THE UNIVERSITY OF CHICAGO LINGUISTIC RELATIVITY, COLLECTIVE COGNITION, AND TEAM PERFORMANCE A DISSERTATION SUBMITTED TO THE FACULTY OF THE DIVISION OF THE SOCIAL SCIENCES IN CANDIDACY FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF SOCIOLOGY BY PEDRO ACEVES CHICAGO, ILLINOIS AUGUST 2018 Copyright © 2018 by Pedro Aceves All Rights Reserved ii TABLE OF CONTENTS List of Tables ................................................................................................................................ iv List of Figures ................................................................................................................................ v Acknowledgements ...................................................................................................................... vi Abstract ....................................................................................................................................... viii Introduction ................................................................................................................................... 1 1 Text for Social Theory ............................................................................................................. 6 2 Language Information Density, Conceptual Space, and Communicative Speed ............ 49 3 Linguistic Relativity, Collective Cognition, and Team Performance................................ 57 4 Moving Forward .................................................................................................................. 106 Appendix A: Materials and methods for the estimation of language information density 117 Appendix B1: Quotes from Hawley’s Seasonal Stories regarding Ama Dablam ................ 118 Appendix B2: Mathematical Simulation of Movement Through Conceptual Space ......... 119 References .................................................................................................................................. 123 iii List of Tables Table 3.1: Descriptive Statistics .................................................................................................. 88 Table 3.2: Correlation Matrix ...................................................................................................... 89 Table 3.3: Zero-Inflated Negative Binomial Model Results ........................................................ 90 Table 3.4: Zero-Inflated Negative Binomial Model Results for Different Data Subsets ............ 93 Table 3.5: OLS Regression Results ............................................................................................. 94 Table 3.6: Zero-Inflated Negative Binomial Model Results for Interaction Effects ................... 97 iv List of Figures Figure 0.1: Appearance frequency of the terms “sociology of language” in the Goolge N-Gram Viewer ............................................................................................................................................. 2 Figure 1.1: Linguistic features for text analysis............................................................................ 15 Figure 1.2: Text analysis and social theory. ................................................................................. 19 Figure 1.3: Properties of four common semantic representations. ............................................... 23 Figure 1.4: Social Inference from Communication. ..................................................................... 28 Figure 2.1: Language information density. ................................................................................... 51 Figure 2.2: Languages plotted by information density and conceptual space density (cosine similarity). ..................................................................................................................................... 53 Figure 2.3: Languages plotted by information density and conceptual space density (coefficient of variation). .................................................................................................................................. 54 Figure 2.4: Languages plotted by information density and speech information transfer rate. ..... 55 Figure 3.1: Example of sparse and dense information density languages and the corresponding structure of the conceptual space. ................................................................................................. 68 Figure 3.2: Distribution of languages by their information density rate (not normalized). .......... 81 Figure 3.3: Predicted number of expedition member summits as a function of the language information density rate. ............................................................................................................... 92 Figure 3.4: Predicted speed to the summit (in days) as a function of the language information density rate. ................................................................................................................................. 95 Figure 3.5: Predicted number of expedition member summits as a function of the language information density rate, by level of team hierarchy .................................................................... 98 Figure 4.1: Temporal flow of the telephone experiment. ........................................................... 116 Figure B2.1: Shape of the transition probability distribution for one row at different degrees of density (top), and sample transition probability matrices at different degrees of density (bottom) ..................................................................................................................................................... 121 Figure B2.2: The average mean first passage time (in # of steps) at each density level. ........... 122 v Acknowledgements This dissertation would not have come to be without the support of some very special people. First, my parents, Pedro Aceves and Kimberly Breeden, have been an ever-flowing spring of encouragement for all the crazy ideas I have taken on over the years, and taking on a Ph.D. with a family in tow has been no exception. I am sure that my choice of a career in academia is in no small part due to my dad’s profound love and admiration for knowledge and learning in all their forms. I thank him for imbuing me with that same appreciation. I thank my mom for her ever-present encouragement and her deep wisdom. She has positively influenced every project I have undertaken and every hurdle I have had to overcome. Her intuition on the human condition is unmatched. I am also thankful to my in-laws, Steve and Terry Chambers, who have been pillars of support for our family at every stage of the doctoral program. On the academic front, my adviser James Evans played a pivotal role in my development as an academic and in the development of this dissertation. It is safe to say that this dissertation would not have developed under anybody else’s guidance. James has an uncanny ability to find interesting possibilities anywhere he looks, and that was certainly the case with this project. He immediately recognized the potential when the ideas were in their infancy and spurred me on along the way with his infectious intellectual playfulness. His breadth of interests and excitement over new ways of thinking about the world inspire me every day to cultivate that same intellectual playfulness in myself. As I leave Chicago, I realize that what I will miss most is being around James’ expansive adjacent possible. If I can cultivate my own adjacent possible to be a tenth as exciting as his, I will consider this an academic life well-lived. My committee members have also been deeply influential. John Levi Martin has been a guiding influence since my first day in the doctoral program. I am grateful for his incisiveness vi and encouragement at every step. Amanda Sharkey has been extremely generous with her time. I thank her deeply for her extensive comments and feedback on just about every paper I’ve written during the last five years. Last, I thank Sameer Srivastava for his active engagement in this dissertation, his astute advice on other projects, and his professional advice and mentorship. This committee has left an indelible imprint on how I see the world, and for this I am thankful. On the family front, I have the three most important people in my life to thank for this accomplishment. My kiddos, Nico and Isaac, patiently put up with their dad’s hectic work schedule and incessant travel between Ann Arbor and Chicago from the time they were a year- and-a-half. They gave up many weekends with me so that this dream could become a reality. To them I promise that those days are over. It is now time for me to pay back that time with interest. I also thank them for their contagious happiness. They never failed to bring me back down to reality and to refocus my attention on the important things in life. I am deeply grateful for this. Lastly, I owe this dissertation to Cassandra Aceves, the most incredible person I know. It is no exaggeration to say that without her keen insights and suggestions, this dissertation would currently be at least two years from completion. Her brilliance and ability to think theoretically have been hugely beneficial for my academic development. That she has managed to cultivate this ability and earn her own Ph.D., all while being a solo Supermom, is beyond me, and makes my accomplishment largely her own. I simply cannot articulate with words the awe I experience when I take the time to contemplate the things she has achieved, from raising our