapter 4 study...... 171 viii

LIST OF TABLES

TABLE 2.1: Summary of female representation by categorical breakdown for each movie and TV show analyzed...... 20

TABLE 3.1: Survey instrument, based on the main descriptive categories associated with the “weather girl” stereotype as outlined in Perryman and Theiss (2014)...... 54

TABLE 3.2: Demographics of all survey respondents...... 58

TABLE 3.3: Exploratory statistics of survey-respondent age by gender...... 59

TABLE 3.4: Geographical market location of total survey respondents and by gender of respondents...... 64

TABLE 3.5: Overview of codebook used in analysis of respondent’s open-ended description of personality, educational, and/or physical traits associated with the “weather girl” stereotype...... 65

TABLE 3.6: Percentage of women and men respondents that used language associated with the established thematic categories when describing the “weather girl” stereotype. 69

TABLE 3.7: Percentage of women and men respondents that used language associated with career impacts of gender for women versus men weathercasters ...... 74

TABLE 3.8: Responses by men weathercasters to the question: “How has your gender impacted your career and/or experiences as a weathercaster?” ...... 77

TABLE 3.9: Percentage of women and men respondents that stated physical appearance impacted their career and used language associated with the impacts of physical appearance on career...... 81

TABLE 3.10: Percentage of women and men respondents that used language associated with the impacts of physical appearance on career...... 85

TABLE 4.1: Survey instrument, reworked and extended from previous research on weathercaster perceptions of the “weather girl” stereotype, as outlined in Rayne et al.

(2020)...... 117

TABLE 4.2: List of frequently-mentioned physical appearance traits that emerged from narrative responses on the “weather girl” stereotype and their associated coding information ...... 126

TABLE 4.3: Percentage respondents by race/ethnicity that used language associated with coded categories, along with chi-square values between Black and white populations .. 129

LIST OF FIGURES

Figure 3.1: Composite view of “weather girls” on one website from Winkler 2019...... 48

Figure 3.2: Self-reported gender of survey applicants...... 58

Figure 3.3: Age histogram of all survey respondents...... 59

Figure 3.4: Race/ethnicity of all survey respondents...... 62

Figure 3.5: Race/ethnicity of female (left) and male (right)...... 62

Figure 3.6: Total number of coded references to common “weather girl” attribute categories, as relayed by survey respondents ...... 66

Figure 3.7: Percentage of coded references to common “weather girl” attribute categories by women versus men, grouped into categories and subcategories ...... 67

Figure 3.8: Total number of coded references to common “weather girl” attribute categories, grouped into subcategories and by gender/total numbers ...... 67

Figure 3.9: Women respondents’ perceived connotation (positive, negative, both, and unsure) of the term “weather girl” when labeled this term by others ...... 70

Figure 3.10: Respondent perception of how their gender has impacted their career, broken into gender and impact effect (positive, negative, both, and unsure) ...... 73

Figure 3.11: Respondent perception of how their physical appearance has impacted their career, broken into gender and impact effect (positive, negative, both, and unsure) ...... 79

Figure 3.12: Physical appearance traits that are commonly referenced by both women and men weathercasters. Organized by frequency-observed within open-ended responses. ... 80

Figure 3.13: Women’s versus men’s perceived need to change their hair color and clothing style, in order to further their career in broadcast meteorology ...... 80

Figure 3.14: Women’s versus men’s perceived need to change their hair color and clothing style, in order to further their career in broadcast meteorology ...... 83

Figure 3.15: Women’s versus men’s perceived need to change weight in order to further their career in broadcast meteorology ...... 83

Figure 3.16: Women’s versus men’s receipt of an email, message, or comment on their physical appearance and/or clothing style, from viewers (left) and broadcast colleagues/station managers (right) ...... 84

Figure 3.17: Respondent perception of how their race/ethnicity has impacted their career, broken into gender and impact effect (positive, negative, both, and not at all)...... 84

Figure 4.1: A photo of June Bacon-Bercey in her position as station meteorologist in the

1970s. Reproduced from Slotnik, 2020...... 101

Figure 4.2: Reported race/ethnicity of respondents...... 120

Figure 4.3: Summary of respondent ages ...... 121

Figure 4.4: Summary of respondent market geographical regions ...... 121

Figure 4.5: Summary of employment market size as reported by respondents...... 122

Figure 4.6: Summary of respondent race/ethnicity by employment market size ...... 123

Figure 4.7: Most commonly-referenced thematic traits –by percentage of respondents who used each term to describe a stereotypical “weather girl” ...... 126

Figure 4.8: Total number of coded references to common “weather girl” attribute categories, as relayed by survey respondents according to respondent race/ethnicity .... 128

xii

Figure 4.9: Total number of responses reporting the most career-impacting factor out of each of the four “weather girl” attribute category options, as relayed by survey respondents according to respondent race/ethnicity ...... 131

Figure 4.10: Percentages of respondents indicating their perception of future impacts to their career due to the Black Lives Matter social justice movement...... 132

Figure 4.11: Percentages of respondents, by race/ethnicity, indicating their perception of future impacts to their career due to the Black Lives Matter social justice movement. .. 133

Figure 4.12: Percentages of respondents indicating the race/ethnicity group they perceive as facing the most discrimination in the field of broadcast meteorology...... 135

Figure 4.13: Percentages of respondents, by race/ethnicity, indicating their perception of the race/ethnicity group facing the greatest discrimination in the field of broadcast meteorology...... 136

Chapter 1: Introduction

1.1 Overview and Objectives

In the field of meteorology, there exist several deep-set divides along the lines of gender, race/ethnicity, and scientific communication, with white men comprising the majority of researchers and academics in atmospheric science and constituting a majority of broadcast meteorologists (Cranford, 2018; Hallows, 2020; Henson, 2010). Reviewing the history of broadcast meteorology reveals that one of the drivers of these divides lies in the historical caricature of the “weather girl,” modeled after women (primarily actresses and entertainers) who broke into the field of broadcast meteorology with in the mid-

1950s but had little in the way of educational or experiential background in delivering a useful weather prediction for the week ahead (Henson, 2010). Instead, these women were hired to increase station ratings with their overtly sexual demeanor and flirtatious talk, a novelty at the time (Henson, 2010). Yet — unbeknownst to them — these women helped cement the ditzy, blonde, sexy, often stupid “weather girl” trope, a stereotype that women are still labeled with in the year 2020. This dissertation delves into the historical context of the “weather girl” stereotype, exploring the present-day ramifications of this cultural caricature through an analysis of popular media, in addition to two surveys of present-day broadcast meteorologists, in order to determine how this “weather girl” image is perpetuated in current cultural media; how women versus men view this stereotypical depiction of women meteorologists; and, further, how this trope is interpreted by those most discriminated against in the field, namely Black and Latina women weathercasters.

Chapter 1 provides the following: a roadmap to this dissertation, including a brief overview of the academic literature that grounds the work; a summarized research purpose; and an outline of research questions and hypotheses that drive each study. Chapter

2 focuses on the portrayal of women broadcast meteorologists in popular films and television shows, with a focus on how the “weather girl” stereotype impacts these portrayals.

The thematic findings associated with the “weather girl” stereotype compiled in Chapter

2 were used to inform and ground the methods in Chapter 3, a survey of broadcast meteorologists on their experiences and perception of the “weather girl” stereotype. Chapter 4 further focuses on more intersectional perspectives of the “weather girl” stereotype, specifically the perceptions of Black and Latina women weathercasters in their own words.

Chapter 5 summarizes the various findings and conclusions of this study. Appendix A, a

2014 PDF file, is the basis for a slightly updated Chapter 2 of this dissertation. Appendix

B is a published letter to the editor of Bulletin of the American Meteorological Society, in response to public feedback after publication of the article that is Appendix A. Appendix

C and D are full copies of the electronic survey used for the studies in Chapter 3 and 4, respectively, including all response options. Note that while these versions include all response options, the logic used in the survey itself (eg. white-participant skip logic in Ap- pendix C for race/ethnicity questions) is not evident in these full copies but is elaborated on in the methods section of each chapter.

1.2 Overview and Origin of the “Weather Girl” Stereotype

A comprehensive overview of the “weather girl” stereotype is compiled in Chap- ter 2 (Perryman and Theiss, 2014). To summarize, this stigmatized label was coined in

response to the first women — with no formal science education or training — emerging in the field of broadcast meteorology. Used by major US television stations as a ploy to increase their ratings in the 1950s, several actresses, models, and the occasional educated weathercaster, with what television station managers perceived as an attractive confor- mation, would serve as “eye-candy” for viewers, while offering little in the way of accurate meteorological forecasts (Henson, 2010).

Through the “happy weather” of the 1960s and ’70s and the integration of techno- logical weather tools in the newsroom in the 1980s and ’90s — even as (primarily white) women began achieving undergraduate degrees in meteorology — the “weather girl” label has persisted, serving as an additional barrier for women to overcome in order to build credibility and trust with their audience (Henson, 2010). Even today, in 2020, the

“weather girl” stereotype lingers, though its utility has changed to become more nuanced.

For example, the “weather girl” alluded to in this dissertation title is often weaponized by critics and trolls to degrade women but considered more neutral by some viewers who take it simply to mean “meteorologist.” For nearly 75 years, this long-standing term has been associated with women, even as they pursue one of the least diverse, most male- dominated fields in science (Goldberg, 2019), yet that role has never been formally studied to determine the full impacts on women in broadcast meteorology. This research sheds light on the “weather girl” label, including its origin, evolution, usage, and interpretation by women, including Black and Latina women.

1.3 Current Demographics of the Broadcast Meteorology Field

White men make up the majority of atmospheric scientists, and have since the field’s origin (Goldberg, 2019). Women have made recent strides in presence and employment to close the gender gap, increasing from 12% in the 1980s (Lazalier, 1982) to roughly 29% in 2018 (Cranford, 2018). However, the vast majority of these women continue to be white (Bacon-Bercey, 1978; Goldberg, 2019; Hallows, 2020), although a striking absence of research on diverse racial/ethnic identities in meteorology further illustrates the field’s primarily white composition. Hallows (2020) reviewed research on the field’s race/ethnicity demographics, finding an updated proportion of Black weathercasters to be 10% in the field, still less than the population parity calculated by Bacon-

Bercey (1978), but, again, based on a limited number of studies. Demographic research pertaining to race/ethnicity in the field of broadcast meteorology needs a stronger focus on intersectional identities, including race/ethnicity and gender, instead of just one or the other.

1.4 #NotAWeatherGirl: Ongoing Controversies in the Weathercasting Field

Recently, the “weather girl” label has received renewed attention, as the result of its recent use by a climate change-denying Australian government official to gaslight a prominent woman weathercaster, after she referenced related facts in conjunction with the large bush wildfires of 2019-2020 (Whigham, 2020). The Australian official later apologized for using this term (SBS News, 2020), but not before the social media response of weather women using the hashtag #NotAWeatherGirl as a way to combat the negative connotations associated with this term. However, the “girl” denotation of

“weather girl”—while relegating women to a juvenile or even infantilizing role that could

be viewed as the antithesis of “weatherman,” has also been reclaimed by women, in efforts to empower women of all ages (e.g., “Black Girl Magic” and “You Go, Girl!”). This research will help to identify and describe how “girl” is perceived by weathercasters in the broadcast meteorology field.

Additionally, a plethora of tabloid and personal websites produce a near-constant stream of overtly exploitive and sexist content on “weather girls,” drawing attention to clothing, makeup, breast and butt size, and other physical attributes of the weather women (Hallows, 2020), some of which even include personal information (doxing) of the women highlighted on the site. This infringement and overt sexism illustrates the importance of further exploring the “weather girl” stereotype, at first to better-draw attention to an inappropriate targeting of women scientists, and equally to evaluate whether or not this stereotype has real-world consequences for women in broadcast meteorology.

1.5 Research Purpose, Questions, and Hypotheses

This research is designed to understand how the “weather girl” stereotype propa- gates through our culture and further determine if — and how — this stereotype impacts weather women. Keep in mind while reading that, while I am the lead author in all cases, because there are several authors for some of these pieces, I’ve used “we” and “ours” to describe assumptions that shaped this work.

Another caveat to this mixed-methods research is that we’ve incorporated methods used primarily in quantitative research, techniques like hypothesis testing and statistical analyses, that may or may not be entirely necessary or appropriate in our studies; however, these techniques were included as a way to more definitively determine which

thematic elements were referenced by respondents most frequently, but should be cau- tiously interpreted rather than equated to the statistics-based methods and results traditionally used in quantitative research studies.

The main research questions and hypotheses for each study are listed below, outlined according to the paper/chapters they’re associated with:

A. Chapter 2: “Weather Girls” on the Big Screen

1. How do the current statistics and past characteristics of the “weather girl” stereo-

type translate to films and television shows?

H0: We hypothesize that stigmas associated with the “weather girl” stereo-

type will translate into popular media depictions of women broadcast meteor-

ologists.

2. Do films portray women broadcast meteorologists as “weather girls”?

H0: We hypothesize, for the reasons stated in our first hypothesis, that televi-

sion shows and movies will depict broadcast meteorologists as overtly sexual-

ized and unintelligent, the two main categorical traits associated with the

“weather girl” stereotype.

B. Chapter 3 – Broadcast Meteorologists’ Perception of the “Weather Girl”

1. Are traits associated with the “weather girl” stereotype, as portrayed in movies and

TV shows, the same traits that weathercasters associate with this stereotype?

H0: We hypothesize that weathercasters will be familiar with the “weather

girl” stereotype and will all report similar characteristics as those portrayed

by popular media.

2. Do weathercaster perceptions of the “weather girl” stereotype differ by gender

identity?

H0: We hypothesize that women — connecting more with the stereotype than

men weathercasters — will report traits related to this stereotype differently.

3. Does this stereotype lead to actual impacts for women weathercasters, or not?

H0: We hypothesize that women will report real-life impacts related to the

stereotypical traits associated with the “weather girl” caricature.

C. Chapter 4 – “Weather Girls” and Whiteness

1. Do Black and Latina women broadcast meteorologists perceive the “weather girl”

stereotype in a negative, positive, or neutral light? How does their view com-

pare/contrast with the perspective of women weathercasters from other race/ethnic-

ities?

H0: We hypothesize that Black and Latina women will view the “weather

girl” stereotype in a neutral light, as opposed to the negative view of white

women weathercasters.

2. Does the “weather girl” stereotype, as visualized by women weathercasters, have a

perceivable race/ethnicity? If so, what is that race/ethnicity?

H0: We hypothesize that the underlying stigma associated with “blonde”

women (similar to the “weather girl” stereotype of unintelligent but sexual,

but with white characteristics) influences Black women and Latinas’ percep-

tion of the “weather girl.”

3. Are there unique career-impacts for Black women weathercasters, due to the

“weather girl” stereotype?

H0: We hypothesize that Black, Latina, and white women weathercasters will

all report similar career-impacts associated with this stereotype.

4. How do women weathercasters view racism in the broadcast meteorology field?

Do the perceived career impacts, due to racism in the field, differ by weathercaster

race/ethnicity?

H0: We hypothesize that while all participants will acknowledge racism in

the broadcast meteorology field, Black women weathercasters will perceive

greater career impacts due to racism than Latina and white women weather-

casters.

References

Bacon-Bercey, J., 1978: Statistics on black meteorologists in six organizational units of the fed-

eral government. Bulletin of the American Meteorological Society, 59, 5, 576-580.

Cranford, A., 2018: Women Weathercasters: Their Positions, Education, and Presence in Local

TV. Bulletin of the American Meteorological Society, 99, 281-288.

Hallows, D. W., 2020: THE FULL FORECAST: A GENDER AND RACIAL ANALY-

SIS OF BROADCAST TV WEATHERCASTERS, [Undergraduate honors the-

sis, Brigham Young University] BYU ScholarsArchive, 117. https://scholarsar-

chive.byu.edu/studentpub_uht/117

Henson, R., 2010: Weather on the Air: A History of Broadcast Meteorology. American

Meteorological Society, 304 pp.

Goldberg, E., 2019: Earth Science Has a Whiteness Problem. New York Times (Online) U6 -

https://www.nytimes.com/2019/12/23/science/earth-science-diversity-education.html,

New York Times Company.

Lazalier, J., 1982: A report on the results of a television weather survey. National Weather Di-

gest, 7, 3, 5-10.

Perryman, N., and S.Theiss, 2014: “Weather girls” on the big screen: Stereotypes, sex ap-

peal, and science. Bull. Amer. Meteor. Soc., 95, 341–

346, https://doi.org/10.1175/BAMS-D-12-00079.1.

SBS News, 2020: “Craig Kelly Apologises to UK Meteorologist He Dubbed ‘Ignorant

Pommy Weather Girl,’ ” Retrieved from www.sbs.com.au/news/craig-kelly-apol-

ogises-to-uk-meteorologist-he-dubbed-ignorant-pommy-weather-girl.

Whigham, N., 2020: 'Ignorant pommy weather girl': Lib MP doubles down after “schooling” on

breakfast TV. Yahoo News. Retrieved from https://au.news.yahoo.com/ignorant-weather-

girl-liberal-mp-doubles-down-on-climate-denialism-233758703.html.

Chapter 2: “Weather Girls” on the Big Screen: Stereotypes, Sex Appeal, and Sci- ence*

Nyssa Perrymana and Sandra Theissb aTruckee Meadows Community College, 7000 Dandini Blvd, Reno, NV 89512 bDesert Research Institute, 2215 Raggio Parkway, Reno, NV 89512, USA

* There are slight modifications from the published version in this dissertation chapter, given changes over the last six years since its original publication. Substantial new research and re-evaluation are added to the published text. A PDF of the original published version is in this document as Appendix A.

2.1 Introduction

The field of broadcast meteorology is plagued by deep-set stereotypes of little work/big reward, fusing forecast with the forecaster and resorting to desperate attention- grabbing stunts for ratings. Women currently in the 2020 broadcast meteorology field have dealt with — and continue to deal with — even more restrictive stereotypes based on the public’s perception of their physical appearance (Smith et al. 2013; Smith and

Cook 2008) and intelligence (National Academy of Sciences 2006), stemming from the

“weather girl” stereotype developed in the 1950s (Henson 2010; Malone 2011). The publicly perceived incapacity of women to understand science fuels this stereotype (Flicker

2003; National Academy of Sciences 2006; Brann and Himes 2010; Henson 2010; Moss-

Racusin et al. 2012), which is best seen and often exaggerated in cinematic films and television shows; however, because local TV stations are the most common source used by the U.S. public to receive weather forecasts (O’Malley 1999; Smith 2000; Lazo et al.

2009) and, indeed, other scientific information in general (Wilson 2008), the public’s ability to distinguish the truthful and fictitious aspects of these stereotypes is important because these stereotypes often limit the level of trust established between female weathercasters and viewers (Brann and Himes 2010), a trust necessary to ensure a public response to dangerous weather situations (Sherman-Morris 2005).

For this study, a list of films and television episodes featuring TV meteorologists with a focus on women weathercasters has been compiled, based largely on Ruggles’s piece entitled “Weathercasters on film” (Ruggles 2002) as well as Potter’s “He’s not a weather-man...but he plays one on TV” (Potter 2008). Many of these films were cited by

Ruggles (2002) as a way to “pay tribute to those who watch our skies and try to keep us safe from tornadoes, floods, winds, and hail,” stressing the value and importance of the broadcast meteorology profession. This study will evaluate the origin of the weather girl stereotype associated with female broadcast meteorologists throughout history (Henson

2010; Hartten and LeMone 2010; Wilson 2008) and use this information to further understand the representation of women weathercasters in these films/episodes, in order to determine if the weather girl stereotype is further perpetrated in popular cultural media. Do these films truly pay tribute, or do they perpetuate stereotypes?

2.2 A Brief History of Women in Broadcast Meteorology

The bulk of stereotypical weather girl behaviors that still define present-day

American female weathercasters have an origin in the “gimmicky” periods of weather broadcasting history, generally from the 1950s into 1970s, a time in which overtly theat- rical antics were implemented in broadcast journalism, due to a struggling American economy and increasing pressure on each station to gain more viewership and increase ratings to avoid going under (Henson 2010). To increase ratings, stations resorted to such gimmicks as puppets, costumes, and even the hiring of women weathercasters — overtly for their perceived sex appeal — into an exclusively male profession (Henson 2010; Las- kin 1996). The first woman hired as a weathercaster in a major market was Carol Reed in

1952, who “had no qualifications aside from a cheerful manner and a knack for communication” (Laskin 1996), and thus the act was considered to be a station’s ploy to steal viewers from a higher-rated competing station (Henson 2010).

Although more stations followed this hiring trend, women weathercasters brought on often had no education or experience and instead were overtly sexualized to draw even further viewership (Turner 2009), culminating in a widely used term, “weather girl,” that women weathercasters are still fighting today. As Henson (2010, p. 112) notes, “the clear emphasis on looks and style among many ‘weather girls’ coincided with public skepti- cism of women’s scientific skills and with programmers’ eagerness to trivialize the weathercast.” Henson refers to an article in the 1956 Science News Letter, which stated,

“Whether pretty girls or trained weathermen should present television weathercasts, long the subject of private discussion among weathermen, now is being openly debated,” and after which Henson astutely points out “whether a weatherman should be handsome or not wasn’t addressed” (Henson 2010, p. 112). Several “television personalities” took the

TV meteorology job in order to achieve stardom, including “sex symbol” Raquel Tejada

(later Raquel Welch), who for a time held the title “Sun-Up Weather Girl” in San Diego

(Henson 2010). It was a peculiar era: “One woman gave the forecast in her bathing suit; another reported from inside a huge tub of water, drawing weathercast maps on its plexi- glass sides. …By the late 1950s, the gimmicks had sparked a backlash” (Zimmerman,

2014).

In 1957, the American Meteorological Society initiated the Seal of Approval program (Wilson 2008) as an effort to combat both the obvious and perceived degradation of the broadcasting meteorological field by defining and endorsing “qualified” broadcasters

(Henson 2010). To acquire the Seal of Approval, the weathercaster had to meet a series of requirements, including holding a degree in a science field and passing comprehensive

meteorology examinations. A total of 95 seals were given to men until the first woman gained a seal in December 1972; of the first 200 seals awarded, 197 were awarded to men

(Turner 2009).

Only after the U.S. women’s rights movements of the early 1970s did women re- appear in broadcast meteorology. Unfortunately, newly educated female weathercasters attempting to break into the broadcasting field in the Nixon era found that local news had taken on a new gimmick termed “happy talk” that forced all members of the news crew, especially the weathercaster, to intersperse large amounts of “friendly banter” between segments, largely cutting down on time available for delivering weather forecasts (Laskin

1996; Henson 2010). A few women, including Diane Sawyer, took the TV meteorology job as a step to achieving a more “superior” news anchor position (Henson 2010). Other women, like Barbara Walters, refused to take on an initial weathercaster role because of the degrading antics associated with the field, and June Bacon-Bercey (1928–2019), the first woman and African American to receive the AMS Seal of Approval (AMS 2012), was quoted as saying, “I did not want to do weather on television, only because at that time [the 1970s] I felt it was still gimmicky from women, and I didn’t want to prostitute my profession by being some kind of clown” (Henson 2010, p. 115). Marilyn Turner, a weathercaster in Detroit, explained in a 1975 Parade article her objection to the sexist, stereotypical “weather girl” term still plaguing female weathercasters at the time, saying,

“I don’t believe anyone over 21 should be called a girl. You don’t call a man a weather boy” (Henson 2010, p. 115). Granted, derision is at times directed at male weathercasters

— on film, Harris K. Telemacher (the Steve Martin character in 1999’s L.A. Story comes

to mind), as does Brick Tamland (Steve Carell in Anchorman: The Legend of Ron Bur- gundy, 2004). But the pool of disdain is far deeper for women weathercasters.

The development of “green screen” graphics, Doppler radar, and the premier of

The Weather Channel in the 1980s added public respect for and trust in the weathercaster position, and the implementation of atmospheric science degrees and technology resulted in more serious weather forecasts (Laskin 1996). Women weathercasters began to popu- late the field as the women’s movement slowly transformed the broadcast world, empow- ering women to pursue meteorology degrees as well as the AMS seal and providing job opportunities through affirmative action legislature; however, most of these women still had to endure sexism and harassment from their stations (Henson 2010). Rebecca Reheis began her career in 1984 while finishing up a degree in atmospheric science and revealed the overt sexism she experienced while at her first job (Henson 2010, p. 116):

I thought they were hiring me as a woman working toward a degree in meteorology. When I finally got my degree, they would not allow me to use the title “meteorologist,” because that demeaned the weekday guy, who was not a meteorologist. Since I was a woman, that made it look even worse. They said, “We’ll give you business cards instead.” At that point, they started talking me into sweaters, opening up my neckline, and I knew that I was not hired as a meteorologist.

Even today, the field has not yet completely overcome some of the older female stereotypes grounded in decades past. A 2010 survey found the percentage of women in local weather broadcast positions is around 21.6% of all local weathercasters, a percentage up only slightly from the 19% of 1999 and the 21% of 2005 (Malone 2011). Upon comparing these percentages to the percentage of women sportscasters, which is about 19% and rising, Bob Papper from the Radio and Television News Directors Association (RTDNA)

stated, “You could make the argument that women are making more headway in sports than they’ve made in weather. It’s just not a strong area for women” (Malone 2011, p.

13). Sandra Connell, a talent agent, has also found that “women frequently find themselves stuck behind a long-tenured male in a station’s weather department. When that man finally retires, the news director will likely hire another male to keep the all-important gender balance on the weather team intact” (Malone 2011, p. 14). Another possible reason for the percentage of female chief meteorologists hovering around 11% is that only 21% of women hold the AMS Seal of Approval (Malone 2011), which was replaced in 2005 by the more rigorous AMS Certified Broadcast Meteorologist credential (Wilson

2008), of which only 14% of women hold in an increasingly competitive job market that yields for only the best of the best (Malone 2011).

Women are lacking in prime-time weather anchor slots. A 2008 study found that women weathercasters filled only a quarter of prime-time positions but dominated the weekend slots (Wilson 2008). However, according to Malone (2011, p. 14), weekend slots are “far less influential roles in local TV weather” and women are often relegated to the “growing local morning programs, where a ‘perky’ personality is often a bigger pre- requisite than a meteorological degree.”

Another explanation for the current discrepancy between male and female weathercasters is ageism, illuminated by Valerie Voss, one of the first national-network female weathercasters, who raised the hypothetical question of “who’s going to want a forty- year-old weather girl?” (Henson 2010, p. 119). Voss’s question reflects the results of a

2005 survey, which found that the distribution of women in broadcast meteorology

peaked in the 26–30-yr-old group and the oldest female cohort was 46–50, while the distribution of men was essentially flat across a 20-yr range (26–45 years old) and the oldest male cohort was 71–75 years old (Hartten and LeMone 2010).

Even though female meteorologists have recently made a slight comeback into the broadcasting sphere, the weather girl image is not about to go away. Kendra Kent, a graduate of Mississippi State’s Broadcasting Meteorology program and one of the few female chief meteorologists in America, commented, “You’re constantly fighting the ‘weather girl’ characterization. Whoever came up with that term really jinxed us these last few decades” (Malone 2011). The term “weather girl” has been characterized as a sexist term that trivializes women, in that, by referring to adult women as girls in a context where male adults are described as “men” implies, among other things, that women are not considered fully grown up (Lei 2006). That U.S. women adults have historically been referred to as girls much more often than adult men are deemed boys (Magnusson 2008) — and the fact that “weather girl” is still widely used today — further show both an underlying sexism associated with women in today’s broadcast meteorology field and that this sexism has not changed much since the 1920s - despite changes in the status and rights of women in society as a whole (Vagianos, 2016).

The weather girl stereotype is further fueled by even deeper-set societal stereotypes regarding the intelligence of women versus men. As WNBC New York chief meteorologist Janice Huff explains: “A lot of people think something coming from a man’s mouth is more authoritative. I still think that happens in society — people like it better if a man says it” (Malone 2011). This statement on gender specific credibility has been

illustrated in a study by Brann and Himes (2010), in which a male and female newscaster were selected to read a 30-second weather-related newscast, after which undergraduate students rated the male newscaster significantly higher in competence, composure, and extroversion than the female newscaster. Another recent study has shown there to be gender bias at the academic level in physical science, as university research professors were more likely to hire a male science candidate, offering a higher starting salary and more mentoring support, than an identical female science candidate, who was perceived as less competent (Moss-Racusin et al. 2012). Additionally, the National Academy of Sciences

(2006) has compiled a comprehensive literature review and discussion on these compounding gender biases, including explicit and unexamined (implicit) forms of bias, impacting women in science-related fields.

That female research scientists straight out of college in the 2010s and onward face these biases leaves little hope for a female broadcast meteorologist who must fight the weather girl label atop this bias. Malone explains that the summary of these culturally pervasive weather girl stereotypes, along with the realistic absence of prime-time chief female weathercasters, helps perpetuate the female “freeze out” cycle (Malone 2011):

Some industry watchers believe the male-dominated world of weather on TV stations perpetuates itself, creating roadblocks for female advancement for years to come. Young girls don’t see many females doing weather on television, or they see the under- certified “weather girls” from the days of yore. Many young women with TV-career dreams, seeing limited role models in weather, instead aspire to be news anchors.

2.3 Methods

This study seeks to the ways in which the “weather girl” stereotype translate to films and television shows. While some aspects of the more general broadcast meteorologist

stereotype can apply to both women and men, the portrayal of women were selected as the primary focus of this study because several implicit societal biases against women who pursue science-based careers already exist prior to the added biases associated with this profession and because these gender biases often lead to self-deprecation via stereotype threat (National Academy of Sciences 2006).

A list of films and television episodes was compiled from Potter (2008) and Rug- gles (2002) and includes the following: To Die For (1995), Weather Woman (Otenki- oneesan) (1995), Up Close and Personal (1996), and a 2005 King of the Hill episode,

“Gone with the windstorm.” Cloudy with a Chance of Meatballs (2009) and Weather Girl

(2010) were also added to ensure that the most current films were represented in this study. Two major thematic categories based on the weather girl stereotype were used to analyze these films/episodes: portrayal of female weathercaster 1) intelligence and 2) appearance. The details of these categories were established in past studies that evaluated the portrayal of female scientists in popular media (Flicker 2003; Smith et al. 2013;

Steinke 2005, 2013). Each category will be discussed with elements from their representative cinematic feature, and the findings have been summarized in Table 2.1.

TABLE 2.1: Summary of female representation by categorical breakdown for each movie and TV show analyzed.

The majority of these films/episodes have been marketed as comedies, which ar- guably contain elements of satire, but the satirical elements in comedies are not always understood or interpreted by the audience as intended by the filmmakers (Bonnstetter

2011). Thus, these cinematic features were analyzed from a “face value” perspective.

However, the possibility and implications of satire usage in these films and TV shows is briefly discussed in the study conclusions.

2.4 Analysis

2.4.1 Intelligence

The historically based weather girl stereotype assumes “beauty over brains,” and perpetuates the lack of public credibility experienced by female broadcast meteorologists by implying that women weathercasters lack the credentials and education to analyze and predict the weather and thus must be dependent on the intelligence of men. Each of these stereotypical attributes associated with female weathercasters was found in the analyzed films.

In this stereotypical view of the weather girl, female broadcast meteorologists are degraded regardless of whether they forecast accurately. For example, if the female forecaster is correct, the field of broadcast meteorology is assumed to be “not that difficult,” implying that women would not be able to understand meteorology if it was a difficult field; however, if she is incorrect in her forecast, the female weathercaster is assumed to be fused with her incorrect forecast and deemed unintelligent. These degradations are also found in all films analyzed.

Lack of Relevant Education

In Up Close and Personal, To Die For, and Weather Girl, the lead female charac- ters each have college degrees but not in meteorology, and they have absolutely no experience in weathercasting prior to getting the TV meteorologist jobs. The other extreme can be found in Cloudy with a Chance of Meatballs, as Sam (presumably, short for Sa- mantha) Sparks, the broadcast meteorologist, repeatedly has moments of excited scientific jargon followed by a moment of pause, mumbled stuttering, an “I mean...,” and a girly laugh or trite airheaded phrase typical of a weather girl. She is stopped after one of these moments and asked why she pretends to be unintelligent. Sam then explains that, as a child, she felt pressured to change her hairstyle, ditch her necessary glasses, and pretend to be stupid in order to both avoid bullying for being a “nerdy” child who only wanted a

Doppler radar and to fit into the established role of a pretty weather girl instead. Although

Sam Sparks does not lack the meteorological education, she feels pressured to “dumb it down” for the audience, contributing to the perception that weathercasting is not an intel- lectually difficult profession.

In an episode from King of the Hill entitled “Gone with the windstorm,” it is un- clear if the female broadcast meteorologist, Nancy Gribble, has a degree in meteorology; however, it can be assumed that she lacks the degree because of her station manager’s decision to hire a male degree-holding meteorologist to improve ratings.

Dependence on Men

Yet another sexist notion expressed in the selected films is the strong dependence upon men that these women exhibit. In Up Close and Personal (1996), initially a weathercaster, Sally “Tally” Atwater (played by Michelle Pffeifer) is deemed her director’s

“protégé́”; when she moves to a larger market as a news anchor, she has trouble presenting her newscasts until he shows up to help coach her through. In To Die For (1995), weathercaster Suzanne Maretto (Nicole Kidman) gets advice from a male network director on how to break into the broadcasting field. He tells Suzanne the story of a female weathercaster who slept her way to the top by performing sexual favors for men and stresses that sexual abilities are considered more important than intelligence or broadcasting experience. While Suzanne is being told this story, this same director is sliding his hand up her thigh and asking if she is prepared to do what it takes to get the job.

Sylvia Winters in 2009’s Weather Girl is put through multiple job interviews where the main focus is her ex-boyfriend and morning show host, Dale Waters. When she is finally offered a job at her original morning show, the director stresses that the reason she got the job is because the audience loved her banter with Dale, who she would be forced to interact with on the show. Dale also self-proclaims to have made the suggestion of rehiring her to the director himself.

Another example from King of the Hill’s “Gone with the windstorm” (2005; season 9, episode 13) is weathercaster Nancy’s initial positive reaction to recent college graduate Irv’s arrival. As the news director is carting in new forecasting technology, he says “Don’t worry about how any of this stuff works, Nancy, that’s what Irv’s here for.

Meet Irv Bennet, fresh from Texas Tech’s meteorological school,” to which Nancy re- plies, “I’m just glad I have someone to do my science for me.”

Not only does this scene portray Nancy as being technologically dependent upon a man, the scene shows her to be incapable of “doing science” and implies she is thus

unintelligent. She is portrayed as the typical weather girl airhead when she requests a forecast from what appears to be a monitor cable and later asks a random news producer,

“Are the puffy clouds good or bad?” Her lack of basic meteorological understanding is unrealistic and nothing that would be tolerated by present-day station directors or viewers. This episode perpetuates the weather girl stereotype to viewers who have little knowledge of the meteorological field and is detrimental in establishing trust between a woman forecaster and the public.

Finally, in the animated film Cloudy with a Chance of Meatballs (2009), Sam

Sparks embraces her inner “nerd” only when the male love interest, Flint, who is himself characterized as a nerd, comments on how beautiful Sam looks when wearing her glasses and hair pulled back, giving her the confidence to be her “true” self. Sam relies on a man praising her appearance, which she changed specifically for him, in order to fully embrace and begin using her scientific skill set.

2.4.1c Perceived Lack of Difficulty of the Broadcast Meteorology Profession

The common misconception of the broadcast meteorologist profession is that an in-depth understanding of science is unnecessary to succeed in this job position, leading to the portrayal of meteorology as not a difficult or “hard” science. This misconception is based on past historical antics associated with the field (Henson 2010). However, because women broadcasters lack the credibility and trust experienced by their male peers, this stereotype associated more generally with the weathercasting profession is even more degrading to the intelligence of women in the field.

In both To Die For and Up Close and Personal, the weathercasting job was only a steppingstone for women on the ladder to ultimate stardom, which could only be found in a “more serious” news anchor job. In To Die For, Suzanne’s husband, Larry, degrades the science behind her broadcast meteorologist position, saying “I’m not selling short what you’re doing now — the weather report stuff — which you are really good at — but let’s face facts, it’s probably not gonna lead to any big network offers.” In Weather

Woman, both women forecasters debase their own broadcast position, stating that the TV meteorology segment is not seen as important as the “hard” news segments and thus is often overlooked.

In Weather Girl, the public perception that the weathercasting job is not as difficult or as important as news journalism is expressed when a woman asks Sylvia, “This

[waitressing] is what you’re doing now . . . that’s really sad. You couldn’t get a job any- where else?” The man accompanying the woman then interjects, “Well, it’s not like there aren’t a million people who can read the weather section and ramble on about it on some morning show. I mean, c’mon, it’s not exactly hard-hitting journalism.” Sylvia also degrades her position by placing more importance on journalism than weathercasting. In

Sylvia’s initial on-air rant, she quits what she deems a “stupid, meaningless job” where every day she claims to have “stood in front of this stupid map, repeatedly trying to find new adjectives to describe the word rain.” Later, she corrects her friend Jane’s comment about Sylvia’s plan to send out resumes, when Jane says, “A weather girl resume? . . .

What? She’s a weather girl,” to which Sylvia responds, “I’m a broadcast journalist,

Jane.” In both of these situations, Sylvia continues to strive for what she sees as a more

respectable reputation in broadcasting than simply forecasting the weather. Sylvia even rationalizes accepting a position at the morning show she quit by belittling her previous position, telling her brother, who is opposed to the idea, “They are offering me a raise, and I get to co-anchor. You know what that means, Walt? It means I get to deliver the news … real news, not just the weather. Well, I mean, I still have to do the weather, but I get to do other stuff too now.”

The perceived stereotype perpetrated by the women weathercasters in these films, that journalistic news is “superior” to weather reporting, is not based on hard evidence. In fact, the weathercast is the most-watched part of the local newscast and the primary reason people choose a local television news product (Monmonier, 1999; Wilson, 2008).

Weather is also the most popular content on TV station websites and the most down- loaded information to mobile devices (Waldman, 2011).

Also, although weathercasters have never in the history of their field read from a prompter (Henson, 2010), the view displayed in movies and TV shows is strongly the opposite scenario, especially in the case of female broadcast meteorologists. In Up Close and Personal, Sally is a weathercaster for all of three minutes in the two-hour film and spends absolutely no time formulating a forecast but instead reads word for word off a scrolling teleprompter that has been written by the male news director, Warren Justice.

This teleprompter allows the news director to easily and forcibly change her name to

“Tally” because “it’s easier to say,” he claims, showing the female broadcast meteorologist submitting to the “better judgment” of her male boss. Similarly, in “Gone with the windstorm,” Nancy presents a sunshine-filled forecast for the weekend pork festival that

proves to be stormy instead; while sitting at the festival signing autographs in the wind, she is confronted by two angry festival goers who claim that it is “her weather” that ru- ined the festival, to which Nancy responds, “It’s not my fault I got the weather wrong. I just read it off the teleprompter.”

2.4.2 Appearance

The weather girl movement focused on fashion and sex appeal instead of knowledgeable, science-based forecasting. Thus, female weathercasters were overtly sexualized while attempting to debunk traditional feminine roles, two concepts that are displayed in these films and will be further described in this section.

Sexualization of Female Weathercasters

The past and present-day importance placed on the sexual appeal of female weathercasters portrayed in film far surpasses that placed upon men and is predominant in all of the films analyzed. In Up Close and Personal, Tally is consulted to acquire sex- ier outfits and change her hair color to become more appealing to the audience. In

Weather Woman, the main female weathercaster, made famous by flashing her panties on air to gain station ratings, also engages in five pornographic scenes, all while either scant- ily clad or completely naked.

To Die For could be described as a slightly more realistic version of Weather

Woman, based on the amount of pervasive, overt sexuality exhibited in all aspects of the film. Suzanne wears short skirts and delivers the forecast with a tone and inflection remi- niscent of female weathercaster Tedi “Miss Monitor” Thurman’s “low, breathy voice” heard on the radio in the late 1950s (Henson 2010), while also being continually

sexualized in descriptions such as “volcano,” “goddess,” and “gangbusters.” The main male character in To Die For also turns Suzanne’s on-air weather report pornographic in his mind’s eye.

In “Gone with the windstorm,” former weathercaster Nancy attempts to win her job back by seducing Irv, the newly hired male weathercaster who replaced her. The lengthy seduction scene includes a hair and clothes adjustment followed by a sexual swaggering approach to Irv’s desk where, as she slides up onto the table, the focus stays on her legs and lower torso. This sexually charged scene follows earlier displays of

Nancy’s sex appeal, when her husband and his friends ogle Nancy as they watch her weathercast on his portable TV, saying, “Even an inch tall and ashen gray, she’s beautiful.” While autographing pictures of herself for the picnic with the help of her neighbor,

Nancy advises, “...try not to sign across my face. Oh, and don’t sign across my cleavage either . . . or as one of my fans calls them ‘my warm fronts.’”

Even in Cloudy with a Chance of Meatballs, a children’s movie, two male station directors discuss the appearance of Sam Sparks, the female intern weathercaster. One director makes the comment that “she’s cute and she’s super perky,” to which the other responds with, “well, those are the only things we look for in a TV weatherperson.” That

Sam changed her childhood appearance — dyeing her hair, getting contact lenses, and wearing more revealing clothing — in order to break into the world of broadcast meteorology, speaks to the perceived appearance expected of women in the field. Research has shown that cartoon portrayals of women are more likely to be sexualized and more likely

to have small waists and an unrealistic body shape (Smith and Cook 2008), which are all exhibited in this film.

In Weather Girl, Sylvia Winters is described by men throughout the movie as “a babe” and compared to talk show host, “Sally Jesse... but hot.” Out of all the movies reviewed, Weather Girl is the only film in which the female weathercaster actively fights to refute the stereotypes associated with her job, seen in one of her on-air rants, where she says,

I get to return to a demeaning position where my job is to giggle and look attractive and trivialize the day’s news . . . So let me just set you and the station and our viewing audience straight on a few things. First of all, my title “sassy weather girl” is inaccurate. I am not a girl, I am a woman. And I really hate the word “sassy,” it’s stupid.

Although this rant attempts to confront many of these stereotypes, the overall film man- ages to belittle the weathercasting job in other ways, shown in the final section of this analysis.

Body Image and Feminine Roles

Another stereotype associated with women in all careers, especially in a broadcast meteorology job, is that they are unable to have a normative family life, partially because of the workload and partially due to the fact that their bodies are always on display in front of the green screen. This stereotype seems to be somewhat founded in truth, as a survey of local women anchors found that they rank concerns with their physical appearance, conflicts between the roles of wife/mother and newscaster, and difficulties in bal- ancing career and family as their major career challenges (Engstrom and Ferri 1998); these issues are transposed onto cinematic depictions of female broadcast meteorologists.

In To Die For, Suzanne responds to pressure from her mother in law to have children, saying “A woman in my field with a baby has two strikes against her . . . You can’t conduct serious interviews with a big fat stomach — or say you’ve already had the baby and you’ve got this blubber — these boobs out to here — It’s just so gross.” In another scene where Suzanne’s husband, Larry, is discussing priorities of their future together, he suggests that her weathercasting job is getting in the way of “doing what a family is supposed to be doing,” placing more importance on his job than hers. In Weather Girl, Syl- via Winters is known as the “sassy weather girl” at a Seattle morning show. Throughout the film, Sylvia’s friends constantly remind her of the fact that she is a single woman in her mid-30s with no boyfriend or children, cautioning her to be less picky in her choice of men because her life is basically over. In both of these movies, the female broadcast meteorologists are portrayed as workaholics without children, further reflecting the career challenges experienced by women.

2.5 Discussion and Conclusions

After reviewing the role of women in the history of broadcast meteorology, several stereotypes and their origins were found and categorized into themes. These themes were used to analyze a list of films that feature female TV meteorologists. The overall conclusion found in this analysis is that these movies are either not really about the weathercaster position, are too ridiculous and absurd to be taken seriously or are still rid- dled with the weather girl stereotypes from the 1950s and become vehicles for present- day sexism to subtly exist. Therefore, Ruggles’s (2002) choice of films to “pay tribute” to broadcast meteorologists is misleading because these films depict female weathercasters

as anything but the “unsung heroes” that Ruggles claims them to be and instead diminish the role of female weathercasters by reducing them to nothing more than a weather girl.

All films and episodes mentioned here were analyzed from a direct, face-value perspective, without attempting to interpret the deeper and possibly obscured satirical messages that are often missed by audiences. However, after the face-value analysis was conducted, these films were again reviewed briefly to determine if possible satirical elements could be found and what this satire appeared to achieve in these films.

Satirical discourse is either progressive, if done correctly, or regressive (Bonnstet- ter 2011). The message of progressive comedic satire is to persuade the audience

(Bonnstetter 2011); while satire functions by way of critiquing social mores, it also seems to be driven by the wish to change (or correct) such social configurations (Harries 2000).

Progressive satire also sets up two winners: the group that was correct and the group that learned to be correct; this satirical form operates through an inclusive comic frame: it points out bad behaviors but also shows that everyone is human and everyone is capable of redemption (Bonnstetter 2011). Regressive satire sets up a winner and a loser: someone who is right and someone who is wrong; this segregation serves to condemn certain members of the viewing audience, making it difficult to persuade those members

(Bonnstetter 2011). Also, regressive satire does not promote progressive thinking or chal- lenge authority and instead serves to further oppress marginalized peoples (Bonnstetter

2011) by re-presenting the damaging humor and stereotypes (Epp 2003).

Using these two forms of satire as an analysis guide, the films were reviewed and found to be largely regressive in their usage of satire. Many of the films lacked a core

focus on the weathercasting position, making it difficult to identify a persuasive satirical argument against the weather girl stereotypes, and instead served only to perpetuate these stereotypes. None of the films/episodes analyzed enabled the weather girl to succeed in the broadcast meteorologist position.

The two films that come closest to exhibiting a progressive satirical discourse are

Weather Girl and Cloudy with a Chance of Meatballs. However, as shown in the analysis section of this study, Weather Girl’s Sylvia demeans the weathercasting position from beginning to end of the film. Cloudy with a Chance of Meatballs makes the best attempt to ridicule societal perceptions of the female broadcast meteorologist. However, while

Sam is able to broadcast a breaking weather segment in her new, nerdy persona at the end of the movie, even using technical terminology in this on-air forecast, because she is not the main character of the movie and gives no other on-air performance after this segment the audience is unable to determine if she later succeeds in the broadcast meteorology profession as a scientist rather than a weather girl. Thus, the progressive satirical message of this movie cannot be fully realized by the audience.

Although current women weathercasters who have been educated in atmospheric sciences are striving to change the public’s perception of the weather girl, deeply embed- ded stereotypes outlined here are commonly reinforced through movies and TV shows.

While more women are entering the fields of meteorology and atmospheric sciences, many refuse to go into the broadcast branch of the field, as a large, unexplained drop-off among women going from broadcast meteorology college programs to the workaday weather world at TV stations has recently been noted (Malone 2011), perhaps due to the

residual weather girl stereotype; however, a more in-depth demographic analysis of the broadcast meteorology field should be conducted in order to determine if this drop-off pertains to women alone or impacts men as well as women.

Popular media plays a role in increasing gender equality and diminishing stereotypes in science, technology, engineering, and mathematics (STEM) fields (Geena Davis Institute on Gender in Media 2013). Research has also shown that, when the public has no real-life example of someone in a particular profession to draw upon when viewing overexagger- ated stereotypical depictions in popular media, the public perceives these flawed depictions as truth (Saltzman 2005; Johnson and Holmes 2009). Thus, instead of perpetrating these often inaccurate and destructive stereotypes that set back women in the field of broadcast meteorology, popular films and TV shows should express a more accurate depiction of the broadcast meteorologist profession, including depictions of successful female weathercasters. The viewing audience needs to see more rants against the weather girl stereotype, like that of Sylvia Winters, but from women with expertise in and a pas- sion for broadcast meteorology.

Acknowledgements

We would like to thank Dr. Alan Gertler, Desert Research Institute; Dr. Paul Starrs, Uni- versity of Nevada, Reno; Dr. Tamara Wall, Desert Research Institute; Michele Swindle,

Mckenzie Swindle, and Dr. Cassie Hansen.

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Chapter 3: You Go, (Weather) Girl! -or- #Notaweathergirl: Understanding Weath- ercaster Perception of the “Weather Girl” Stereotype

Nyssa Perryman Rayne a, Dr. Paul F. Starrs a, and Dr. Sandra Rayne b a Department of Geography University of Nevada, Reno, 1664 N. Virginia Street, Reno, NV, 89557-0154 b Southeast Regional Climate Center University of North Carolina at Chapel Hill Chapel Hill, NC 27599-3220

Abstract

This manuscript chapter analyzes demographic and experiential survey data from broadcast meteorologists to determine how the “weather girl” stereotype, found in movies and television shows (Perryman and Theiss, 2014), is understood by weathercasters themselves; if this understanding differs by weathercaster gender; and if the stereotype impacts the lived experiences of women weathercasters. Results indicate that while more women than men reported experiencing negative career and social impacts related to their physical appearance and gender identity—impacts that largely stem from the sexist

“weather girl” label of the 1920s—men were more likely to state that the “weather girl” stereotype doesn’t exist anymore or that this label holds no negative connotation. Addi- tionally, not only were men weathercasters more likely to recognize and overstate the privileges afforded women via more recent diversity-based hiring practices, men also under-acknowledged their own longstanding privileges in the field, including that they experience less harassment than their women colleagues and that they have held the majority of weathercasting positions since the beginning of broadcast meteorology. Finally, women, more often than men, were required by station management to change their appearance, a finding that should inform future station hiring practice reform in efforts to create a more equitable newsroom for all weathercasters.

3.1 Introduction

Recently, more and more women broadcast meteorologists have voiced their rejection of the “weather girl” stereotype, in both individual interviews (Diabri, 2017) and panel-based segments on the Weather Channel (Gallucci, 2017) and the Weather Net- work (Ibrahim, 2018). Yet, the “weather girl” stereotype itself, and more specifically how this stereotype is understood by women and men weathercasters, is minimally studied and documented in academic literature. This study seeks to categorize and analyze weathercaster beliefs and experiences that stem from the existence of the “weather girl” stereotype, including the traits and behaviors they view as associated with this stereotype; their experiences being referred and/or using this term as a descriptor of women weathercasters; and if these views differ between men versus women weathercasters. The main questions driving this analysis are:

• Are traits associated with the “weather girl” stereotype, as portrayed in movies

and TV shows, the same traits that weathercasters associate with this stereotype?

• How do weathercaster perceptions of the “weather girl” stereotype differ by

gender identity?

• Does this stereotype lead to actual impacts for women weathercasters, or not?

3.2 Literature and Media Review

3.2.1 Demographics of Women Broadcast Meteorologists

Since the publication of our initial research (Perryman and Theiss, 2014), several subsequent studies have analyzed the gender of broadcast journalists (field reporters and anchors) by television market areas in several U.S. regions. These studies found that

while women are underrepresented as news talent in many markets (Desmond and

Danilewicz, 2010; Craig, 2017) and in particular, lack a presence in smaller television markets (Craig, 2017), they also present “hard” news stories less often than their male colleagues (Desmond and Danilewicz, 2010; Craig, 2017). These past studies purpose- fully excluded weather anchors from their datasets, focusing only on news anchors and reporters, leaving a gap in the literature that this study addresses. Additionally, women broadcast journalists — including weathercasters — are still required to meet much more rigid physical appearance standards (that often value/prioritize White characteristics) than their male colleagues (Bock et al., 2018).

Additional studies have verified the gender gap in the broadcast meteorology profession continues (Cranford, 2018; Green et al., 2018; Maibach et al., 2017). For example, Cranford (2018) conducted an analysis of weathercaster biographies, which are commonly hosted on station websites, and found that women still hold only a small fraction of weathercasting positions (29%), are less likely to hold either a meteorology degree or the AMS Seal of Approval, and are typically relegated to lower-ranked weekend positions or as fill-ins, instead of holding the prime evening slots typically covered by the

Chief Meteorologist (a title that only 8% of women weathercasters hold). Similarly, research on the educational background of broadcast meteorologists found that women hold a significantly lower number of meteorology degrees as compared to their male colleagues, with the authors even stating that “regardless of the reasons, these results suggest we have not achieved gender equality” (Green et al., 2018, p. 12).

In response to this gender gap in the broadcast meteorology field, Rainear (2019) conducted several experiments to test whether a viewing audience perceives specific social metrics, including physical attractiveness, competency, composure, credibility, and trustworthiness, of weathercasters, based on weathercaster gender, race/ethnicity, and educational background. While findings were sparse and statistically insignificant, one clear finding emerged from these experiments: women are perceived by the viewing audience as less competent, composed, credible, and trustworthy than men, regardless of weathercaster race/ethnicity or even educational degree status (Rainear, 2019). Additionally,

Rainear (2019) found that “…in both experiments, physical attraction to the meteorologist and issue involvement [i.e. general viewer interest in weather or science] were the primary driving covariates – in some cases with effect sizes of 0.5 or higher” and “…that without background information about an individual, an attitudinal set of beliefs may be more important to driving outcome perceptions,” (p. 65). Regarding educational background, Rainear (2019) concludes the following:

In experiment two, adding the additional manipulation of whether a forecaster earned a Bachelor of Arts or Bachelor of Science degree appears to not influence the results in any manner. It’s possible that simply offering somebody a short one sentence blurb about the broadcaster’s educational background may not elicit enough thought for an individual to have no- ticeable differences in perceptions of trust or credibility. On the flipside, it is possible that those consuming the weather broadcasts simply just don’t care about the training or background a broadcaster has (in a non-life- threatening weather scenario at least) as long as they can deliver the information in a consumable or enjoyable fashion. (65)

However, this finding contradicts one of the primary characteristics of the “weather girl” stereotype — namely, the lack of educational credentials, and thus is important to keep in mind when analyzing weathercaster perceptions of this stereotype.

3.2.2 “Weather Girl” Stereotype and Media Portrayal

Gender stereotypes have been comprehensively researched and documented in the academic literature (Ellemers, 2018), including specifics on how these stereotypes have changed over time (Eagly et al., 2019) as well as how popular media depictions contrib- ute to and perpetuate these stereotypes (Ward and Grower, 2020). The emergence of the

“weather girl” stereotype is previously documented (Perryman and Theiss, 2014). Our

2014 study found that popular media forms — such as fictional television entertainment shows and movies — reinforce negative gender stereotypes when depicting women broadcast meteorologists, and tend to focus on the physical appearance, sexuality, and restrictive family roles of women, rather than their knowledge and broader expertise about science, hazards, and local conditions.

In recent years, many women weathercasters have come forward to express their rejection of the term “weather girl” in individual interviews (Diabri, 2017) and in panel- based segments on both the Weather Channel (Gallucci, 2017) and the Weather Network

(Ibrahim, 2018). The most recent and news-making example of broadcast meteorologists rejecting the “weather girl” label happened in response to a climate-change-denying,

Australian official, Craig Kelly, labeling Laura Tobin, a broadcast meteorologist, as a

“pommy [British] weather girl,” after she rejected his claims on-air that the Australian wildfires weren’t connected to climate change (Whigham, 2020).

This is just one recent example illustrating how the term “weather girl” has been weaponized by a conservative man to delegitimize and squelch the scientific expertise of a woman broadcast meteorologist; however, a completely random, quick survey of social

media platforms reveals similar use by conservative and liberal men and women alike to discredit or belittle women weathercasters. As examples, one man responded to a tweet by U.S. Representative Alexandria Ocasio-Cortez [the youngest woman elected to US

Congress] by calling her “the congressional equivalent of the local news channel hiring a pretty weather girl. Totally vacant of thought” (Gump, 2020); a woman critical of Presi- dent Trump suggests he may be auditioning as a “Fox News weather girl” in order to get himself on TV daily (Carrigan, 2020); and a liberal male user suggests U.S. Press Secre- tary Kayleigh McEnany will make “an excellent weather girl one day… NOT” (Mal- licoat, 2020). In some instances, Twitter users reference “weather girl” in a neutral or even positive context (Ostrowski, 2020; Rumrill, 2020), sharing their support of women broadcast meteorologists while illustrating the contextual nuances associated with this label. Because these examples provide only anecdotal evidence of the term’s past and current use in news and popular social media formats, our research focuses on prevailing weathercaster attitudes towards both women broadcast meteorologists and the “weather girl” stereotype; how this stereotype is perpetuated both within and outside of the broadcast meteorology community; how these attitudes and long-set stereotypes consequently shape views of the general public; and the direct impact for women weathercasters of using the term “weather girl” to describe women in broadcast meteorology.

Additionally, several characteristics of the “weather girl” stereotype that were previously explored in our research — namely, the assumption that women weathercasters are sexually attractive and use their appearance, rather than their intelligence, to get ahead in the broadcast meteorology field (Perryman and Theiss, 2014) — are still

prevalent, even among those in the weathercasting field. A notable example of this stereotypical-based thinking is illustrated in the legal case of Kyle Hunter, a male broadcast meteorologist who brought a discrimination lawsuit against both CBS and ABC corporations on the grounds that the companies’ affiliate stations in Los Angeles (KCBS and

KCAL-TV, respectively) had “repeatedly shunned [not hired him] for numerous on-air broadcasting positions due to his gender and his age” (Hunter v. CBS Broadcasting Inc.,

2013). Hunter claimed that “KCBS decided to hire Jackie Johnson, a ‘young attractive female’ who had previously served as the weather anchor on KCAL’s prime time newscast” (Hunter v. CBS Broadcasting Inc., 2013) instead of an older male like himself - claiming to be “far more qualified, and far more experienced, [than] the female hired…”

(Belloni, 2012) and alleging that “he contacted the station manager and was told that he had not been considered for the position because KCAL-TV ‘catered to male viewers' and that Hunter ‘wouldn't be the type men would want to look at’ ” (Belloni, 2012;

Hunter v. CBS Broadcasting Inc., 2013). When his lawsuit was dismissed, using the peculiar logic that hiring practices are protected under free speech legislation, Hunter brought a similar lawsuit against the local ABC affiliate in Los Angeles, claiming the station “decided to hire a young, attractive female for this position -- preferably a blonde who physically resembled Indra Petersons,’ the woman who previously held the job”

(Couch, 2013), a case that was also dismissed. That a male meteorologist would directly single out the sexual attractiveness of women broadcast meteorologists, including hair color, while claiming that his own education and experience better qualified him for the position over these women, is further proof that the “weather girl” stereotype still shapes

the views of even individuals working in the weathercasting field. Thus, his claims regarding station hiring practices are briefly examined in our research to determine if (and how) these protocols are being impacted by the stereotypical “weather girl” stigma.

Another example of this persistent and fetishistic “weather girl” stereotype is am- ply corroborated in Internet searches. For example, one study conducted a random

Google search and found that for the term “‘female meteorologist’ results show every single link to an article regarding why ‘all female meteorologists are wearing this dress!’, whereas ‘male meteorologist’ results show rankings of important male meteorologists and contributions they have made to the field” (Chouinard, 2016, p. 13). Additionally, several recent qualitative, interview-based analyses note the continued presence and impact of the term “weather girl,” with a profusion of stereotypes associated with this label

(Anderson, 2017; Chouinard, 2016), evidence that supports continued work on this topic.

Our research seeks to determine the extent to which the “weather girl” description — and stereotypical characteristics associated with this still often-attributed title — continue to impact women working in weathercasting (Figure 3.1).

Figure 3.1: Composite view of “weather girls” on one website from Winkler 2019; from top left, clockwise: Evelyn Taft, KCAL- TV (Los Angeles); Dylan Dreyer, MSNBC & NBC News; Jackie Johnson, KCBS (LA); Me- gan Glaros, Good Morning America (Chi- cago); Marilu Kaufman (Mexico City); Lauren Sanchez, The View.

However, the opposite use of the term— and consequentially the subversion and appropriation of derogatory, often-stereotype-based slurs by the recipient of these slurs

(e.g., “we’re here; we’re queer”) into a positive identifier — has been extensively documented (Ritchie, 2017). This appropriation of slurs has been interpreted as a mechanism through which group identity and solidarity can be formed, as Ritchie (2017) states, “appropriation involves members in the target group working together to subvert the derogatory element of a slur. When appropriation is successful, speakers in the target group can use the slur to express something positive which conveys group solidarity” (176). This seems to be at least partially true in the case of the “weather girl” term, as anecdotal evidence suggests some women embrace the term, even to the point of implementing it in

their social media handles (e.g., @WxGirl), a point of view this study seeks to better understand.

3.2.3 Role of Race/Ethnicity

Race/ethnicity has played an important role in several recent examples of viewer- based harassment disclosed by women weathercasters (Duster, 2017; Starr, 2014). In response, leaders in the field of meteorology — including Marshall Shepherd, the 2013 president of the American Meteorological Society — published commentaries that analyzed the connection between race/ethnicity and viewer feedback (Shepherd, 2018).

Shepherd includes two such examples of non-White women weathercasters who were harassed by viewers (and one even fired) simply because their hair was deemed too

“curly.” He further points to the connection between hair and race/ethnicity, stating that these women felt the need to “mask their true hairstyles because of the ‘unwritten’ rules of the [broadcasting] industry,” rules that reflect the racially-biased public preference for smooth hair over the more “natural” styles most commonly worn by Black women, and states the following:

There has been an underlying perception in society that there are only certain standards of beauty when it comes to hair. If you pay attention to past beauty magazine covers, Hollywood standards of beauty, or even childhood dolls, the hair presentation is usually straight and flowing. You don't even have to go back that far. There are current labor rules and laws that explicitly send messages that thick, curly, or “nappy” hair textures are not professional, political in nature, or messy. (Shepherd, 2018, p. 3)

In addition to these anecdotal examples of viewer harassment directed at Black women, further evidence that broadcast meteorology has found only limited space for ethnic/racial minorities is readily found in the lack of research — including survey-based studies — conducted to understand the experience of Black weathercasters. For example,

most surveys of broadcast meteorologists only evaluate other demographic data such as gender, education/certification, rank/title, years of experience, and views on certain current, science-based issues such as climate change (Maibach, 2017). Another study related to ethnicity in the field of broadcast meteorology focused just on equitable access to meteorology courses at two- and four-year colleges designated as Historically Black Col- leges & Universities (HBUC) (White et al., 2013). More recently, Rainear (2019) found that weathercaster race/ethnicity as perceived by an audience did not significantly impact an audience’s perspective of the weathercaster’s credibility, and that – in certain instances — Black men were viewed as most trustworthy, even over white men; however, women were always perceived as significantly less credible than men, indicating gender, rather than race/ethnicity, to be a more limiting factor in perceived weathercaster credibility (Rainear, 2019). Nevertheless, research also suggest that individuals who identified with multiple stereotyped groups (e.g., Black women) face more discrimination than those who identify with only one marginalized group (white women) (Remedios and

Snyder, 2018), which is inconsistent with previous findings of the trustworthiness of

Black men (Rainear, 2019). What is not known, then, is the degree to which negative attributes associated with a gender-based stereotype like the “weather girl” trope, that is additionally situated in a predominantly white field like broadcast meteorology, are perceived by and impact the careers of Black and Latina women weathercasters. In our survey of men and women weathercasters, we incorporate ethnicity/race to determine if knowledge and impacts of the “weather girl” stereotype extend to all weathercasters regardless of race/ethnicity.

3.3 Methods

The goals of this study are twofold: a) to determine whether or not the “weather girl” stereotype, as portrayed by popular media, is similar to how women and men weathercasters view and interpret this label; and b) to determine if women broadcast meteorologists report being disproportionately impacted due to the weather girl stereotype. Meth- ods based on these goals are further described below.

Prior to participant solicitation, all survey documents, including an advertisement flier, application form, consent form, and full copy of the questionnaire questions, were all submitted to the UNR Institutional Review Board ([1114547-1] Demographic and Ex- periential Survey of Broadcast Meteorologists) for review as a Social/Behavioral exempt status. Because broadcast meteorologists are considered public figures, with contact information available to the general public, the study was approved to be Exempt (Category

2), with additional exempt status extended for follow-up surveys of the same population.

3.3.1 PARTICIPANT SOLICITATION METHODS

During a one-month span from November to December of 2017, a list of contact information for broadcast meteorologists — grouped by both Nielsen market rankings (top markets [1–50], middle markets [51–100], and small markets [101–210]) and major networks (ABC, CBS, FOX, and NBC) — was compiled. A few networks, primarily in middle and small markets, are jointly owned by a single company and share newscasts with other networks. In these rare cases, efforts were made to determine the primary network that weathercasters stated they were affiliated with, including the station affiliation used in their email address. The total number of broadcast meteorologists compiled in our

target population is 2,151; however, only 1,312 weathercasters had unique, personal email addresses posted on their station websites. Using this convenience sampling strategy, all of the 1,312 weathercasters with publicly available email address was sent an individual invitation to participate with a unique URL link to our survey, a flyer describing the study and its purpose, and an explicit request to not share the link with anyone else.

Approximately 50 stations that we reviewed either provide a general station email address as a contact for all station employees or host a message software platform embed- ded on the station website as a means to contact employees. For these stations, we crafted a separate email flyer asking each station’s weather team employees to email back from an individual email account, either their personal account, or a private email linked to the station, in order to receive a unique survey URL link, and to preserve privacy.

The survey was conducted over a one-and-a-half-month period from January to

March 2019. We sent two follow-up reminder emails to respondents at the halfway point of the survey period and a day prior to the survey closing. Additionally, the author developed and posted advertisement reminders on social media, alerting those that had been sent a link to check their emails.

We realize that by using unique survey links instead of one anonymous, general link for all survey participants, sample size was potentially limited. We felt, however, that it was more important to limit extraneous or falsified survey responses, since the topic of the survey could be viewed by some participants as divisive, in calling out potential injustices or harassment experienced by individuals who identify as members of a minority group within the broadcast meteorology field.

Weathercaster email addresses were collected approximately a year before the survey was sent out in an effort to sample a variety of experiences from newer, less experienced weathercasters hired since data collection, in addition to the views of older, more experienced weathercasters who might have left the field over the previous year. Efforts were made to acquire email addresses of new station hires, whose profiles might not yet be available on the station website, by adding a statement in the survey instructions request- ing that weathercasters encourage everyone on their weather team to reach out and request a unique access code to the survey, if they had not been emailed one already. We distinguished among weathercasters currently working in the field and those who have since left their station job through a survey question on this topic that differentiates between current and past weathercasters.

3.3.2 SURVEY INSTRUMENT: THEORY AND PURPOSE

In order to differentiate how broadcast meteorologists perceive the “weather girl” label— as either a negative slur; a more positive, subversion or appropriation of the term; or neither; — our survey included several open-ended questions asking respondents to describe the personality, educational, and physical traits of a “weather girl,” as well as perceived connotations (positive or negative) associated with the term. We also asked women respondents to describe whether or not they felt that the term “weather girl” had impacted their career or relationship with viewers in any way, to further and better ascer- tain the motivating factors behind rejecting or embracing the term and tease out nuances associated with the term’s use in public vs. professional settings.

To compare weathercaster perception of the “weather girl” stereotype with previously found characteristics of this stereotype, survey questions were developed based on the “weather girl” characteristic categories observed in popular media and defined in Per- ryman and Theiss (2014). Additional questions were posed to gauge knowledge and outside application and recognition of the “weather girl” title by the public, newsroom management, and other broadcasters, in order to determine potential career impacts associated with this stereotype. Our survey questions are included in Table 3.1 below, and the full set of survey questions with response options is provided in Appendix C.

One final note related to the metric for educational background used in this study: the

American Meteorological Society’s Broadcast Meteorologist Certification seal (formally, the “Seal of Approval”) is the highest accolade in the broadcast meteorologist field. To receive this seal, applicants must meet a set of requirements for approval that include holding a meteorology degree, a minimum of three-years working as an on-air broadcast meteorologist, pass a written test covering principles of meteorology, and submit to an evaluation of the meteorologist’s on-air broadcast presence – in addition to paying application, testing, and renewal fees, amounting to upwards of $700 (AMS, 2020).

TABLE 3.1: Survey instrument, based on the main descriptive categories associated with the “weather girl” stereotype as outlined in Perryman and Theiss (2014).

Survey Questions 1. Do you currently OR have you EVER worked as a broadcast meteorologist? (allows quali- fying answer)

2. What gender do you identify as?

3. What is your age?

4. Are you familiar with the term "weather girl"?

5. Briefly list any personality, educational, and/or physical traits that you associate with the term "weather girl."

6. Have you ever been called or described as a "weather girl"? (women only)

7. When you were labeled as a "weather girl," did it have a perceived positive or negative connotation? (women only)

8. Do you feel that the term "weather girl" and/or the traits associated with this stereotype have impacted your job and/or relationship with the viewing audience in any way (good or bad)? Please briefly explain your answer in the text box below. (women only)

9. Do you feel that your gender has impacted - either positively or negatively, or both - your career as a weathercaster?

10. Do you feel that your physical appearance has impacted your career - either positively or negatively, or both - as a broadcast meteorologist?

11. Have you ever felt the need to change your hair color and/or style in order to further your career?

12. Have you ever felt the need to change your weight in order to further your career?

13. Have you ever felt the need to change your clothing style or type in order to further your career?

14. Have you ever received an email, message, or comment (positive or negative) from a viewer (of any gender) about your physical appearance and/or clothing style?

15. Have you ever received an email, message, or comment (positive or negative) from a broadcasting colleague or station manager (of any gender) about your physical appearance and/or clothing style?

16. Do you feel that your race/ethnicity has impacted - either positively or negatively, or both - your career as a weathercaster?

3.3.3 SURVEY ANALYSIS TECHNIQUES

Discrete Dataset Responses

Survey questions with discrete response options were first analyzed using descriptive statistics to determine the average mean, median, and mode of survey respondents.

We then differentiated these results by gender and conducted a Chi-square test (for respondent counts greater than 0) or a Fisher’s exact test (for answers with zero respondents in either group) to determine the statistical relationship between responses from women versus men.

Continuous Dataset Responses

For open-ended survey questions, including those prompting respondents to describe physical, behavioral, or other gender-specific traits associated with the “weather girl” stereotype, a word frequency count was first compiled. Responses were then coded and analyzed according to the category and purpose in our analysis, using methods described below.

Our decision to numerically quantify commonly referenced coded themes is, in part, driven by research findings suggesting that men typically communicate more frequently than women, in both oral (Nittrouer, 2018) and written (Van Duyn, Peacock, and

Stroud, 2019) forms, potentially leading to over-representation in our qualitative analysis.

To control for this, individuals that referenced a thematic element more than once were only coded as a single contributor, reducing this potential data bias. Additionally, we selected quantification of qualitative data in order to distinguish the most important themes found in our open-ended survey responses. While quantification of qualitative data is not a common practice in social science research, there is a precedent for this

methodology (de Block and Vis, 2019), though caution should be used in interpreting these elements of significance in a traditionally quantitative manner.

Study Limitations

Due to time constraints, this study surveyed only the weathercasters working at four major networks (ABC, CBS, NBC, and FOX), leaving out other networks (such as the CW and Telemundo) that employ a smaller subset of the weathercaster population.

Additionally, as mentioned above, email addresses were compiled a year prior to the survey being sent out, creating the potential that new hires were not surveyed, while other weathercasters who may have left the station in the year since data collection were surveyed; however, we explain the rationale for this method in the section above. Finally, relatively small sample and response sizes (while standard for research in the broadcasting field as noted above) restrict the generalization of these findings to the broadcast meteorology field as a whole.

3.4 Results and Analysis

3.4.1 Demographics of survey respondents

OVERVIEW: GENDER, AGE, AND RACE/ETHNICITY

Overall, a total of 185 respondents completed the survey, a response rate of 14% of those solicited and 8% of all weathercasters identified from station websites. While this response rate is much lower than the “optimal” rate of 80% (Hendra and Hill, 2019), recent research suggests that for surveys conducted in the journalism field, including broadcasting, a reasonable response rate is closer to 8.4% (Finneman, Thomas, and Jenkins, 2019).

Additionally, a recent survey of broadcast meteorologists published in the Bulletin of the

American Meteorological Society had a response rate of 5% (Reed and Senkbeil, 2020), indicating that our response rate of 8-14% is not unreasonable for our surveyed population.

Out of these respondents, 54% of participants identified as male and 46% identified as women (Figure 3.2). See Table 3.2 for the demographic breakdown of all survey respondents.

Self-Reported Gender of Survey Respondents Figure 3.2: Self-reported gender of survey applicants. NOTE: The number of participants in each of these gender groups can be con- Women Men sidered the same in all analyses 46% 54% and resulting figures, unless oth- n=85 n=100 erwise stated in the caption (due to some respondents opting-out of certain open-ended questions).

TABLE 3.2: Demographics of all survey respondents. Respondent Percent of Average Self-Identified Race/Ethnicity Respondents Age Gender white 85% 32 years Black/African American 3% Women 46% old Hispanic/Latinx 7% Biracial 5% white 93% 42 years Black/African American 3% Men 54% old Hispanic/Latinx 3% Biracial 1%

The majority of respondents were between the ages of 25 and 34, with an average reported age of 37-years-old and the median age of 34-years-old (Figure 3.3). Age results were also analyzed by gender, in order to compare gender-differences in age. We found that both the mean (32 years old) and median (30) age of women was approximately ten years younger than the mean (42) and median (41) age of men. Additionally, the male population had a larger standard deviation of ages (12.6) — a lower minimum age, and higher maximum age,Histogram than women of (Table Survey 3.3). Respondant The majority Ages(36%) of women respondents were40% in the 25–29 age group, while the majority of men (19%) respondents were in 35% 32% 32% the 30–34 age group. 30% 25% 20% 17% 15% 11% 10% 8% 5%

0% 20-29 30-39 40-49 50-59 60+

Figure 3.3: Age histogram of all survey respondents. n=185

TABLE 3.3: Exploratory statistics of survey-respondent age by gender.

Gender Mean Median Maximum Minimum Std Deviation Male 42 41 65 20 12.57 Female 32 30 56 22 7.47

Data show that the majority of survey respondents identified as White/Caucasian (89%), with small numbers of respondents identifying as Hispanic/Latinx (5%), African Ameri- can/Black (3%), and biracial (3%) (Figure 3.4). When examining race/ethnicity of respondents by gender, data show women respondents to be slightly more diverse than

male respondents, with a slightly greater percentage of Hispanic/Latinx and African

American/Black respondents (Figure 3.5).

Percent of All Respondents Black or African American 3% Biracial 3% Hispanic/Latinx 5%

White/Caucasian 89% n=185

Figure 3.4: Race/ethnicity of all survey respondents. NOTE: None of the survey respondents reported identifying as Asian/Pacific Islander or American Indian/Alaskan Native.

Self-Reported Race/Ethnicity of Self-Reported Race/Ethnicity of Women Respondents Men Respondents Black/African American Black/African American 3% 3% Biracial Biracial 5% 1% Hispanic/ Latinx Hispanic/ 3% Latinx 7%

White/Caucasian White/Caucasian 85% 93% n=85 n=100

Figure 3.5: Race/ethnicity of female (left) and male (right). NOTE: None of the survey respondents reported identifying as Asian/Pacific Islander or American Indian/Alaskan Native.

MARKET SIZE AND GEOGRAPHICAL LOCATION

When asked about the location of their market, survey respondents were presented with the following 9 standardized geographical regions to choose from: New England,

Middle Atlantic, South, Midwest, Southwest, Pacific Northwest, Nationwide, Other

(please specify). Due to the fact that several survey respondents selected “Other” and listed specific states (i.e. Texas, California, Colorado) and vernacular areas (i.e. Great

Plains, Rocky Mountains, Southern Plains, West Coast, Mountain West), the data was analyzed and further grouped into 4 larger U.S. regions, based on the following World Atlas

(2019) categories: West, Midwest, Northeast, and South (see Simpson, 2020 for a breakdown of specific states in each region). Only ten survey responses (out of 185) were manually added to these new regional groups, based on these categories. One response

(Southern Plains) was an ambiguous region, with portions in both the Midwest and

Southern area, and was grouped in the Midwest category, since the majority of this vernacular region is situated north of Texas. Table 3.4 shows the number of respondents per market region and by gender. Both gender groups were mostly distributed equally in the four categorical geographical regions, with slightly more regional variation found for women respondents, including higher numbers of women in the South, but fewer in the

Western markets.

TABLE 3.4: Geographical market location of total survey respondents and by gender of respondents.

Men Women Regional Totals West (Southwest and Pacific Northwest) 21 17 38 Midwest 29 23 52 South 26 25 51 Northeast (Mid-Atlantic and New England) 23 19 42 Nationwide 1 1 2

Total 100 85 185

3.4.2 Analysis of Weathercaster Perception of the “Weather Girl” Stereotype

In order to determine weathercaster perception of the “weather girl” stereotype, and if women broadcast meteorologists reference certain negative traits when describing this stereotype more often than their male colleagues do, we analyzed – by gender — survey responses to questions about the “weather girl” stereotype (see Table 3.1 for survey questions).

“WEATHER GIRL” DEFINITION, INTERPRETATION, AND CONNOTATION

Respondents were first asked if they were familiar with the term “weather girl,” with

100% of women and 98% of men reporting familiarity with the term. Participants were then asked to describe in their own words the “personality, educational, and/or physical traits that you associate with the term ‘weather girl.’” These open-ended responses were then manually coded into thematic categories using NVivo software platform. While codes were based on the “weather girl” attributes found in the portrayal of “weather girls” by movies and TV shows (Perryman and Theiss, 2014), a grounded theoretical coding approach, we also adapted coding to the traits that emerged during the data coding process

(a priori coding approach) and created a few additional categories based on our findings

(Saldaña, 2015). Efforts were made to keep coded responses in the voice of respondents

(in vivo coding); however, in order to generalize some thematic concepts (eg. “neutral definition), process and values coding techniques were also incorporated (Saldaña, 2015).

A brief overview of the codebook used to analyze this data, including common terms grouped into each set, can be found in Table 3.5.

TABLE 3.5: Overview of codebook used in analysis of respondent’s open-ended description of personality, educational, and/or physical traits associated with the “weather girl” stereotype.

Category Code Description Development Category Timeline Age Any mention of age (young or old) During coding Any statement taking the term “weather girl” at face-value, Basic Neutral suggesting the term to mean only “woman broadcast mete- During coding Definition orologist” with no other connotations Career Any mention of terms associated with early career, first job, Before coding Experience or unseasoned Any mention of the term’s origin, including changes/evolu- Compares Old tion of the term itself (eg. old = weather girl; new = meteor- During coding to New ologist), or reference to a different generation/time period Education + Any mention of educational background, degrees, seals, cre- Before coding Merits dentials, or general knowledge obtained through education Any mention of gender-based domestic activities, including Gender Roles home life or children; also includes “high-pitched voice,” a Before coding trait that emerged during the coding process Any mention of intelligence, qualification for the job, or un- Job Skills Before coding derstanding of weather concepts Personality Includes the terms “bubbly,” “ditzy,” “Type-A,” “fun,” and Before coding Trait other generalized descriptions of personality traits Any mention of physical attributes, including weight, hair Sex Appeal color or general attractiveness, as well as clothing descrip- Before coding tions (eg. “tight-fitting” or “unprofessional” clothes) Any mention of the term “hired for” or suggestion that the Utilized by “weather girl” received a position based on any other Station for a During coding trait/characteristics outside of her meteorological expertise Purpose and/or experience

The general categories based of “weather girl” traits that were used to code these open-ended responses are the following: Education/Merits, Sex Appeal, Personality

Traits, Age, Job Skills, and Career Experience. The three attribute categories with the highest number of total coded respondent references to “weather girl” categories were

Education/Merits (103 coded references), Sex Appeal (93), and Personality Traits (50)

(Figure 3.6). After analyzing all responses, two general themes emerged with regards to the “weather girl” stereotype: the pitting of knowledge versus persona (ie. looks and behaviors). This is also validated in the top three categories that emerged in the coding (Fig- ure 3.7) and often in the individual responses as well, generalizable to “’weather girls’ are attractive, but not intelligent nor educated in the meteorology field.” This juxtaposition of

“beauty vs. brains” was used to group sub-categories of our coded traits, and also broken down into respondent gender, all shown in Figures 3.7 and 3.8.

Total Number of Coded References by "Weather Girl" Stereotype Trait 103 100 93 80 60 50

40 30 27 20 12 8 0 Education and Sex Appeal Personality Age Job Skills Career Gender Roles Merits Traits Inexperience

Figure 3.6: Total number of coded references to common “weather girl” attribute categories, as relayed by survey respondents

Total Percentage of Women and Men Weathercasters Referencing Each Grouped Stereotype Category and Sub-Category

Women Men 76% 80% 57% 61%58% 60% 38% 40% 27% 18%17% 22% 12% 8% 20% 7% 7% 4% 0% 2% 0%

Figure 3.11: Total number of coded references to common “weather girl” attribute Traits Career categories, as relayed Skills byJob survey respondents Merits NOT a Personality Sex Appeal Sex Voice Pitch Voice Inexperience Gender Roles Gender Meteorologist Education and Education Knowledge Looks/Behaviors

Figure 3.7: Percentage of coded references to common “weather girl” attribute categories by women versus men, grouped into categories and subcategories

Total Percentage of Women and Men Weathercasters Referencing Each Grouped Stereotype Category and Sub-Category

Women Men 30% 28% 23%

20% 16% 14% 14% 12% 10% 7% 7%

0% Age Utilized by Station for Basic Neutral Compares Old to New a Purpose Definition Either Knowledge or Knowledge VS. Stereotype Not Stereotype Doesn't Looks/Behaviors Looks/Behaviors Negative Exist Anymore

Figure 3.8: Total number of coded references to common “weather girl” attribute categories, grouped into subcategories and by gender/total numbers

As might be expected, a few subcategories didn’t fit into the established overarching themes, but were related to these themes in unique ways; and while these categories cor- responded to far fewer coded references, several interesting insights about the “weather girl” stereotype. For example, responses for the “Age” category mostly pertained to

“young,” which could be interpreted as referencing knowledge or looks, meaning this could refer to a young-looking person or an inexperienced person. Another trait that emerged was a framing of the “weather girl” as being hired by TV stations because of her looks alone, implying that these women were incapable of embodying both looks and intelligence and instead pitting the categories against each other. Other respondents referenced the past origin of this stereotype in the ’60’s and ’70’s, and described the term

“weather girl” as antiquated, evolving to mean something else, and/or rarely used in current vernacular, seemingly negating the stereotype’s current existence. Finally, one of the most interesting responses that emerged — one that was given four times as often by men than women respondents — was a generic, tone-neutral (with neither a negative or positive connotation) definition of “a woman who is a broadcast meteorologist,” implying that the “weather girl” stereotype is perceived by these respondents to have no negative connotation or potentially not existing at all.

A list of chi-square test comparisons by gender and p-values, for each thematic category, are listed in Table 3.6. Five categories had chi-square values that were greater than

1, indicating a difference in usage of categorical language between women and men in their descriptions, including the following: Education, not a meteorologist, Personality

Traits, Age, and Neutral Definition. However, only two descriptive categories were statistically different, with significantly more women (76%) than men (57%) referencing a

69 lack of education or merits in their descriptions (�2 = 6.3, p=<0.05), and men (28%) offering a neutral working definition as their description of the “weather girl” significantly more often than women (7%, �2 = 11.8, p=<0.01). These findings suggest that women value their educational background in the field and see this background as critical to sep- arating themselves from the negative “weather girl” stereotype. On the other hand, men don’t necessarily equate the “weather girl” stereotype to educational achievements, and instead view the term as interchangeable with “broadcast meteorologists,” a view that, based on our study, women weathercasters do not share.

TABLE 3.6: Percentage of women and men respondents that used language associated with the established thematic categories when describing the “weather girl” stereotype, along with chi-square values between women and men populations and associated significance p-values. Bolded �2 values are statistically significant.

Women Men �2 p-value

Education 76% 57% 6.2912 <0.05 Job Skills 18% 17% 0.0135 not significant Not a meteorologist 22% 12% 2.5948 not significant Career Inexperience 8% 7% 0.1106 not significant Gender Roles 7% 4% 0.7988 not significant Sex Appeal 61% 58% 0.1438 not significant Personality Traits 38% 27% 2.3145 not significant Age 23% 16% 1.3526 not significant Station Utilization of 14% 15% 0.029 not significant Looks or Gender Neutral Definition 7% 28% 11.7219 <0.01

IMPACTS OF THE “WEATHER GIRL” STEREOTYPE ON WOMEN METEOROLO-

GISTS

Because the “weather girl” stereotype differentially impacts women the most, several follow-up questions were conveyed to only women weathercasters to understand these direct stereotype-related impacts to their career experiences. When asked, the percentage of women weathercasters who reported that they had been called a “weather girl” was

99% (n=85), with only one woman reporting they’d never been called this term. When asked about the perceived connotation of being labelled as a “weather girl,” nearly half of respondents (47%, n=82) stated that the perceived intent was both positive and negative, indicating that they’ve been referred to by this term more than once and highlighting its ongoing, multi-faceted present-day usage (Figure 3.9). However, 27% of women — the second-largest group out of those surveyed — reported “neutral/no connotation” when this term was applied to them directly, followed by 15% reporting a perceived negative connotation, 7% a perceived positive connotation, and 4% unsure of the connotation (Fig- ure 3.9). This breakdown further indicates that women weathercasters perceive use of the term “weather girl” as a descriptor rather than put-down, but also that a potentially larger group of women weathercasters recognize the stigma attached to this title.

Perceived Connotation of "Weather Girl" Label as Reported by Women Weathercasters 48% 50% 40% 27% 30% 20% 15% respondents 7% 10% 4% Percent of women 0% Both Neutral / No Negative Positive Unsure connotation

Figure 3.9: Women respondents’ perceived connotation (positive, negative, both, and unsure) of the term “weather girl” when labeled this term by others

To further determine if women weathercasters saw the “weather girl” stereotype as a barrier to building trust with their viewing audience, participants were also asked if they felt that the term "weather girl" and/or the traits associated with this stereotype have impacted their job and/or relationship with the viewing audience in any way (good or bad).

Results were split, with over half of women respondents (51%; n=83) stating that the

“weather girl” stereotype has real impacts on women working in the field of broadcast meteorology.

Although only a small subset of women elaborated on how the “weather girl” stereotype does (or does not) impact their daily lives, 33% of women in this group (and 17% of all women surveyed) described encountering a decrease in self-confidence when labeled with this term; 31% (16% of all women surveyed) associated a negative connotation with the term; and 26% (13% of all women) reported feeling less respected, valued, and credible in the eyes of the person who referred to them as a “weather girl.” On the flip side, of the women who reported no career impacts related to the “weather girl” term, 27% (13% of all women surveyed) indicated either a lack of emotional or other connection to the term, no experience with being called a “weather girl,” or acceptance of the term based on the fact that they haven’t received a degree in atmospheric science and aren’t, therefore, qualified to consider themselves a “meteorologist.”

Two additional themes that emerged across both groups (women reporting stereotype impacts AND those reporting no impacts) were the penchant of respondents to rationalize the public’s use of “weather girl” as a descriptor rather than as a slight, but also to actively educate users about the term’s negative background and implications they encoun- tered. 22% of respondents who reported the “weather girl” stereotype had no impacts

(and 2% that did report impacts from the stereotype), downplayed the public’s use of this term, primarily citing a public ignorance of the term’s negative connotations and hypoth- esizing that “weather girl” is just “easier” to remember, spell, and understand than the term “meteorologist.” Additionally, 5% of both respondent groups stressed that when labeled as a “weather girl,” they were quick to address and correct the title to “meteorologist.” Again, while the patterns outlined here are interesting, the total number of women who even provided responses to the open-ended portion of this question was small to begin with, so we decided against running statistical tests as it would be difficult to draw strong, definitive conclusions from this subset of data.

INDIRECT EFFECTS OF THE “WEATHER GIRL” STEREOTYPE

In order to evaluate additional indirect impacts of the “weather girl” stereotype on the experiences of women versus men weathercasters, several follow-up questions regarding the main attributes of this stereotype were asked, including questions on how gender and physical appearance characteristics impacted respondents’ career experiences.

Gender-Based Career Impacts

While gender could be categorized as an extension of physical attributes, as gender is largely perception-based, we wanted to explicitly ask respondents if their gender identity impacted their career, to both gain a better understanding of how weathercasters viewed gender-based impacts to their career, as well as how they viewed their own gender in relation to the opposite gender. We should note that gender is a fluid, culturally constructed concept, but because none of the respondents identified as a gender other than man or woman, we evaluated these responses through the lens of a gender binary.

When women and men participants were asked if their gender identity impacted their career, nearly all women respondents (94%) reported some career impacts from gender

(regardless of effect — positive, negative, or both), a significantly larger group than men respondents (66%, p=<0.01) (Figure 3.10). When asked about the impact effect, significantly (p=<0.05) more men (17%) reported positive career impacts from gender than women (7%).

Reported Impacts of Gender on Career

Women Men

100% 81% 75%

50% 46%

26% 25% 17% 6% 7% 8% 1% 3% 5%

Number of Respondents 0% No Yes - both Yes - mostly Yes - mostly Unsure positively and negatively positively negatively

Figure 3.10: Respondent perception of how their gender has impacted their career, broken into gender and impact effect (positive, negative, both, and unsure)

To better understand the nuances behind how men and women weathercasters see gender as impacting their career, respondents were given the option to explain their thinking in an open-text format. To organize findings from responses to this open-ended question, we developed categories from commonalities that emerged from the dataset. Most responses framed their description of gender impacts as a comparison to the opposite gender, providing evidence as to why men or women had an advantage in the broadcast

meteorology field over the opposite gender. Common subcategories of supporting evi-

dence were established and included (A) hiring advantages, (B) career advancement, and

were not shared between the two gender groups but were common enough responses to

include as additional categories, including (D) pay advantage, (E) less harassment, and

(F) gender advantage that varies based on management or station needs. Similarly, re-

sponse themes NOT associated with gender advantage but that were commonly found in

responses include (G) references to the “weather girl” stereotype and (H) references to

viewers (see Table 3.7 for entire list and frequency of reference by gender group).

TABLE 3.7: Percentage of women and men respondents that used language associated with career impacts of gender for women versus men weathercasters, along with chi- square values between women and men populations and associated significance p-values. Bolded �2 values are statistically significant.

Women Men 2 or � p-value (n=84) (n=74) Fisher’s* Hiring 2% 4% 0.3594 not significant Career Advancement 7% 4% 0.6987 not significant Men Perceived Trust/Credibil- 52% 14% 26.4188 <0.01 Advantage ity/Seriousness Less Harassment 45% 16% 15.3188 <0.01 Higher Pay 5% 0% 0.1232* not significant Hiring 37% 43% 0.6593 not significant Women Ad- Career Advancement 1% 7% 3.3366 <0.1 vantage Perceived Trust/Credibil- 0% 3% 0.4988* not significant ity/Seriousness Gender Advantage Depends on Station 2% 22% 14.4281 <0.01 No Gender Impacts 1% 7% 3.3366 <0.1

To assess the number of individuals attributing a perceived gender-based career advantage to women versus men, we first assessed the subcategories and found that over one-third of both women (37%) and men (43%) relayed the view that women had a hiring advantage –mostly due to diversification practices at the station management level

(�2 = 0.6953, not a significant difference between men and women). However, over half of women (52%), versus only 14% of men, indicated that men have an advantage in being perceived by viewers as more trustworthy, credible, and serious than women; a chi- squared test indicated this reporting difference between men and women to be large and statistically-significant (�2 = 26.4, p<0.01). Findings associated with differential gender- based-opportunities for career advancement were weaker and more mixed by gender (see

Table 3.7), indicating more uncertainty between gender groups; however, half of women

(45%) also reported that men experience less harassment from viewers than women, a view not as commonly expressed by men (16%). The fact that men are less likely to report their own gender-based career advantages, coupled with the finding that a greater number of men (22% vs. 2% of women; �2 = 14.4, p<0.01) expressed gender advantage to be variable and dependent on station, indicates that either men are largely unaware of or overlook their own gender advantages in the field of broadcast meteorology, or possibly view the career advantages that benefit women as more important than their own advantages.

We lean towards the latter explanation, as 20% of men respondents directly stated in a variety of ways that they’d been “passed over” for a job that was given to a less qualified woman candidate, simply because of her gender or her appearance (see Table 3.8 for

76 a list of these statements). The fact that almost a quarter of men directly cited –in the words of one man — a “reverse discrimination” against men in the hiring process indicates that a large number of men view women as less qualified than themselves and thus believe this negative “weather girl” stereotype to be at least partially true. Our findings seem to suggest that male broadcast meteorologists help fuel the stigmatized “weather girl” dichotomy of “beauty not brains,” that is also externally propagated by viewers and popular culture, as one woman notes that, “people assume you’ve gotten where you are simply because you’re a woman or just a “pretty face” who doesn’t know the science.”

Our findings are best summarized in the words of a woman survey-respondent:

The negative impacts [of gender] are related to the positive impacts. Because there are positions that are solely held open for qualified female candidates [the positive impacts], male meteorologists end up resenting women in this industry because they feel like they are passed over for positions because they aren't a woman. But what they fail to acknowledge (a lot of the time) is that I will more than likely be passed over for Chief Meteorologist positions because I’m not a man.

And while many of the men surveyed felt that women have benefited from the diversification of the field and have been “given” seemingly rare job opportunities over men, as one qualified woman respondent (who holds a Bachelor’s degree in Atmospheric Sci- ence) notes, women don’t necessarily view this hiring advantage as a completely positive thing:

I know that I was hired at my current station because my News Director was looking for a ‘female.’ This makes me feel as if I was not hired based on my skills and abilities, but rather based on my gender.

TABLE 3.8: Responses by men weathercasters to the question: “How has your gender impacted your career and/or experiences as a weathercaster? Feel free to provide as many or as few examples as you want in order to communicate your experience!”

“…I will say that if men were wearing v necks on the news we would probably receive a few emails. I believe women are the givers and creators of life and the greatest thing on this planet.”

“The industry has now changed over the past 30 years to become a "female first" industry to where the male gender is now undergoing what you can call reverse discrimination”

“Young females who, unfortunately, will work for lower pay to "get on TV" are now being hired ahead of male meteorologists.”

“Management, especially in mid to large markets, seem to prefer an attractive female instead of a more experienced candidate.”

“Being a male has limited the opportunities for me to change jobs since the new “thing” is to hire women instead of men.”

“For example, if a station loses a female, it's almost a safe bet to know that they'll want to hire another female. It's stopped me from applying to certain jobs in the past. Instead of hiring based on experience and a strong resume, this line of work is unique in that appearance means just as much.”

“As a pretty well established broadcast meteorologist in my market, I have a pretty strong sense of security in my job. And I am likely to stay here through retirement. I keep up on continuing education, I seek out input on presentation style, I am a sought after event emcee, and I am involved in a number of local charity organizations. I am trying not to sound egotistical here, but based on the feedback I get from viewers and management, I am pretty good at what I do. Earlier in my career, despite trying maintain these same standards, I found that any position in another market that I was reasonably considered for (with at least one and sometimes 2 personal interviews) was lost to a woman always with less experience and academic credentials. I have no solid evidence that the decisions were gender based, but they were con- sistent.”

“From college I was told by educators and professionals in the field that I need to be twice as sharp (educated, knowledgeable, dressed, groomed) as my peers because everyone has a "white guy" and that employers are now looking for diversity via females and cultural and racial minorities. I had even been told that most viewers would rather look at a woman than a man, so I had that working against me.”

“As a young person, I was overlooked for an on air job years ago based on my sex. The station I was working at was going to put a former Miss Connecticut with zero meteorological experience on the air over me, a degree meteorologist with 18 months of experience and over 5 years of forecasting experience.”

“As a completely separate topic, I have no doubt there is still indeed selection bias (gender, race, etc.) in hiring in broadcasting based on an attempt by managers to make an on-air team representative of the demographics of the community. These are never outlined specifically and could well be illegal, but it happens. Not always, but often in my opinion. You'll occasionally hear through the grapevine, "They're looking for a woman," or, "They're replacing an African-American man," and know that there is no point if you're a white male for applying for that position.”

“Also, I have been passed on for jobs because a female applied. I was looked over for a job at a time when I had 3+ years experience but the station went with someone who had less than one year experience, but because she was a she, I was looked over.”

“I lost two jobs to the same woman b/c both weather departments were looking for a female.”

“Many places will seek out the hot young weather women.”

“Working on the West Coast, being a white male has harmed my career advancement chances, not improved them.”

“There are times when I have asked about a job opening and I am told by other people who know management that they want a female...so I know I have no chance of getting that job. I even applied once where I had interned and the Chief Meteorologist who was also part of company management told me that the management was looking for “The Perfect Female”...even though they had a male in there temporarily who wanted the job...he said that he wasn't going to be the permanent replacement.”

“I was passed up by a potential employer because they were looking for a female weather broadcaster. The person they hired did not have any type of meteorology degree when I did.”

Physical Appearance Attributes

To evaluate physical appearance, respondents were asked if they felt their physical appearance had impacted their career and were given the option to qualify, in a close- ended response, if the impacts were positive, negative, or both. Significantly more men

(18%) than women (only 4%) indicated that their physical appearance did NOT impact their career (�2 = 9.56, p<0.01); however, women respondents (55%) showed more uncertainty than men (41%) as to whether the career-impact of their physical appearance was mostly positive or negative (Figure 3.11). Additionally, more male respondents (9%) indicated that their physical appearance negatively impacted their career than women respondents (5%) (Figure 3.11), an interesting data point that we elaborate on in our conclusion section.

Reported Impacts of Physcial Appearance on Career

Women Men

60% 55%

41% 40% 29% 26% 18% 20% 9% 7% 4% 5% 6% 0% No Yes - both Yes - mostly Yes - mostly Unsure positively and negatively positively negatively

Figure 3.11: Respondent perception of how their physical appearance has impacted their career, broken into gender and impact effect (positive, negative, both, and unsure)

Respondents then had the opportunity to provide what they perceive as important traits in their own words first, before evaluating a pre-set list of physical trait attributes prompted by us, as the survey authors. From open-ended responses, several physical attributes emerged and were compiled into thematic groups (Figure 3.12 and 3.13) for comparison between women versus men respondents (Table 3.9). Unsurprisingly, three traits previously found to be associated with “weather girls” portrayed in films — namely weight, clothing, and hair — were also three of the most frequently referenced physical

80 traits in the open-ended question. Two of these traits — clothing and weight — were mentioned by significantly more women weathercasters (33% and 35%, respectively) than by men weathercasters (5% and 13%), indicating a gender-based double-standard associated with the perceived impacts of these traits on women in the field. These traits are further explored in additional follow-up questions outlined and discussed in later sec- tions.

Commonly Referenced Physical Appearance Traits

39 41 40 31 30 21 20 15 15 10

Number of Coded References Age or "I'm Hair/Bald Clothing Weight "I'm Youth Average" Attractive"

Figure 3.12: Physical appearance traits that are commonly referenced by both women and men weathercasters. Organized by frequency-observed within open-ended responses.

Commonly Referenced Physical Appearance Traits by Gender Women Men

40% 33% 35% 27% 30% 23% 20% 13% 15% 12% 13% 9%10% 10% 4% 5% Appearence Job Impacts

Percentage of Respondents 0% Answering "Yes" to Physical Age or I'm Average Hair/Bald Clothing Weight I'm Youth Attractive

Figure 3.13: Women’s versus men’s perceived need to change their hair color and clothing style, in order to further their career in broadcast meteorology

TABLE 3.9: Compiled from open-ended question, the percentage of women and men respondents that stated physical appearance impacted their career and used language associated with the impacts of physical appearance on career, along with chi-square values between women and men populations and associated significance p-values. Bolded �2 values are statistically significant.

Physical Attributes Referenced Women Men �2 p-value Age or Youth 4% 15% 5.8265 <0.05 “I'm Average” 9% 10% 0.0605 not significant Hair/Bald 12% 13% 0.0415 not significant Clothing 33% 5% 21.4228 <0.01 Weight 35% 13% 10.0174 <0.01 “I'm Attractive” 27% 23% 0.3445 not significant Other References Related to Physical Appearance Importance to Management and/or Viewers 23% 32% 1.3879 not significant Viewers Comment on It (Neutral) 53% 12% 31.0513 <0.01 Subject of Many Inappropriate, Threatening, or Creepy Messages from Viewers (Negative) 14% 1% 9.1289 <0.01

Another commonly referenced physical trait, Age/Youth, was mentioned by signifi-

cantly more men (15%) than women (4%), while generalized statements by men and

women weathercasters about their own average or attractive looks differed but not signif-

icantly. Finally, several generalizable statements were found to be common amongst

women and men respondents, including the perceived importance of physical appearance

to management and/or viewers, and specification on the different types of common

viewer comments related to physical appearance and received by weathercasters. While

both women and men indicated that physical appearance was important to management

and viewers, significantly more women than men reported receiving both neutral com-

ments (53%) and inappropriate, threatening, or creepy messages (14%) from viewers re-

lated to their physical appearance (versus 12% and 1% of men). While many women

82 generalized these comments, especially the negative ones, some of the most disturbing accounts reported by women included sexualized name-calling (i.e. “from calling me a slut to a whore” and “hot”), critiques on their clothing choices (i.e. “would you please find some proper attire”), and even dangerous encounters that required additional safety precautions. For example, one woman stated:

I had stalkers come to the station to find me because they were infatuated with my body and because they were perverts. This got so bad that I took a class in gun safety, pursued a conceal and carry license, and now carry a gun. Another woman relayed a similar experience working as a broadcast meteorologist:

I’ve had one incident that required law enforcement to become involved. The har- assing communications I receive from men does sometimes discourage me from moving forward out of fear for my safety.

Our study shows the transition between viewer harassment of women weathercasters into becoming a very real physical threat, and that this occurs more frequently for women weathercasters than men in the field, warranting additional measures taken by station management to increase the safety of women meteorologists. This finding aligns with similar findings in the more general broadcast journalism field (Finneman, Thomas, and

Jenkins, 2019; Lewis, Zamith, and Coddington, 2020; Miller and Lewis, 2020), affirming the importance of considering gender-based harassment when forming and revising station-based hiring, personnel, and harassment policies.

In addition to these open-ended responses, we also surveyed for specific physical appearance attributes associated with the “weather girl” stereotype, including the following: hair style (color and cut), clothing/wardrobe, weight, and race/ethnicity. It should be noted that for questions related to race/ethnicity, we only asked respondents who identified as non-white. Additionally, we asked two closed questions on whether or not

83 respondents had ever received an email about their appearance or clothing from either a viewer or colleague/manager and analyzed these results by gender. Results for each of the previous outlined questions are found in Figures 3.14 – 3.17, and all tests of significance can be found in Table 3.10.

Reported Need to Change Physical Attributes to Further Career

Women Men 74% 75%

58%

50%

33%

25% 21% Percentage of Respondents 0% Hair Color Change Clothing Style Change

Figure 3.14: Women’s versus men’s perceived need to change their hair color and clothing style, in order to further their career in broadcast meteorology

Reported Need to Change Weight to Further Career Women Men

75% 67% 58%

50% 41% 29%

25%

Percentage of Respondents 4% 1% 0% No Yes - to lose weight Yes - to gain weight

Figure 3.15: Women’s versus men’s perceived need to change weight in order to further their career in broadcast meteorology

Participants who have Received an Email, Message, or Comment on their Physical Appearance and/or Clothing Style

Women Men 99% 100% 90% 80% 80% 66% 70% 60% 50% 42% 40% 30% 20% 10% 0% From a viewer From broadcast colleague and/or station manager

Figure 3.16: Women’s versus men’s receipt of an email, message, or comment on their physical appearance and/or clothing style, from viewers (left) and broadcast colleagues/station managers (right)

Reported Impacts of Race/Ethnicity on Career

Women Men 100% 90%

75% 57% 50% 29% 25% 10% 14%

Percentage of Respondents of Percentage 0% 0% 0% 0% Yes - both Yes - mostly Yes - mostly No positively and negatively positively negatively

Figure 3.17: Respondent perception of how their race/ethnicity has impacted their career, broken into gender and impact effect (positive, negative, both, and not at all). Due to small sample size, the authors calculate chi-square but do not attempt to draw meaningful conclusions from this dataset. (women: N=10; men: N=7)

TABLE 3.10: Compiled from categorical questions, the percentage of women and men respondents that used language associated with the impacts of physical appearance on career, along with chi-square values between women and men populations and associated significance p-values. Bolded �2 values are statistically significant.

Felt need to change or has im- 2 or Women Men � p-value pact on career? Fisher’s* No 4% 18% 9.5609 <0.01 Yes – Both Positive and Nega- 55% 41% 3.764 <0.1 Physical tive Appear- Yes – Mostly Negative 5% 9% 1.2968 not significant ance Yes – Mostly Positive 29% 26% 0.2678 not significant Unsure 7% 6% 0.0849 not significant Hair Change 58% 21% 26.2345 <0.01 (Hatched Cells = Out of Required by Station 57% 5% 16.6218 <0.01 “Yes” Group)

Personal Choice 6% 14% 1.25 not significant

Mentioned Any Style Change 59% 48% 0.7968 not significant Curlier 6% 0% 0.5488* not significant Specific Straight 12% 0% 0.1684* not significant Style Shorter Change 37% 10% 5.3333 <0.05 Longer 2% 14% 4.0909 <0.05 Mentioned Any Color Change 35% 5% 6.8946 <0.01 Specific Color Blonde or Lighter 16% 0% 0.0949* <0.1 Change Brown or Darker 6% 5% 0.0505 not significant No Gray 2% 29% 11.4966 <0.01 Clothing 74% 33% 31.1162 <0.01 No 29% 58% 15.1805 <0.01 Weight Yes – Lose Weight 67% 41% 12.5243 <0.01 Yes – Gain Weight 4% 1% 1.3896 not significant Received Com- ments on From Viewer 99% 80% 16.1782 <0.01 Physical Appear- ance

Hair (Style and Color)

In their review of pop media, Perryman and Theiss (2014) found that hair style and color were two physical traits commonly utilized to overtly sexualize the “weather girls” portrayed in films. Additionally, in the current study, two respondents (one man and one woman) listed “blonde” — implying hair color — in their description of a stereotypical

“weather girl,” while several women (12%) and men (13%) referenced their hair (or the lack thereof) in an open-ended response about how they perceived specific physical attributes to have impacted their career (Figure 3.12). These hair references are anecdotal but interesting, especially when framed against the backdrop of the longstanding and well-researched “dumb blonde” stereotype (Morosini, 2020). Similar to the “weather girl” stereotype, the “dumb blonde” stigma incorporates elements of sexuality, objectifi- cation, and pitting “beauty vs. brains” while reducing women to a single characteristic: their hair color (i.e. “a blonde,” a “brunette”) (Barnes, 2005; Weir and Fine-Davis, 1989).

While our goal is not to separate out different attributes and impacts of each stereotype, or even compare/contrast these stereotypes, we did want to determine if women weathercasters felt additional pressure from the “weather girl” stereotype to fit a certain “look.”

To address this question, our survey specifically asked respondents if they’d ever felt the need to change either hair color or clothing style/type to further their career. Results of a chi-squared test revealed that significantly (�2 = 26.2, p<0.01) more women — over half of the women who participated in the survey (58%) — reported feeling compelled to change their hair color and/or style in order to further their career, than reported by their male colleagues (only 21% of all men) (Figure 3.14).

When responses were analyzed specifically for references to haircut or style, 59% of women and 48% of men reported feeling the need to change their look, although the difference was not statistically significant. We also grouped commonly reported hair styles and cuts into four categories: shorter, longer, straighter, and curlier/more volume. While women were the only ones to mention the need for straighter (12% of women) and curlier

(6% of women) styles, more men mentioned the need to grow their hair out longer (2% women; 14% men; �2 = 4.09, p<0.05) while, the change most-frequently cited by women

AND the largest difference reported between genders, was cutting hair shorter (37% of women; 10% of men; �2 = 5.33, p<0.05). These findings align with recent research by

Finneman and Jenkins (2018), which evaluated gender-based appearance standards in broadcast journalism and cited a station “style guide” from 2016, in which “young reporters are encouraged to wear medium-length haircuts with a slight curl at the bottom but are told not to curl it too much or ‘it looks TOO fancy’ (original emphasis)” (482). It’s no surprise, then, that women from our study reported the “above the shoulders” hair length requirement as well.

In addition to style changes, women are also statistically more likely than men to report feeling the need to change their hair color (�2 = 6.89, p<0.01), with blonde/lighter being the most mentioned color change found in the qualitative analysis. While both women and men also mentioned the need to prevent or mitigate gray hair, 29% of men and only 2% of women mentioned gray hair color in their responses (�2 = 11.5, p<0.01).

This could be due to the age demographics (younger women than men) represented in our sample population.

Of the women who stated they felt the need to change their hair style to further their career, over half (57%) indicated that management required them to make this change, versus only 5% of men respondents, a statistically significant difference between men and women (�2 = 16.6, p<0.01). Similarly, only 6% of women stated their color or style change was driven by personal choice, versus 14% of men, and while this difference was not found to be statistically different, this finding indicates further the unequal appearance standards required of women versus men, while also showing that management and other station leaders perpetuate this gender-based inequity in the broadcast meteorology field.

Clothing Style and Weight

In their description of the “weather girl” stereotype, three different women respondents stated that “weather girls” dress “less professionally than a meteorologist,” describing their fashion sense as “skimpy” and “short and tight.” Additionally, clothing and weight were two of the top three attributes referenced by women when describing how physical appearance impacts career (Figure 3.13). It comes as no surprise, then, that when respondents were asked if they felt compelled to change their clothing style in order to further their career, a chi-square test revealed that nearly three-quarters of women respondents (74%) confirmed, a number significantly greater than the portion of men

(33%) who felt the need to change their wardrobe (Figure 3.14). When respondents were asked if they felt compelled to change their weight (with differentiation options of gain- ing weight or losing weight) in order to further their career, a chi-square test revealed that significantly more women (71%) more likely to report pressure to change their weight than men (42%), regardless of directional change (ie. gain or loss); however, the majority

89 of this change was recorded as a need to lose weight (67% of women; 41% of men) (Fig- ure 3.15).

Email Responses from Viewers and Colleagues/Managers

Results from our question to participants about whether or not they’ve received an email from viewers or broadcast colleagues/managers reflected findings from the open- ended question on physical appearance, in that while a large number of women (99%)

AND men (80%) both reported receiving emails from viewers, significantly more women than men received emails on their physical appearance from both viewers (�2 =16.1782; p=<0.01) as well as from broadcast colleagues/managers (66% versus 42% of men; �2

=10.5196; p=<0.01). Again, this gender differential implies that women are held to significantly different physical appearance standards than men, many of which our study has shown are also connected to the “weather girl” stereotype.

Analysis of Race/Ethnicity

Although we had few Black, Latinx, or other racial/ethnic minority participants represented in our dataset, we still observed a few interesting insights related to ethnicity and felt it was important to include these in our analysis, especially since race/ethnicity is an understudied topic in the field of meteorology, and what scant research exists continues to show that diverse racial/ethnic groups continue to be underrepresented in the broadcast meteorology field (Hallows, 2020) and, even more broadly within all Geoscience fields

(Goldberg, 2019).

First, we posed questions related to how race and/or ethnicity impacted the careers of non-white participants, in order to analyze the “weather girl” findings through a more

90 intersectional lens. Our results are compiled in Figure 3.17. As previously mentioned, only 11% of our respondents self-identified as Black, Hispanic/Latinx, or biracial; there were no Asian-American, Native American, or Indigenous respondents to our survey.

This 11% was composed mostly of women (65%), with Latinas being the largest sub- group; equal numbers of Black women, Black men, and Hispanic men; and a smaller number of both biracial women and men.

When participants were asked if they felt their race/ethnicity had impacted their career, 100% of women and 71% of men reported impacts, with women experiencing more mixed to negative impacts related to race/ethnicity versus men, 29% of which reported no impacts and 14% even reporting positive impacts. Because the total number of respondents within this group was under 20, we decided against running a chi-square test, which is sensitive to small datasets; however, the observation that more Black, Latina, and biracial women experience negative effects from race/ethnicity than men further speaks to the compounded inequities women face in the broadcast meteorology field. When asked to elaborate on these race-based impacts, several respondents mentioned positives like being a role model and representation within their communities, as well as the hiring preferences towards more diverse job candidates (similar language to that found in the previous gender-based analysis). However, several respondents mentioned also experiencing both implicit and overt racism from viewers (e.g., “…one viewer who for a year would call our department and harass everyone because of the “awful” job we did. He would almost exclusively refer to me as “colored boy…”), as well as from management (e.g., “I had a boss at my first job who always questioned if English was my first language and didn't like the accent I had…” and “… the negative experiences come from viewers assuming I

91 am not American, telling me to go back where I came from and not respecting my professional opinion”), indicating that weathercaster race/ethnicity — in addition to gender — is a compounding factor and leads to additional targeted harassment from viewers.

Finally, one particularly memorable statement made by a Black woman weathercaster in response to the question of whether or not the “weather girl” stereotype had real impacts for women broadcast meteorologists stood apart from the others:

No, mainly because as a African American broadcast met I feel as if I have a little bit more to worry about than whether or not someone calls me a ‘weather girl’ it doesn't hurt my feelings like it hurts my non women of color colleagues. This statement seems to suggest that Black women don’t fully identify with the “dumb blonde” image evoked by the “weather girl” stereotype, which –while positive in prevent- ing the internalization of the “weather girl” stigma — might also lead Black and Hispanic women weathercasters to feel like outsiders in their own profession. Future research is needed to determine how racial and gender identities intersect to create unique impacts for diverse women weathercasters.

3.5 Summary and Conclusions

The purpose of our study is to better understand the real-world impacts of the

“weather girl” stereotype, how this stereotype is viewed by both men and women weathercasters, and whether or not this stereotype holds any real-world impacts for women in the broadcast meteorology field. From our survey, we found that women are significantly more likely to experience negative effects related to their physical appearance and gender identity. The majority of women weathercasters also indicated that the “weather girl” stereotype affects many aspects of their actual careers, including how viewers and colleagues perceive and respond to their job skills and physical appearance.

Stereotype Definition vs. Real-World Impacts

While it’s unsurprising that women weathercasters face actual structural sexism from, not only the structural sexism in our culture and society that suggest women are less intelligent, authoritative, credible, and trustworthy than men (Rainear, 2019), but also from similar assumptions rooted in the “weather girl” stereotype, it IS, however, surprising that in our study, men were more likely to state that (a) the “weather girl” stereotype doesn’t exist anymore or holds no negative connotation (when, clearly, this study proves otherwise); and (b) that their own gender and physical appearance has impacted their career, but neglect to provide the evidence to back up these claims (while women provide multiple examples of their career being negatively impacted by their gender and physical appearance). It’s almost as if — similar to racism — these gender-based experiences go unnoticed by the group that is less impacted, until efforts are made to correct these gender-based discrepancies in the field of broadcast meteorology. Regarding the race/ethnicity gap in the weathercasting field, far more research needs to be conducted in order to better determine how men in the field perpetuate the “weather girl” stereotype and act as gatekeepers into broadcast meteorology.

It’s not enough to simply “hire more women;” stations must work to standardize their appearance requirements of women and men weathercasters, including those related to hair and wardrobe. In a recent study, Finneman and Jenkins (2018) found “no progress in reducing discourse critical of broadcasters’ appearance in… 20 years” (479). While station managers can’t control negative comments from viewers about broadcast meteorologists, they can control — and change — their own gender-based appearance standards

93 in order to foster a more inclusive work environment for their employees. In summary, we echo the words of Finneman and Jenkins (2019):

“Television is a business that relies on viewers; however, ignoring sexist comments or saying “thank you” may continue a vicious cycle that clearly has psy- chological effects on some employees. News stations could create strategies for addressing sexist social media comments that are not top-down policies but encourage input from employees without fear of retribution. By supporting new rou- tines and expectations, news organizations can perhaps create a working environment in which success is determined by work rather than gender and appearance.” (492) (our emphasis)

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Chapter 4: “Weather Girls” and Whiteness: A Qualitative Survey Analysis Nyssa Perryman Rayne a, Dr. Paul F. Starrs a, and Dr. Sandra Rayne b a Department of Geography University of Nevada, Reno, 1664 N. Virginia Street, Reno, NV, 89557-0154 b Southeast Regional Climate Center University of North Carolina at Chapel Hill Chapel Hill, NC 27599-3220

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4.1 Introduction and Background

Over 42 years ago, June Bacon-Bercey — a record-shattering, trailblazing Black woman in atmospheric science — authored an article in the Bulletin of the Meteorological Soci- ety that stressed the need for more demographic data and research on the status and presence of Black men and women scientists working in atmospheric science fields (Slotnik,

2020, Figure 4.1).

Figure 4.1: A photo of June Bacon-Bercey in her position as station meteorologist in the 1970s. Reproduced from Slotnik, 2020.

An advocate for underrepresented populations in meteorology, Bacon-Bercey (1928–

2019) calculated the amount of time it would take to reach racial parity for Black scientists in the field, as compared to the general population and based on college enrollment and workforce demographics, to be on the order of 87 years (Bacon-Bercey, 1978, p.

579).

102

Now, at the end of 2020, we’re roughly halfway through her proposed timeline, yet we still have only a few, outdated demographic datasets and academic research studies focused on Black scientists working in the atmospheric sciences. Worse yet, many of these studies suggest that the number of Black meteorologists — regardless of career sec- tor — remains roughly only 8–10% of the field’s population (Burt, 2015; Hallows, 2020), indicating the presence of a large racial gap; however, these studies are, at best, estimates since so few studies have focused on this racial/ethnicity-based discrepancy. Addition- ally, these studies neglect to account for the intersectional aspects of diverse identities.

For example, Black, Latina, Asian, Indigenous, and other diverse ethnic/racial groups of women all experience both the racial/ethnic discrimination AND gender barriers that continue to persist in atmospheric science fields, and therefore need additional support and research-based interventions to succeed against these odds.

Recent exploratory, survey-based research found that Black women meteorologists may hold a contrasting perspective of the “weather girl” stereotype than held by white women and men (this dissertation, Chapter 3). In particular, one Black woman from our previous survey-based study of weathercasters, responding to the question of whether or not the “weather girl” label had impacted their career, stated the following:

…as an African American broadcast met[eorologist] I feel as if I have a little bit more to worry about than whether or not someone calls me a “weather girl,” it doesn’t hurt my feelings like it hurts my non women of color colleagues, (survey participant, quoted in Chapter 3)

Rather than viewing this gender-based stereotype as a barrier to success in the broadcast meteorology field — as many white women have — limited evidence suggests that Black women might be more likely to disregard the “weather girl” characterization and consider

103 that stereotype as a way-down-the-list barrier compared to other obstacles in their career trajectory. This study seeks to amplify the voices of more Black and Latina women, in order to better understand their career experiences in the field of broadcast meteorology as well as their perception of the “weather girl” stereotype.

Other research findings related to the topic of race/ethnicity in meteorology are limited by either the lack of race/ethnicity focus (Cranford, 2018) or by the small number of Black women represented (Hallows, 2020), making it difficult to draw any conclusions about the perspectives of Black women weathercasters, specifically. This small, survey- based case study seeks to initiate amplifying the diverse voices and experiences of Black and Latina women in the broadcast meteorology field, while answering the following research questions:

• Do Black and Latina women broadcast meteorologists perceive the “weather

girl” stereotype in a negative, positive, or neutral light? How does their view

compare/contrast with the perspective of women weathercasters from other

race/ethnicities?

• Does the “weather girl” stereotype, as visualized by women weathercasters,

have a perceivable race/ethnicity? If so, what is that race/ethnicity?

• Are there career-impact differences for women from different race/ethnicity

backgrounds due to the negative “weather girl” stigma?

104

• How do women weathercasters view racism in the broadcast meteorology field,

and are their perceived impacts from racism related to the race/ethnicity they

identify with?

Before outlining our study, we provide a brief overview of several concepts and theories pertaining to several metrics we explore in our survey, including beauty standards, ideals, and physical appearance traits (like weight and hairstyle), and how these uniquely intersect with race/ethnicity and gender. Additionally, we review a few important theory- based considerations pertaining to our methodology.

Cultural Differences in Perception and Embodiment of Beauty

While perceived “beauty” as a concept is variable and individualized, culturally in our society, women are subconsciously pushed to pursue more rigorous beauty ideals than men (Ramati-Ziber et al., 2019). However, research has also shown that these gender-based beauty standards differ based on race/ethnicity, often pitting women of all racial/ethnic backgrounds against each other by idealizing white beauty over any other skin color.

In our society, whiteness is especially valued over Blackness, evidenced in the following statement by Cox (2020):

As a minority, Black people are inundated with information about the majority…, are not given a choice to turn off the constant ringing in our ears that is White America…, [and] have to learn about their [white] version of history, their version of living, and even their version of culture, despite being in it. (p. 76)

And because the dominant white culture most values “white femininity (the most noted type of physical beauty)” (Shackelford, 2019, p. 13), Black women are continuously measured against an impossible metric, resulting in a “… deep history of Black women

105 and femmes being compared to the purity, beauty, and humanity of white women”

(Shackelford, 2019, p. 12).

In addition to facing these restrictive white-oriented definitions of beauty, Black women must also contend with several different harmful stereotypes perpetuated by popular media (Zimdars, 2019). For example, historical (and even some current) depictions of American Black women often perpetuate the “mammy” trope (Okoro, 2019; Shackel- ford, 2019; Zimdars, 2019), a “physically large, desexualized and nurturing figure”

(Okoro, 2019); and when compounded with societal racism, sexism, and fatphobia, leads to the further de-sexualization of Black women (Okoro, 2019), best explained by

Shackelford (2019):

The rich history of the Deep South and the violence around troping, codifying, and oppressing Black women and femmes is centered on mammification, sexual violence excused through hypersexual mythologies, denial of beauty, animalizing our humanity, and utilizing our bodies as literal and symbolic vessels for the con- tinuation of slavery and subordination. (10)

Due in part to the overblown features of the “mammy” caricature, in addition to white-culture’s inherent fatphobia, body size/weight is another trait used by white culture to demonize and desexualize Black women, as, to quote Shackelford (2019), “Blackness

+ fatness denies us beauty proximity through the constructions of whiteness…” (13). Fur- ther, white women often target Black women in their fat-shaming, in order to deflect similar negative attention from themselves, while negating Black sexuality and thus reducing their own perceived sexual competition (Hobson, 2019). Hobson (2019) further explains how and why white women use fat-shaming to disparage Black women, describing the origin of the common “Becky” white girl caricature:

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‘Becky’ as a moniker for white women stems from rapper Sir Mix-a-Lot’s infa- mous Baby Got Back music video (1992), in which two white women are shown at the start of the video (one who is called “Becky”) making disparaging remarks about the size of a black woman’s behind. Their fat-shaming comments betray their innate fear of a black female sexuality that might render their own sexuality as inauthentic and insufficient, given the racial expectations surrounding white women’s supposed racial and sexual purity. (33)

Despite this weaponization of fatness by white women to restrict Black women from achieving white “ideals” of beauty, the “mammy” figure stereotype’s incorporation of both large body size (negative) in addition to more positive, gender-based stereotypical traits of comfort and caregiving via motherhood, allows for potentially a broader, more complex interpretation of fatness for Black women. For example, Cox (2020) describes the diverse, positive representation of bodies exhibited by the women who raised her:

I grew up in a matriarchal household. My gram (who was really my grandaunt) was a G! Gram had stepped in as “Mom” to fill the role with my mother and her siblings after her sister passed away unexpectedly. I looked up to her for her strength and ability to handle business…. My gram at one point was also fat (smaller fat). Her daughter, my aunt, had been fat (mid- to superfat) as long as I could remember. Then there was me. Under one roof, three generations of fat people resided. I had someone to look up to, and these people would also understand my needs. I had a vision before me that showcased what success looked like in a body like mine… The way I saw it, if I could learn how to balance the personalities of my gram and my aunt, I’d be the perfect person. The size of my belly or hips simply did not matter in this version of the world they had crafted… I also lived with my mother, two sisters, and cousin. They were slender in size. I thought body diversity was the norm . . . everywhere. (3-4)

This example is given not to argue that fatness wasn’t perceived as a negative element to

Cox — on the contrary, she provides many specific examples of how being labeled fat negatively shaped and impacted her life — but is referenced to suggest that this complex relationship between fatness and Blackness should be kept in mind when analyzing Black women weathercaster descriptions of a stereotypical “weather girl” — a trope found previously to be significantly associated with body size and weight (Chapter 3). Do Black

107 women meteorologists focus as much on the negative aspects of weight/body size associated with “weather girls,” as much —and in the same way — as white women weathercasters? This is one of the research questions our study seeks to address.

Another physical trait associated with the “weather girl” stereotype that differs based on race/ethnicity and thus could have implications in our survey of Black women weathercasters is hair style, including the cut, length, and color of hair. Over the last dec- ade, Black women in broadcast journalism, including the meteorology field, have brought to light multiple instances of racist comments from viewers after wearing a natural hair style, including complaints about their hair being “unprofessional” (Payne, 2018), with one weathercaster reporting that she’d even been fired for speaking out against a racist comment associated with her hairstyle (Shepherd, 2018). However, due to the nationwide trend of working from home this past year in response to the COVID-19 pandemic, women in broadcasting have been more in control of their on-air “look” and consequently have increased wearing their hair naturally (Gillespie, 2020). Coupled with newly-passed anti-discrimination laws, like the Crown Act, which restrict employers from banning specific hair styles and textures (a ban often used to specifically target Black hair styles), more Black women in broadcasting have shared their experiences of past racist encounters with viewers and management alike, tied to their natural hair and, consequently, have developed the social media tag #NaturalHairOnAir to raise awareness of this issue (Gil- lespie, 2020). The connections among Black hair, identity, and racism have also been outlined in theoretical discussions, including a discussion of Beyoncé’s artistic album,

Lemonade, in which “‘Becky with the good hair’ symbolizes the Other Woman, the

White Woman as both historical and present-day nemesis for black women,” where

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“good hair” is “a vernacular term in black communities used to describe hair that is long and straight” (Hobson, 2019). This “long and straight” definition of white femininity is the antithesis of natural Black hair, and further illustrates that “hair is integral to identity, agency, and a more complicated racial consciousness” for Black women (Hobson, 2019), best illustrated in the recent statement of one Black woman broadcast journalist, who noted in regards to the #NaturalHairOnAir movement, “I’m so happy to be a part of an industry-wide shift challenging and refusing ‘beauty norms’ that stem from white su- premacy” (Gillespie, 2020).

Additionally descriptions of beautiful white women’s hair as “long and straight” is an interesting observation when also considering the previous finding (Chapter 3) that a significant number of weathercaster women reported being told to shorten their hair by station management to further their career. This contradicting advice that goes against typical feminine beauty could thus further indicate that femininity is less valued than masculine features in the broadcast meteorology field (perhaps in efforts to pass women off as more masculine and thus “serious”?)

Our previous research found that significantly more women than men weathercasters reported feeling the need to change their hair style or color, and that this directive to change their hair came explicitly from station management (Chapter 3). Although only three Black women weathercasters responded to the previous study, all three of these women reported feeling the need to change their hair color/style, with one participant stating, “I'm an African American female, and I don’t wear my natural hair because it’s not as acceptable.” This recurring negative messaging — that Black women’s natural hair is unprofessional and inferior to white women’s hair styles — has real negative impacts

109 for Black women’s confidence and self-esteem, and potentially shapes their perspective of the “weather girl” stereotype, an interaction we hope to better understand through this research.

Finally, to add even more complexity to our research, we note that some have ar- gued that Hispanic /Latina women weathercasters are often the targets of “machismo,” defined as the pervasive Spanish-based “culture that expects – even demands – the sexualization of women, but then turns around and shames these very women for being sexy, rather than pointing fingers at the patriarchal conditions that create this system” (Morse,

2016). This is most evident in the pervasive sexualization of “hot weather girl” ranked- lists online that are actively refreshed annually. However, this complicating argument was not leveraged in the past survey study of broadcast meteorologists. While we at- tempted to further study the perspectives of Latina weathercasters, due to our low response rate from this group of women, we suggest this topic as one for future researchers to explore.

Taking all of these ideas into consideration, it follows then that Black women, white women, and Latina weathercasters might each hold a unique view of the stereotypical “weather girl” stereotype — but, if these perspectives do prove to be different, how significantly different are these opinions? Additionally, which aspects of the “weather girl” stereotype are viewed differently by women from different race/ethnicity backgrounds (and why these traits)? These are two main questions our study seeks to answer.

Ongoing Anti-racism Social Justice Movements in the US

To contextualize our research further, the recently publicized deaths of Black men and women at the hands of police have fueled massive nationwide protests, many

110 organized by the Black Lives Matter movement. These protests have further led to discussions on social media about the role and importance of Black voices in a variety of traditionally-white spaces, including academia as a whole (#BlackInTheIvory) and in academic fields with the least diverse perspectives, like the geosciences and meteorology

(#BlackInGeosciences). But how do women in broadcast meteorology view these movements? Are they seen as a driver that will spur further changes within the meteorology field or as simply performative gestures undertaken prior to the field backsliding to the status quo?

In response to these questions, we conducted a survey that focuses on the experiences of women weathercasters from all racial backgrounds, in order to fill in the literature gap and offer a more complete representation of women working in the broadcast meteorology field.

Research Purpose

This work, based on survey data, seeks a better understanding of how an intersection — and at times, a veritable collision — of gender and racial/ethnicity-based identities impacts the lives, professional realities, and the perspectives of women working in the field of broadcast meteorology, and – further – how Black and Hispanic women interpret both the pervasive “weather girl” stereotype and ongoing Black Lives Matter movement as applying to themselves (or not).

While this work on weather broadcasters focuses on physical attributes including hair, weight, skin color, it follows on a larger national realization that women have for too long, and in too many settings, been marginalized — and often excluded altogether from receiving credit for their accomplishments and careers — or else hidden in

111 science/STEM roles. While sadly remarkably common across the last 70 years or so, current media culture can in some circumstances be considered “awakened.” The contributions of Black women are known now, for example, to be crucial in handling mathemati- cal calculations for early NASA efforts in the Mercury, Gemini, and Apollo space programs. Their work is prominent in recent books, articles, and films, including 2016’s

Hidden Figures, directed by Theodore Melfi, which focuses on Katherine Johnson and other Black women who, in the early 1960s, handled much of the theoretical mathematics of the developing space program, when that effort — nearly at a panic — was infused with Cold War urgency. Margot Lee Shetterly’s 2016 book, with the same lead title, was subtitled “The American Dream and the Untold Story of the Black Women Mathemati- cians Who Helped Win the Space Race.” If participation in television weather broadcasting may at first glance not seem so momentous as sending men to orbit and space and eventually the moon, in fact women weathercasters today are hugely more in evidence than the Black women working for NASA, who went all but unknown for nearly sixty years, now. Geographer-author Dava Sobel runs the clock back farther still in her 2016 book The Glass Universe, about the women (generally white) who were a crucial force at the Harvard Observatory from the 1880s to the 1950s, handling the mathematics and observations and glass plates and documentation that created modern-day astrophysics (Orf,

2016).

As geographer and cartographic historian Mark Monmonier notes in his 1999 book Air Apparent, by far the greatest exposure Americans have to maps and cartographic science comes through the daily on-screen presentations of television (cable or broadcast) meteorology. Add in the crucial role that weathercasters are assigned when an

112 unpredictable severe or potentially cataclysmic weather or earth-science event arrives

(hurricanes, tornadoes, typhoons, atmospheric rivers, prolonged drought, earthquakes and floods) and the significance and prominence of competent weathercasters becomes ines- capable fact. For Black women and Latinas — and no doubt in some markets, Native

American, Asian, or Pacific-Islander women as well — to be excluded is invidious and entirely inappropriate, considering how substantive their contributions have been to physical science fields. A question that this research cannot answer definitively, or at least not now, is whether “bad weather news” is attended to more closely when the person delivering it somehow matches the “complexion” of the television viewer. A question to be asked in future studies, then.

4.2 Methodology

The purpose of this survey is to focus on the experiences and perspectives of

Black and Latina women broadcast meteorologists; however, as outlined in the literature review, Black and Latina women make up only an estimated 5–10% of the total current broadcast meteorology population (Hallows, 2020). To further complicate our research efforts, there exists, to date, no comprehensive demographic database of broadcast meteorologists by market, and, thus, studies incorporating this population have had to compile their own database, based on individual broadcast station website information, which more often than not provides no details pertaining to a weathercaster’s race/ethnicity. If this information has been collected, it would likely be done by one of the meteorological academic organizations; however, if this database exists, none of the atmospheric science groups have made this data available for research purposes. The closest comprehensive list available of American broadcast meteorologists is provided by the American

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Meteorological Society in the form of weathercasters who have successfully been creden- tialed with the Seal of Approval, more recently renamed as the Certification of Broadcast

Meteorologists program; however, this list provides only the names of these weathercasters. If organizational efforts to diversify the field of atmospheric science are to be successful, a comprehensive survey of broadcast meteorology demographics needs to be compiled, even in summarized form to protect the privacy of this group.

One important, yet nuanced, assumption our study makes is the separation of racial identity from racial appearance, particularly as these relate to external bias and discrimination. Recent research suggests that “racial phenotypicality,” or the “within-category variation of racial appearance,” is an important attribute to consider in studies that evaluate outsider perception and judgement of racial attributes (Maddox and Perry, 2018) because, as Maddox and Perry (2018) state:

“Individuals whose facial characteristics are more stereotypical of their racial group experience greater discrimination and receive less favorable outcomes across a variety of domains. Thus, without considering racial phenotypicality, policies designed to address racial disparities may fail to acknowledge outcomes associated with this subtle but important element of social perception and judgment.” (57)

Additionally, older research also suggests that the perception and self-reporting of one’s own racial phenotypicality may differ from observer reports, and that “people’s self-reported skin tone may reflect a bias” (Coard, Breland, & Raskin, 2001, referenced in Mad- dox and Perry, 2018, p. 62), but that the appropriate incorporation of racial phenotypicality should be limited to studies that evaluate “outcomes in contexts involving face-to-face interaction or visual information (photographs or video)” (Maddox and Perry, 2018, p.

62). While this study does not attempt to make a comparison between racial identity and

114 physical appearance, nor the form(s) of bias and discrimination that result from either attribute, this study does attempt to evaluate the experiences (including discrimination) stemming from the physical appearance of particular Black women weathercasters, in a field that further amplifies and places value on physical appearance. Based on this logic, our study sought out women that presented (to an external observer) as a Black woman, in order to survey, for this initial case study, those individuals facing the greatest race- based discrimination. In following this logic, we most likely overlooked women whom identify as Black or African American; however, our goal was not to compile an exhaus- tive survey based on gender identity, but rather to amplify a few of the often-neglected voices of Black women weathercasters.

In response to this limited survey population, and in order to maximize our participant survey pool, a similar database collection methodology was used in this study, using station website biographies and photos. Black and Latina women were visually identified via two separate researcher observations, in addition to consulting race/ethnicity identifying information often included in station biographies (eg. references to Black and

Hispanic professional organization membership or outright self-descriptions of their race/ethnicity). While admittedly this judgmental sampling method relies on observer assumptions and is prone to a myriad of biases, efforts were made to reduce biases by first vetting the final list of potential respondents with several Black and Latina women weathercasters. Additionally, after the potential survey respondents were identified, respondents were then asked to self-report their own race/ethnicity in the survey itself. That said, our methodology techniques could be interpreted as a racist extension of the “white colonial gaze,” (Paris, 2019), in that the white authors evaluated and categorized race-

115 based attributes of Black and Latina women in a way that evokes the very racist ideals this study seeks to call out. Despite these shortcomings, we felt that this research was too important not to add our findings to the academic discourse within the broadcast meteorology field; however, we encourage future research on this topic to use alternative, more accurate, less biased methods—either through surveying all weathercasters; using a different sampling strategy; or acquiring a vetted list of broadcast meteorologist demographic data (as discussed in the paragraph above)—to ensure that no voices are sup- pressed or invalidated, even inadvertently.

For this study, the contact information for all Black and Latina women broadcast meteorologists was compiled from station websites in the top (1–50), middle (51–100), and part of the lower (100–140) Nielsen Designated Media Market areas, a longstanding database that is updated annually and is based on regional populations. Because the majority of markets lower than 140 shared broadcasts with larger market syndicates, and therefore had no unique broadcast meteorologists working at these stations, we limited our contact information collection to markets that ranked higher than 140.

For markets in which either a Black woman or Latina weathercaster (or both) was identified, the contact information for one randomly selected white woman weathercaster working in this same market was also collected, for comparison purposes. For markets with more than one Black woman or Latina weathercaster present, one of these weathercasters was randomly selected to be surveyed, while information for all other Black and

Latina women were banked into a running list of potential survey respondents to draw from for markets missing all three demographics (Black, Latina, and white women). We used these methods to both incorporate perspectives from weathercasters in a variety of

116 market sizes and regions, while also accounting for other geographical and associated cultural variables that could impact participant’s responses and complicate our findings.

Ultimately, however, because the survey data was generalized by region and market size for anonymity, we are unable to say with certainty that comparisons between Black/La- tina and white weathercasters are limited to exactly the same market; rather, we made sure similar populations were surveyed by restricting our survey recipients to these bounds. We were able to group respondents by similar (rather than exact) geographical regions and market sizes for comparison purposes.

Over the course of a one-month period (July 2020), we assembled a roster with an equal number of Black women, Latina, and white women weathercasters. After reviewing station websites for the top 140 markets, we collected the contact information for a total of 68 Latina weathercasters and 50 Black women weathercasters, in addition to a corresponding number of white women weathercasters, working in 63 different Nielsen markets. To standardize the number of respondents in each demographic, we surveyed the maximum number of Black women identified (50 total) and standardized the other two race/ethnicity groups based on this number, surveying 50 Latina women and white women, resulting in a total of 150 potential respondents.

We crafted several survey questions as extensions of those used in Rayne et al.

(2020) (see Table 4.1 for full list of survey questions, and Appendix D for full survey including all provided answer options). Prior to participant solicitation, all survey documents were all submitted to the UNR Institutional Review Board ([1114547-1] Demo- graphic and Experiential Survey of Broadcast Meteorologists) for review as a Social/Be- havioral exempt status. Because broadcast meteorologists are considered public figures,

117 with contact information available to the general public, the study was approved to be

Exempt (Category 2), with additional exempt status extended for follow-up surveys of the same population.

TABLE 4.1: Survey instrument, reworked and extended from previous research on weathercaster perceptions of the “weather girl” stereotype, as outlined in Rayne et al. (2020). Survey Question(s) 1. What gender do you identify as?

2. What is your age?

3. What size television market do you work in? (nationwide, top/1-50, middle/51-100, lower/101+)

4. In what US Region is your television market located? (Northeast, South, Midwest, West)

5. Which race/ethnicity best describes you? Please select all that apply. (American In- dian or Alaskan Native, Asian / Pacific Islander, White / Caucasian, Black or Afri- can American, Hispanic / Latinx, or Other (please specify))

6. When you visualize and describe a stereotypical "weather girl," what physical characteristics does she have? In other words, what does a typical "weather girl" look like?

7. Which personal characteristic do you think most impacts long-term career success of women in broadcast meteorology? (gender, race/ethnicity, physical appearance, education/experience)

8. In your opinion, women from which of the following racial/ethnic backgrounds face the MOST race/ethnicity-based discrimination, specifically in the field of broadcast meteorology? (American Indian or Alaskan Native, Asian / Pacific Is- lander, White / Caucasian, Black or African American, Hispanic / Latinx, or Other (please specify))

9. Do you think the Black Lives Matter movement has or will impact your career, and in what way? (no impact, unsure, yes-positive, yes-negative, yes- but unsure if positive or negative)

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Email was the primary means of distributing the survey, and efforts were made to find individual station email contacts for all participants. However, due to the small number in each population group, when potential survey candidate email addresses were not provided on their station website, we used the messaging features of social media platforms, such as Instagram, Facebook, and Twitter, to share the survey with respondents

(but only those that had public, station-affiliated profiles on these platforms). In total,

73% of candidates were sent an email link, with the other 28% sent a link via social media. An anonymous URL link to our Qualtrics survey was sent out to this finalized respondent list, and the survey remained open for a one-month period (from September to

October 2020). Two reminder emails/messages were also sent at the halfway point of the survey period. A summary and discussion of our survey results are given in the next section.

Theoretical Considerations, Study Limitations, and Future Research Goals

Because the primary researchers in this study have backgrounds in meteorology, but no direct experience working in the broadcast meteorology field—in addition to each holding an individual set of experience-based lenses and biases through which the data were interpreted— several theories commonly referenced in social science research were employed in the interpretation of open-ended comment-based responses. For example, the researcher used subjective interpretation to generate knowledge; however, while “bias informed the identification and framing of the pattern in the data, the interpretation was, at the same time, grounded in the data and deliberately developed through processes of constant comparison” (Walther, Sochacka, and Kellam, 2013).

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Because our study focused on an intersectional population that represents two minorities in the field of atmospheric science — specifically, diverse race/ethnicities and women — our study was therefore limited in possible survey respondents, and further so in the small number of participants that completed the survey. Although efforts were made during analyses to account for this small sample size, our findings should be interpreted with consideration of this limitation, while future research is needed to verify our results. To improve results, future studies similar to this one can allow for a longer survey period, more sustained efforts to contact participants, broader and more inclusive survey techniques, and in-person interviews to gain a more nuanced perspective of individual experiences of Black and Latina women weathercasters.

4.3 Results and Discussion

4.3.1 Demographics of survey respondents

Out of the 150 respondents solicited, 27 weathercasters responded, a response rate of 18% for all women and the following rates for corresponding race/ethnicity groups:

24% for Black women; 22% for white women; and 6% for Latinas. Not all survey participants completed all questions; however, due to the small sample size, we decided to keep and implement all answers, but have only incorporated the total number of respondents per question in our analyses and we include exact respondent amounts in each graph.

Demographically, our survey population was evenly distributed between white

(41%) and Black/African American (44%) race/ethnicity groups, with 11% Latina respondents and 4% identifying as biracial/Latina/Asian-Pacific Islander (Figure 4.2). The average respondent age was 33 years old, with over three-quarters (81%) of respondents under the age of 40 (Figure 4.3). For market location of respondents, the same categories

120 found in Rayne et al. (2020) were used: South, Northeast, Midwest, and West (see Simp- son, 2020). Geographically, most respondents (44%) came from Southern markets, followed by the West (32%) and Northeast (20%) regions (Figure 4.4). Only one participant reported working in the Midwest and one reported working Nationwide. When considering race/ethnicity differences by region, we found an equal distribution of white and

Black women weathercasters in all regional groups. Surprisingly, all Latina weathercasters reported working in the Northeastern region rather than in regions with higher

Latinx/Hispanic populations such as the South or West.

Respondent Race/Ethnicity Biracial 4%

White / Caucasian 41% Black /African American 44%

Hispanic / Latina 11% n=27

Figure 4.2: Reported race/ethnicity of respondents. (n=27)

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Summary of Respondent Ages 30% 27% 25% 23% 19% 20% 15% 12% 12% Respondents Percentage of 10% 4% 4% 5% 0% 20-24 25-29 30-34 35-39 40-44 45-49 50+

Figure 4.3: Summary of respondent ages (n=26)

Respondents by Geographical Market Region 50% 44% 40% 32% 30% 20% 20%

Percentage of Respondents 10% 4% 0% Northeast Midwest South West

Figure 4.4: Summary of respondent market geographical regions (n=25)

Due to the overall small respondent sample size, we were unable to definitively associate regionality to respondent answers; however, it should be noted that in a study of regional weathercaster gender and racial representation, the Midwest market reviewed by

Hallows (2020) had one of the largest gender gaps, tied only with Florida for more men than women represented. Additionally, Hallows (2020) reported the largest number of

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Latinx/Hispanic respondents in the New York market, a result similar to our findings. Fu- ture research should further evaluate the impacts that geography, and associated cultural differences, have on regional hiring practices in the broadcast meteorology field.

The market size of respondents was skewed towards larger markets, with over half (59%) of respondents working in top markets (1–50), roughly a third (33%) working in middle markets (50–100), with the smallest number working in nationwide and smallest markets (101+) (4% each) (Figure 4.5). When considering race/ethnicity of respondents versus market size (Figure 4.6), we found greater diversity in top markets, indicative of more diverse populations found in the major cities that these markets represent. Addi- tionally, more white weathercasters reported working in top markets, while more Black weathercasters work in middle and lower markets.

Total Respondents by Market Size

59% 60% 50%

40% 33% 30% 20%

10% 4% 4% Percent of Respondents 0% Nationwide Top (1-50) Middle (51-100) Lower (101+)

Figure 4.5: Summary of employment market size as reported by respondents.

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Race/Ethnicity of Respondents by Market Size and Respondent Race/Ethnicity 100%

80%

60%

40%

Race/Ethnicity 20%

Percentage of Respondents by Nationwide Top (1-50) Middle (51-100) Lower (101+) Biracial (n=1) Black / African American (n=12) Hispanic / Latina (n=3) White / Caucasian (n=11)

Figure 4.6: Summary of respondent race/ethnicity by employment market size (n=27)

4.3.2 Black Women Perspectives of the “Weather Girl” Stereotype

Again, because only 3 Latina weathercasters responded to our survey, we limited our primary focus to analyzing the perspectives of Black women weathercaster. To first gain an overall sense of how Black women view and interpret the “weather girl” stereotype, participants responded to an open-ended question asking them to characterize the physical appearance and traits of the “weather girl.” Open-ended text answers were then the- matically coded by the author in a similar method to that used in Chapter 3, using both a priori and in vivo coding techniques for themes previously established in the previous, similar survey question and themes that emerged from responses in this study as well.

As expected, the most commonly-referenced physical attribute that Black women associated with the “weather girl” stereotype was beauty/sex appeal, indicating that women, regardless of race/ethnicity consistently associate these traits with the label. The second most commonly-used reference to the “weather girl” as described by Black women

124 weathercasters was a neutral definition equitable to “a woman broadcast meteorologist.”

This response was also commonly given by men respondents in our previous survey, and pointed to a similar respondent disassociation with the “weather girl” label. Other commonly mentioned “weather girl” traits include references to hair, ethnicity (ie white), clothing, weight, and age/youth.

Regarding “weather girl” race/ethnicity, all responses by Black women weathercasters either directly or indirectly characterized “weather girls” as white. For example, two Black women explicitly mentioned race/ethnicity, stating that the “weather girl”

“…is thin and fit. Not too curvy. She is usually white. Blonde is a plus. She doesn't have glasses and looks picture perfect,” while another respondent said, “When I visualize a stereotypical "weather girl," I think of a young and pretty white woman in a form-fitting dress.” Two other Black women weathercasters described white attributes associated with the “weather girl” stereotype in their answers, as one woman said, “as horrible as this sounds but I think of someone who is highly attractive, blonde with blue eyes” and another woman described the “weather girl” as “like a Barbie doll. Blonde hair, blue eyes, large breast and wearing tight fitting low-cut dresses.” One additional interesting observation is that three out of the four Black women participants who associated whiteness with the “weather girl” were also the only three Black respondents that reported working in Southern markets, with all other Black women participants hailing from the Pacific

Northwest, the Southwest, or the Mid-Atlantic regions. It should be noted that this observation is based on three data points, and thus any connections based on this relationship are tenuous at best; however, future research should determine if geographical attributes,

125 such as the underlying demographics of regional populations, play a role in shaping the perspectives of women weathercasters working in these specific regions.

Of the Black women who characterized the “weather girl” with neutral, definition- based characteristics, several also emphasized that, in the words of one respondent, “a weather girl comes in all shapes, ethnicities and sizes,” signifying that — instead of dis- associating themselves with this stereotype — some women view the label of “weather girl” as representing a more diverse array of women, including themselves, almost to the point of identifying with this non-negative version of the stereotype.

4.3.3 Comparing Perceptions of the “Weather Girl” Stereotype

To determine if Black and Latina women weathercasters hold significantly different views on the “weather girl” stereotype than white women weathercasters, we developed survey questions similar to those implemented in Rayne et al. (2020), specifically those questions pertaining to physical appearance aspects of the “weather girl” stereotype. For comparison purposes, the original survey questions from our Chapter 3 study are found in

Table 3.1. To determine if Black and Latina women identify with the physical attributes associated with “weather girls,” we first asked respondents to describe their own visualization of a stereotypical “weather girl” in an open-ended narrative answer format. These open-ended responses were then manually coded into thematic categories using NVivo software platform. While codes were loosely based on the “weather girl” attributes found in the portrayal of “weather girls” in popular media (Perryman and Theiss, 2014) and previous research (Chapter 3), we further adapted coding to traits that emerged during the data coding process, which created a few additional categories based on our findings. The full list of codes found in over 20% of respondent narratives, along with a brief

126 explanation for each, is provided in Table 4.2. Additionally, the traits mentioned by the highest percentage of all respondents are shown in Figure 4.7.

TABLE 4.2: List of frequently-mentioned physical appearance traits that emerged from narrative responses on the “weather girl” stereotype and their associated coding information

Code Category Description

Beauty and Sex Appeal Includes references to any aspect of beauty or sexuality

Hair Color, length, style, or texture of hair

Clothing Any reference to clothing.

Weight Any reference to weight, body size, or eating habits. Any statement taking the term “weather girl” at face-value, suggesting the Neutral Connotation term to mean only “woman broadcast meteorologist” with no other connotations Any reference to age (primarily descriptions of young or youth as associ- Age or Young ated with “girl”) Any direct mention of race/ethnicity (“white woman”) or implied associa- Race/Ethnicity tion with white physical features (“blonde hair, blue eyes”) Any direct or implied reference to intelligence (or lack thereof), including Intelligence education, behaviors (“airhead”), or field-based career experience.

Total Number of Coded References for Most Frequently Mentioned "Weather Girl" Stereotype Traits 74% 75%

50% 37% 33% 33% 30% 25% 22% 22% Percentage of Respondents 0% Beauty or Hair Clothing Weight Neutral Age or Ethnicity Sex Appeal Connotation Young

Figure 4.7: Most commonly-referenced thematic traits –by percentage of respondents who used each term to describe a stereotypical “weather girl”

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The most commonly-mentioned physical characteristic of a stereotypical “weather girl” among all participants was a reference to beauty/sex appeal, mentioned in roughly three-quarters (74%) of all narrative responses to this survey question. This finding aligns with previous research, in which sex appeal was the second most commonly-referenced attribute of the “weather girl” stereotype, cited by 58% of men and 62% of women weathercasters –and second only to education/experience, an attribute not related to physical appearance and thus not an expected finding the current study.

Other top-referenced traits by women weathercasters in the current study include mentions of hair, clothing, weight, and age/youth — all traits which were also previously found to be associated with the “weather girl” stereotype by weathercasters (Chapter 3).

Two other coding categories that emerged in a third of respondent narratives were the use of a generalized broadcast meteorologist definition –with a neutral connotation — to describe a stereotypical “weather girl” and the characterization of a “weather girl” as a white woman — either through an explicit reference to ethnicity or implied via other common features of white people (“blonde hair” and “blue eyes”). Finally, a few additional traits emerged from survey response narratives and were coded for, but because these traits were in less than 20% of responses, equating to 5 respondents or (in most cases) fewer, we did not include them in our codebook or analysis but describe them briefly here. These additional “weather girl” traits included descriptions of a “beauty or pageant queen”; references to their lack of intelligence, makeup, chest size, eye color, gender, height, or facial accessories (“does NOT wear glasses”); and even one expression of self-identification with the term “weather girl.” While these traits are interesting, and many related to traits found in previous research on the “weather girl” stereotype, due to

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our small sample size, we felt it was not useful to attempt running a statistical analysis

comparing individual responses for these traits. However, future research could use these

traits to inform additional survey studies within a larger population of similar respond-

ents. Next, we compared respondent race/ethnicity with each coded response in order to

determine the proportion of Black women, Latinas, and white women that referenced

each of the coded categories and, due to the small population size, we conducted both a

chi-square and Fisher’s exact test (used for small populations, like that represented in our

study) for all comparisons, in order to determine whether differences in usage amongst

respondent race/ethnicity were significant. It should be noted that only a Fisher’s test was

used for those comparisons that included a value of zero, in order to fulfill conditions of

the chi-square test. Consequently, because only 3 Latina weathercasters responded to the

survey, many comparisons between Latina and white women weathercasters could only

be evaluated with the Fisher’s test, and since none of the analyses revealed any signifi-

cant relationships between white and Latina weathercasters, these analyses are not

Total Number of Coded References by "Weather Girl" Stereotype Trait and Respondent Race/Ethnicity 10 9 9

8 6 6 6 5 4 4 4 4 3 3 2 2 2 2 2 2 1 1 1 1 1

0 Total Number of Coded References Beauty or Hair Clothing Weight Neutral Age or Ethnicity Sex Appeal Connotation Youth Biracial (n=1) Black/African American (n=12) Hispanic/Latina (n=3) white/caucasian (n=11)

Figure 4.8: Total number of coded references to common “weather girl” attribute categories, as relayed by survey respondents according to respondent race/ethnicity

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included here. Figure 4.8 shows the coded categories broken down into number of men-

tions by respondent race/ethnicity, and the statistical test results for reference compari-

sons between Black and white women weathercasters are found in Table 4.3.

TABLE 4.3: Percentage respondents by race/ethnicity that used language associated with coded categories, along with chi-square values between Black and white populations and associated significance p-values. Bolded �2 and Fisher’s values are statistically significant.

Black white Fisher’s Narrative Category women women �2 exact p-value (n=12) (n=11) test Beauty 75% 82% 0.1568 1 not significant Hair 33% 46% 0.354 0.6802 not significant Clothing 25% 27% 0.0154 1 not significant Weight 17% 55% 3.6301 0.0894 <0.1 Neutral Definition 50% 9% 4.5365 0.0686 <0.05 Age/Young 17% 36% 1.1548 0.3707 not significant Ethnicity 33% 18% 0.6833 1 not significant

Out of the top seven coded categories, only two were alluded to a significantly dif-

ferent number of times by Black women versus white women weathercasters, namely

weight and the use of a neutral definition to describe the stereotypical “weather girl.”

While 55% of white women meteorologists mentioned body size or weight in their de-

scription of the “weather girl” stereotype, including references like “slim” and “fit,” only

17% of Black women used these descriptors, a significant difference between respondent

groups. One possible explanation for this difference in description could be related to the

broader yet more nuanced view of weight that exists for Black women, as outlined in the

background literature section above. An alternate rationale for this difference in view-

points could lie in the disassociation between Black women and the “weather girl” stereo-

type, in that Black women do not view themselves as “weather girls.”

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This disassociation could also explain the second significant difference in responses to this survey question, as 50% of Black respondents provided a “neutral” definition of a genderless broadcast meteorologist in their description of the “weather girl,” while only

15% of white women included non-negative, definition-based descriptions. This difference is strikingly similar to that found in our past study of women versus men weathercasters, in which a significantly larger number of men (28%) used a similarly neutral meteorologist definition to describe the “weather girl” stereotype, versus only 7% of women

(Chapter 3).

While the frequency of use for all other coded categories did not differ significantly between Black and white women weathercasters, the explicit mention of ethnicity by over 33% of Black women (versus only 18% of white women) is an interesting and potentially telling sign that the “weather girl” stereotype is embodied by a white woman. Of those who referenced ethnicity in their description, half explicitly mentioned the color

“white” and the other half mentioned other traits that are characteristic of a white person, namely blonde hair and blue eyes. This finding suggesting that at least a subset of Black women do not perceive themselves as, nor identify with, the “weather girl” stereotype, and thus express a less negative view of the stereotype; however, this disconnect may also undercut their feeling of belonging in the atmospheric science field.

4.3.4 “Weather Girls” and Black Lives Matter: Perceived Career Impacts for Di-

verse Women Broadcast Meteorologists

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To determine if (and how) the “weather girl” stereotype has had any differential im-

pacts on the careers of white, Black, and Latina women surveyed in our study, partici-

pants were first asked to select the trait they felt had most impacted their broadcast mete-

orology career from the following set of personal characteristics: gender, education,

physical appearance, and race/ethnicity (Figure 4.9). The majority of all respondents

(68%) reported that their physical appearance had the greatest impacts on their careers,

followed by education/experience (16%), and all other categories equally selected (8%)

after these.

Most Career-Impacting Personal Trait as Perceived by Respondents by 10 Race/Ethnicity 8 8 7

4 2 2 2 1 1 1 1 1 1

Number of Respondents 0 gender education/experience physical appearance race/ethnicity Biracial (n=1) Black / African American (n=11) Hispanic / Latinx (n=3) White / Caucasian (n=10)

When evaluating these responses through the lens of respondent race/ethnicity, no

significant differences were found among the groups; however, we note an interesting

finding that race/ethnicity was not selected as the most important trait for Black or Latina

women, even when offered as a choice, indicating that the intersection of physical

132 characteristics associated with both gender AND race/ethnicity have important impacts on the careers of women in broadcast meteorology than simply race/ethnicity alone.

Next, a set of questions related to the Black Lives Matter (BLM) social justice movement were asked. Respondents were first asked if they felt the BLM movement would have an impact on their career, and whether that impact would be positive, negative, neutral, or unknown. Participants indicated a large degree of uncertainty in their answers, as over a quarter (28%) of all respondents were unsure whether or not BLM would impact their careers, while almost another quarter (20%) of respondents indicated that while there would be impacts, they were unsure about whether those impacts would be positive or negative (Figure 4.10). 24% of respondents felt there would be no impact from the movement on their careers; however, 20% felt the BLM movement would lead to positive career impacts and only 8% (2 participants) suggesting their career could be negatively impacted by the movement.

Will the Black Lives Matter Movement Impact Your Career? 30% 28% 24% 20% 20% 20%

10% 8%

0% Yes - but unsure Yes - positively Yes - negatively Maybe/Unsure No impact if impact will be (explain) (explain) Percentage of Respondents positive or negative (explain) Figure 4.10: Percentages of respondents indicating their perception of future impacts to their career due to the Black Lives Matter social justice movement.(n=26)

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In order to view nuances associated with group race/ethnicity identity, we also analyzed these same responses by respondent race/ethnicity (Figure 4.11). The only significant statistical finding was that more white participants (50%) indicated no perceived future impacts from BLM on their careers versus Black and Latina respondents (Fisher’s statistic = 0.0527; p<0.1), with another 30% of white respondents indicating possible but uncertain impacts, suggesting that white women broadcast meteorologists view themselves as outside of or separate from the BLM movement. Alternatively, over half (63%) of Black women weathercasters indicated some change, with most (36%) indicating a positive impact from the BLM movement, although these results were not statistically significant.

Perceived Future Impact of Black Lives Matter Movement on Respondent Career, by Percentage of Respondents by Race/Ethnicity 100% 100%

75% 67% 50% 50% 36% 36% 33% 30% 25% 18% 10% 10% 9% Percent of Respondents 0% Yes - but unsure if Yes - positively Yes - negatively Maybe/Unsure No impact impact will be (explain) (explain) positive or negative (explain) Biracial (n=1) Black or African American (n=11) Hispanic / Latinx (n=3) White / Caucasian (n=10)

Figure 4.11: Percentages of respondents, by race/ethnicity, indicating their perception of future impacts to their career due to the Black Lives Matter social justice movement. (n=25)

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Respondents who felt there would be future career impacts due to the BLM movement were also given the opportunity to explain their choice via textbox, and these narrative explanations were then analyzed for common themes. Of participants indicating a positive future impact from the BLM movement on their careers, 60% mentioned both the increase in field and workplace diversity as well as increased opportunities for work colleagues to listen and learn about racism. Explanations for uncertainty of career effect

(positive versus negative) included a Latina weathercaster, who questioned whether the movement would last long enough to effect actual change, while a Black woman weathercaster mentioned the increased ability and pressure to speak out against racism as both a potentially positive and negative impact. Finally, of the two respondents perceiving negative impacts from the BLM movement, a Black woman weathercaster indicated the potential for some viewers to “feel attacked” by the movement and consequentially lash out at Black broadcasters, while a Latina weathercaster expressed concern about how potential future hiring practices would change to favor Black weathercasters over other minorities, increasing job competition amongst women of color. The final comment echoes similar sentiments expressed by male weathercasters in our previous study, as further elaborated in our Discussion section.

Finally, to better gauge this inner-group competition, we asked respondents to select, from a list of race/ethnicity categories, the group they perceived to face the most discrimination in the field of broadcast meteorology; race/ethnicity groups given as options include the following: American Indian/Alaskan Native, Asian/Pacific Islander,

Black/African American, Hispanic/Latinx, white, and Other, with an optional textbox.

Over half (67%) of respondents indicated that Black/African Americans faced the

135 greatest discrimination in the broadcast meteorology field, followed by Asian/Pacific Is- landers (13%) and Hispanic/Latinx (8%) (Figure 4.12)

Race/Ethnicity of Women Most Discriminated in the Broadcast Meteorology Field 75% 67%

50%

25% 13% 8% 4% 4% 4% 0% American Indian Asian / Pacific Black / African Hispanic / White / Unsure / Alaskan Native Islander American Latinx Caucasian Percentage of Respondents

Figure 4.12: Percentages of respondents indicating the race/ethnicity group they perceive as facing the most discrimination in the field of broadcast meteorology. (n=24)

When this question was analyzed by respondent race/ethnicity (Figure 4.13), we found white responses to be more widely distributed among the race/ethnicity groups.

The only statistical finding from this dataset was that according to a chi-squared test (� =

3.8095; p < 0.1), Black women and Latinas were significantly more likely than white women to report Black/African American weathercasters as experiencing the greatest discrimination in the field, although this significance did not show up in the Fisher’s exact test (0.1409). However, the general consensus of all respondents — that Black broadcast meteorologists experience the most discrimination in their field — is important, in that if offers an internal perspective for station management to consider when determin- ing and implementing measures that best support diverse employees.

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Perceived Race/Ethnicity Experiencing Most Discrimination in the Field, by Percentage of Respondent Race/Ethnicity 100% 100% 90%

80%

60% 50%

40% 33% 33% 33% 20% 20% 10% 10% 10% 10% Race/Ethnicity Identity Identity Race/Ethnicity

0% Percentage of Respondents by Their Their by Respondents of Percentage American Indian Asian / Pacific Black / African Hispanic / Latinx White / Unsure / Alaskan Native Islander American Caucasian Biracial (n=1) Black or African American (n=10) Hispanic / Latinx (n=3) white / caucasian (n=10) Figure 4.13: Percentages of respondents, by race/ethnicity, indicating their perception of the race/ethnicity group facing the greatest discrimination in the field of broadcast meteorology. (n=24)

4.4 Summary and Conclusions

The purpose of this survey was to extend research on how the “weather girl” ste-

reotype — a negative label that is often used to degrade women weathercasters (Chapter

3) — is perceived and impacts Black and Latina women broadcast meteorologists specifi-

cally, in order to determine if these impacts are similar or different than those experi-

enced by white women broadcast meteorologists. We also wanted to evaluate how

women weathercasters perceive race/ethnicity and racism, including how these issues im-

pact their careers. We surveyed nearly 30 women weathercasters, half of which were

Black women and half white women. Because only 3 Latina weathercasters responded to

our survey, we weren’t able to draw meaningful conclusions from such a small dataset;

however, we included this data in our analysis, as several narrative responses yielded im-

portant insights when compared with Black and white participant answers.

Our study found that, for the most-commonly mentioned traits, Black and Latina

women weathercasters referenced the same physical attributes when describing the

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“weather girl” stereotype — such as beauty/sex appeal, hair, and clothing — as white women weathercasters in both this study and in similar past studies (Chapter 3). That said, white women referenced weight and/or body size when describing the “weather girl” stereotype — using modifiers that align with traditionally white beauty standards

(i.e., thin, skinny, fit) — significantly more often than Black or Latina women, while

Black women were significantly more likely to use a neutral definition of a broadcast meteorologist to describe a “weather girl,” similar to that used by men weathercasters in a previous study (Chapter 3). These findings combined indicate that Black women view the

“weather girl” stereotype as external to and separate from their own identity as a broadcast meteorologist, and thus do not readily identify with this stereotype, as much as their white women colleagues do. This disassociation potentially stems from the finding that the “weather girl” stereotype is most often visualized as a white woman, as illustrated in many narrative response references to blonde hair color and blue eyes. While disassociation from this negative stereotype could benefit Black women weathercasters — allowing them to form an identity separate from the older sexist stigmas of the past — the white

“weather girl” visualization also speaks to the race/ethnicity gap in the field, as the majority of broadcast meteorologists (men and women) are white and could ultimately lead to fewer Black women pursuing the field in response to this lack of visual representation.

As an aside, the practice of distancing oneself from the “other” group is a common thematic element in this study and past research (Chapter 3), between the attitudes of male weathercasters in our previous survey study and responses of certain women weathercasters in this current study. A prime example of this distancing is illustrated in the words of a Latina weathercaster in the current study who expressed concern over a

138 potential change in hiring practices that would benefit Black weathercasters while reducing opportunities for “other” minority groups (i.e., Latinx, Asian, Native American). This comment is similar to many others expressed by men weathercasters about diversity hiring practices that favor what they perceive to be “less qualified” women over men. In response to these perceived competitions among broadcast meteorologists, station management should adopt greater efforts to make hiring practices more transparent for employees, while fostering an open dialogue about the career impacts of racism, sexism, and other social inequities and encouraging especially white staff to actively advocate for a more equitable newsroom for all (Baron, 2020).

Finally, 67% of all survey respondents, and 50% of white women weathercasters, said that Black/African American broadcast meteorologists experience the most field- based discrimination; however, only 20% of white women broadcast meteorologists identified potential career impacts due to the ongoing Black Lives Matter movement. This disconnect between recognizing racism in the broadcast meteorology field, yet interpreting this racism as external to their own lives, is jarring. In contrast, more than 60% of

Black women not only recognized potential career impacts from this movement, but also viewed these impacts as an opportunity to initiate conversations about racism with their colleagues. It should be noted, however, that Black women have historically been bur- dened with the largely unpaid labor of organizing and leading diversity initiatives that educate — and ultimately end up primarily benefitting — white people (Baron, 2020; Chan- cellor, 2019; Jean and Feagin, 1998; Klugman, 2020; Ray, 2020; St. Jean, 1997; Times

Higher Education, 2020). Thus, station management should take the initiative in institut- ing both an internal support system for Black and Latina women weathercasters, as well

139 as educational initiatives that center the lived experiences of Black women, Latinas, and other intersectional identities, but that also target white employees, training them to recognize social injustices like racism or sexism and actively intervene (Baron, 2020). Baron

(2020) effectively summarizes this responsibility of station leadership in the following statement:

…addressing intersectionality starts from the top. CEOs and senior executives need to acknowledge their unconscious bias, force themselves to see where disparities have previously been invisible to them, and transparently work towards the creation of an inclusive workspace so that they are hiring, retaining, and pro- moting the variety of workers who deserve a seat at the table.

Additionally, future research on demographics related to the broadcast meteorology field need to be more inclusive of Black and Latina women, in addition to other intersectional identities. Based on data collection from our previous survey study (Chapter 3) and this study, we calculate that out of the roughly 2,100 broadcast meteorologists, 50 are Black women, making up roughly 2% of the total weathercaster population. Compared with

June Bacon-Bercey’s 1978 estimate of an 11% Black weathercaster population that would be needed in order to achieve racial parity, and assuming gender parity equates to

50% (WHO, 2020), we would expect roughly 6% of the weathercaster population to be composed of Black women. Instead, as of 2020, the current number of Black women weathercasters is closer to 2% of the total population, a 200% difference and underrepre- sentation. Our field won’t become more diverse on its own — we have to take active steps to foster an environment where anyone who loves weather can access the career of their dreams, rather than only a select few.

140

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Chapter 5: Summary and Conclusions

Through analysis of popular media and two survey studies, our research shows that the “weather girl” term is multi-faceted in both use and interpretation. While popular media depictions of the overly sexy, stupid, blonde “weather girl” are both driven by, and aid in the further propagation of, the negative attributes that stem from the term’s origin, these stigmas transfer into the real, everyday lives of women in broadcast meteorology.

First, our media review study found that out of all films portraying a woman broadcast meteorologist, 67% of films showed these women as both lacking the meteorological knowledge and/or educational background necessary to succeed as a weathercaster, while doubling-down on women’s perceived inaptitude by having them depend on men to complete basic tasks related to their job. Additionally, 83% of films inaccurately portrayed job tasks as easier than they actually are (i.e., weathercasters reading from tele- prompters), and 100% of the films portrayed these women as overtly sexualized. These findings confirm our hypothesis that popular media is, in part, responsible for the cultural persistence of this antiquated stereotype as well as its propagation in time and space.

In response to these findings, we surveyed weathercasters about how they perceive the “weather girl” stereotype, with participants indicating that women broadcast meteorologists receive significantly more harassment about both their physical features and scientific knowledge than their male counterparts. This confirms our hypothesis and aligns with findings from Rainear (2019) which found that audience perception of weathercaster trustworthiness was not a factor of meteorologist education but, instead, was based on gender, with a sexist partiality for having men deliver their weather.

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Finally, our follow-up survey of Black and Latina versus white women weathercasters indicate that Black women do not relate as much to the “weather girl” stereotype, in part because this stereotype is perceived as being white. While this white embodiment is not surprising, given the race/ethnicity gap that persists in the broadcast meteorology field, the overall response from white women recognizes that Black weathercasters are the most discriminated-against in the field. Unacknowledged in their answers were any perceived future impacts to their own careers. That they see little recourse or utility in ongoing 2020 social justice movements to rectify this discrimination is disheartening, and something with roots that should be further explored in future research.

Many insights regarding social science research and survey-based studies of broadcast meteorology were gained from this project. Future research can benefit from the following methodology consideration illuminated through the process, including the following:

• A greater focus on in vivo coding methods, especially when analyzing qualita-

tive responses from Black and Latina women

• Broader attempts to survey the entire broadcast meteorologist community, ra-

ther than a subset, in order to gain more generalizable results

• More focused studies based on anonymous, interview-based correspondence

with Black and Latina women weathercasters

• An evaluation of how the cultural concept of Latinx machismo intersects with

the “weather girl” stereotype, including impacts on the careers of Latina

weathercasters

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One key takeaway from our research is that academic organizations associated with the atmospheric science field must compile an accessible list of demographic information that characterizes all weathercasters, rather than the white, male majority. Without this information, women will be viewed not as the important arbiters of weather, climate, and other science communication that they are, but instead, as just another beautiful, but stupid, “weather girl.”

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APPENDIX A: Perryman, N., & Theiss, S. (2014). “Weather Girls” on the Big Screen: Stereotypes, Sex Appeal, and Science, Bulletin of the American Meteorologi- cal Society, 95(3), 347-356. Retrieved Dec 2, 2020, from https://journals.ametsoc.org/view/journals/bams/95/3/bams-d-12-00079.1.xml

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APPENDIX B: 2018: Year of the (Weather?) Woman — Discussion of email responses to Perryman and Theiss (2014)

Originally published: Bull. Amer. Meteor. Soc. (2019) 100 (4): 544. https://journals.ametsoc.org/view/journals/bams/100/4/bams-d-18- 0315.1.xml?rskey=H6INUH&result=1#.X8faL9_2wH0.link

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APPENDIX C: Full survey used for Chapter 3 study.

Introduction and Consent

What does the term "weather girl" mean to you?

Review these important survey details, then complete the consent form below to begin!

PURPOSE

The purpose of this research is to determine what broadcast meteorologists like you think about the term "weather girl," with a focus on how this term has been used (or misused) by both weathercasters and t he general public. We also want to know if and how the "weather girl" stereotype is related to other aspects of identity, such as race/ethnicity and physical appearance.

This research is being conducted by Nyssa Rayne, a Geography doctoral candidate at the University of Nevada - Reno.

LENGTH + TOPIC

We realize how precious your time is. That’s why we made sure this survey will only take a quick 8 minutes! (Seriously, we timed it!)

The survey questions will be about your demographic background,

experiences working as a weathercaster, and your thoughts about the "weather girl" stereotype.

PROCEDURES + CONFIDENTIALITY

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We appreciate you giving us insight into your life as a broadcast meteorologist, and want you to know that the data we collect will be anonymous and used only for this research.

Your responses will be confidential and we do not collect identifying information such as your name, email address or IP address.

You may only complete the survey once, using your unique, emailed access URL link.

Once you begin the survey, you may not start over.

Your participation in this research study is voluntary. You may choose not to participate. If you decide to participate in this research survey, you may withdraw at any time.

If you decide not to participate in this study or if you withdrawl from participating at any time, you will not be penalized.

We will do our best to keep your information confidential. All data is stored in a password protected electronic format.

The results of this study will be used for scholarly purposes only and may be shared with University of Nevada-Reno representatives.

RAFFLE

Because you're helping us out with this research, we wanted to do something nice in return! Take the survey for a chance to win a $25 Visa gift card (or one of three other $5 Visa gift cards)!

The last question will direct you to a completely separate, unconnected raffle survey (which is also voluntary and confidential).

QUESTIONS?

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If you have any questions about the research study, please contact Nyssa Rayne at [email protected].

This research has been reviewed according to University of Nevada-Reno IRB procedures for research involving human subjects.

ELECTRONIC SURVEY CONSENT FORM TITLE OF STUDY: Demographic and Experiential Survey of Broadcast Meteorologists Investigators: Nyssa Rayne Paul Starrs, Ph.D. Department of Geography/0154 [email protected]

ELECTRONIC CONSENT: Please select your choice below. Clicking on the "agree" button below indicates that:

1. you have ready the above information 2. you voluntarily agree to participate 3. you are at least 18 years of age

If you do not wish to participate in the research study, please decline participation by clicking on the "disagree" button.

Do you consent to participate in this survey?

Agree Disagree

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Main Questions

What is your age?

Do you currently OR have you EVER worked as a broadcast meteorologist?

Yes, currently work as a broadcast meteorologist. Yes, previously have worked as a broadcast meteorologist, but not currently. No

What gender do you identify as?

Male Female Other (please specify)

Do you feel that your gender has impacted - either positively, negatively, or both - your career as a weathercaster?

No Yes - mostly positively Yes - mostly negatively Yes - both positively and negatively Unsure

How has your gender impacted your career and/or experiences as a weathercaster? Feel free to provide as many or as few examples as you want in order to communicate your experience!

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What size television market do you work in?

Largest (1-50) Medium (51-100) Smallest (101+)

In what US Region is your television market located?

New England Middle Atlantic South Midwest Southwest Pacific Northwest Alaska/Hawaii Nationwide Other (please specify)

What is the highest level of school you have completed or the highest degree you have received?

High School Degree / GED Some College Associates degree Bachelor's degree

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Graduate degree (M.S. or Ph.D.) Other (please specify)

Do you currently hold the AMS Seal of Approval OR are a registered Certified Broadcast Meteorologist (CBM)?

No Yes

What was your college/university major?

Do you work part-time or full-time?

Part-time Full-time Other (please specify)

Do you have any children?

Yes, one or more aged 18 or older Yes, one or more aged under 18 No

Have you ever quit your job as a weathercaster in order to support the career of a significant other OR provide care for family member(s), including children?

Yes

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No Other (please specify)

Which race/ethnicity best describes you? Please select all that apply.

White / Caucasian Hispanic / Latinx Asian / Pacific Islander Black or African American American Indian or Alaskan Native Asian / Pacific Islander Other (please specify)

Do you feel that your race/ethnicity has impacted - either positively, negatively, or both - your career as a weathercaster?

No Yes - mostly positively Yes - mostly negatively Yes - both positively and negatively Unsure

How has your race/ethnicity impacted - either positively, negatively, or both - your experience as a weathercaster? Feel free to provide as many or as few examples as you want in order to communicate your experience!

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Do/did you have a mentor (such as a(n) instructor/professor, station manager, broadcast meteorologist, etc.) whom you consulted with for help when "breaking into the business" of broadcast meteorology?

Yes No

Briefly describe the mentor (including gender, race/ethnicity and occupation) that you consider to be the most important in helping you achieve your weathercasting career goals. Do not include specific names.

Do you feel that your physical appearance has impacted your career- either positively, negatively, or both - as a broadcast meteorologist?

No Yes - mostly positively Yes - mostly negatively Yes - both positively and negatively Unsure

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How has your physical appearance impacted your career - either positively, negatively, or both - as a broadcast meteorologist? Feel free to provide as many or as few examples as you want in order to communicate your experience!

Have you ever felt the need to change your hair color and/or style in order to further your career?

Yes, please briefly explain:

Have you ever felt the need to change your weight in order to further your career?

Yes - to gain weight Yes - to lose weight No

Have you ever felt the need to change your clothing style or type in order to further your career?

Yes No

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Have you ever received an email, message, or comment (positive or negative) from a viewer (of any gender) about your physical appearance and/or clothing style?

No Yes

Please briefly describe and/or summarize the comment(s) / message(s) and your perceived gender of the commenter (man, woman, or unknown).

Have you ever received an email, message, or comment (positive or negative) from a broadcasting colleague or station manager (of any gender) about your physical appearance and/or clothing style?

No Yes

Please briefly describe and/or summarize the comment(s) and your perceived gender of the commenter (man, woman, or unknown).

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Are you familiar with the term "weather girl"?

Yes No

Briefly list any personality, educational, and/or physical traits that you associate with the term "weather girl."

In your experience, how has the term "weather girl" primarily been used by weathercasters and the general public? Select from the following choices below:

Mostly used Mostly used "Weather Girl" as Mostly used "Weather Girl" Descriptor Only "Weather Girl" Never with Positive (No Perceived with Negative Experienced / Connotations Connotations) Connotations NA

Female

Weathercasters

Male Weathercasters

Female Members of Viewing Audience/Public

Male Members of Viewing Audience/Public

Female Broadcast Journalists (other than Weathercasters)

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Male Broadcast Journalists (other than Weathercasters)

Have you ever been called or described as a "weather girl"?

No Yes

When you were labeled as a "weather girl," did it have a perceived positive or negative connotation?

Positive Negative Both Neutral / No connotation Unsure

Do you feel that the term "weather girl" and/or the traits associated with this stereotype have impacted your job and/or relationship with the viewing audience in any way (good or bad)? Please briefly explain your answer in the text box below.

Yes

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Do you see yourself still working in the broadcast meteorology field 10 years from now? Feel free to elaborate in the text box beside your response.

Yes

Maybe

Block 2

Would you like to enter the raffle for a chance to win a giftcard?

Yes No

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APPENDIX D: Full survey used for Chapter 4 study.

Introduction and Consent

What does the term "weather girl" mean to you?

Review these important survey details, then complete the consent form below to begin!

PURPOSE You may have been previously sent a survey about your experiences in the field of broadcast meteorology. After analyzing the data, we had a few follow-up questions about the "weather girl" stereotype, in addition to sexism and racism in the broadcast meteorology field. You have been identified as an important voice in the field, and we'd love to hear your thoughts on these issues!

This survey is a follow-up to the previous survey, with the primary purpose of this research being to determine what broadcast meteorologists like you think about the term "weather girl." We also want to know if and how the "weather girl" stereotype is related to other aspects of identity, such as race/ethnicity and physical appearance.

This research is being conducted by Nyssa Rayne, a Geography doctoral candidate at the University of Nevada - Reno.

LENGTH + TOPIC

We realize how precious your time is. That’s why we made sure this survey will only take a quick 2-3 minutes! (Seriously, we timed it!)

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The survey questions will be about your demographic background, experiences working as a weathercaster, and your thoughts about the "weather girl" stereotype.

PROCEDURES + CONFIDENTIALITY

We appreciate you giving us insight into your life as a broadcast meteorologist, and want you to know that the data we collect will be anonymous and used only for this research. Your responses will be confidential and we do not collect identifying information such as your name, email address or IP address. You may only complete the survey once, using your unique, emailed access URL link. Once you begin the survey, you may not start over.

Your participation in this research study is voluntary. You may choose not to participate. If you decide to participate in this research survey, you may withdraw at any time.

If you decide not to participate in this study or if you withdrawl from participating at any time, you will not be penalized.

We will do our best to keep your information confidential. All data is stored in a password protected electronic format.

The results of this study will be used for scholarly purposes only and may be shared with University of Nevada-Reno representatives.

QUESTIONS?

If you have any questions about the research study, please contact Nyssa Rayne at

[email protected].

This research has been reviewed according to University of Nevada-Reno IRB procedures for research involving human subjects.

173

ELECTRONIC CONSENT: Please select your choice below. Clicking on the "agree" button below indicates that:

1. you have ready the above information 2. you voluntarily agree to participate 3. you are at least 18 years of age

If you do not wish to participate in the research study, please decline participation by clicking on the "disagree" button.

Do you consent to participate in this survey?

Agree Disagree

Main Questions

What is your age?

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What gender do you identify as?

Male Female Other (please specify)

What size television market do you work in?

Nationwide 1 - 10 11 - 20 21 - 30 31 - 40 41 - 50 51 - 60 61 - 70 71 - 80 81 - 90 91 - 100 101+

In what US Region is your television market located?

New England Middle Atlantic South Midwest Southwest Pacific Northwest Alaska/Hawaii Nationwide

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Other (please specify)

Which race/ethnicity best describes you? Please select all that apply.

White / Caucasian Hispanic / Latinx Asian / Pacific Islander Black or African American American Indian or Alaskan Native Asian / Pacific Islander Other (please specify)

When you visualize and describe a stereotypical "weather girl," what physical characteristics does she have? In other words, what does a typical "weather girl" look like?

How have the following attributes and physical characteristics impacted your career trajectory in the field of broadcast meteorology, especially your ability to move up or down in the field?

Extremely Mostly Neutral Extremely Negatively Negatively or No Mostly Positively (Hindered (Obstacle Impact to Positively (Progressed Career) or Barrier) Career (Asset) Career)

race/ethnicity

gender

weight

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Extremely Mostly Neutral Extremely Negatively Negatively or No Mostly Positively (Hindered (Obstacle Impact to Positively (Progressed Career) or Barrier) Career (Asset) Career)

educational background

career experiences

other physical appearance or abilities (please describe)

Which personal characteristic do you think most impacts long-term career success of women in broadcast meteorology?

gender race/ethnicity physical appearance Other (please specify):

In you opinion, women from which of the following racial/ethnic backgrounds face the MOST race/ethnicity-based discrimination, specifically in the field of broadcast meteorology?

White / Caucasian Hispanic / Latinx Asian / Pacific Islander Black or African American American Indian or Alaskan Native Asian / Pacific Islander Other (please specify)

177

Do you think the Black Lives Matter movement has or will impact your career, and in what way?

Yes - positively (explain)

Yes - negatively (explain)

Yes - but unsure if impact will be positive or negative (explain)

Maybe/Unsure

No impact