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Replication Data for: Civic Responses to Police Violence
No full textReplication files for "Civic Responses to Police Violence
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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Essays on Diversity
No full textThis dissertation consists of three chapters. All papers focus on diversity and use a mix of econometrics and machine learning techniques.
My first chapter focuses on police discretion. Using a novel dataset from Washington D.C. that contains extensive administrative data, we estimate the degree to which individual police officers vary in their responses to calls for service. We find that officer identity accounts for approximately 10\% of the explainable variation in stop and arrest outcomes and that officers vary widely in their propensity to make a stop or arrest. We find that officer level propensity trends are persistent over time and that a one standard deviation increase in officer propensity to make a stop and arrest increases odds of stops and arrests by approximately 20-25\% in the six months following the sample period. These results are robust to a variety of specifications. Rather than officer race or gender, we find that officer rank and supervisor are the most predictive features of officer propensity to arrest or make a stop. This finding is consistent across various specifications and machine learning methods.
My second chapter focuses on machine learning and studies of racial disparities. It is well documented that individuals of different races have disparate experiences in the criminal justice system in the United States. As most studies focus on Black-white interracial differences, intraracial disparities are often overlooked. Analyzing intraracial disparities is further complicated by the fact that it has been historically difficult to accurately and consistently measure skin tone and Afrocentric features. Utilizing convolutional neural networks and photos as data, this study creates a consistent, running measure of perceived race. Using this new measure and data type, new types of analysis are possible. This study presents photographic summary statistics, shows the positive relationship between perceived race and sentence length is robust to the inclusion of various controls and, reevaluates traditional Black-white gaps, measuring both inter- and intraracial disparities. This study also evaluates how new advances in race inference methodology perform throughout the perceived race spectrum and the implications of misclassification for metrics of racial disparities.
My third chapter focuses on ideological diversity in classroom settings. Surprisingly, little is known about the impact of ideological diversity on classroom outcomes given the amount of attention paid to the role of ideological diversity on higher education outcomes such as critical thinking and academic performance, scant causal evidence exists. We use a lab-in-the-field experiment to test whether the presence of ideologically more conservative students in academic discussion groups, as compared to groups of students who all slanted ideologically liberal, would improve academic outcomes in terms of the quality of each student’s individual academic work. The complete population of an incoming cohort of policy graduate students (N = 78) took part in the experiment. Results demonstrate that students assigned to the ideologically heterogeneous discussion groups subsequently wrote individual assignments that received significantly more negative grades by a professional grader blind to experimental condition and to student identity. Survey results from participating students also suggest that students in the ideologically heterogeneous discussion groups were also significantly more likely to perceive interpersonal conflict and to dislike their group dynamics—a result that was not driven by students of a particular ideological slant. As a small pilot, this study provides questions to resolve with future research, including the role of pedagogy in managing ideological diversity, and provides a template for future experimental designs
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The Price of a Neighbor's Hate: Assessing the Educational Impacts of the 2019 Xenophobic Uprising in South Africa
No full textXenophobic uprisings in South Africa have killed, injured, and displaced hundreds of Black, African migrants. Using school location as a proxy for exposure to xenophobic violence, I estimate a difference-in-differences model on immigrant performance in the South African National Senior Certificate Examinations (NSC). From this estimation, I find that the 2019 xenophobic uprising led to a 12 percentage point decline in immigrants’ NSC Overall Pass Rate. This effect is unique to immigrant students, whose 2019 pass rates declined by 8% relative to non-immigrants and immigrants far from attacks. Adverse impacts are, however, short-term, and do not persist past the year of exposure. For all other NSC outcomes, including Mathematics pass rates and Distinction attainment, noisy nulls obscure the full scope of the uprising’s educational impacts.Applied Mathematic
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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Three Essays on the Provision of Local Public Goods
No full textThis dissertation consists of three papers on the provision of local public goods.
Chapters 1 and 2 consider the criminogenic and social consequences of New York City's ``Stop and Frisk'' program, respectively. In these papers, co-author Andrew Bacher-Hicks and I leverage the quasi-random movement of NYPD police commanders across precincts to identify the causal impact of this policing strategy on crime and long-run educational attainment. We first find that a commander’s predicted effect on stops—--based on data from previous precincts—--is highly predictive of changes in observed stops after that commander enters a new precinct. In Chapter 1, we find that high propensity-to-stop commanders decrease low-level offenses within their precinct. However, we find no corresponding decrease in more serious felony offenses, and find suggestive evidence that within-precinct misdemeanor crime reductions are offset by crime displacement to adjacent neighborhoods. Contrary to the broken windows theory of policing, our findings suggest that stop-and-frisk tactics do not deter more serious criminal behavior.
In Chapter 2, we estimate the social impact of stop-and-frisk policing. We find that exposure to high propensity-to-stop commanders in middle school has negative effects on students' high school graduation, college enrollment, and college persistence rates. These effects are concentrated among black students, who belong to the racial group overwhelmingly targeted by police stops. We find evidence of improvements to school safety and positive spillovers for white and Asian students, who are less likely to directly interact with police.
Finally, Chapter 3 estimates the impact of top-down local public goods provision on citizen engagement. I leverage the fact that routine street maintenance in Boston is determined according to a well-defined set of criteria---underlying street quality and city geography---to estimate the causal impact of traditional, bureaucrat-driven local public goods provision on citizen requests. I find that exogenous shocks to seasonal street paving decrease requests for future street repairs, while at the same time increasing future requests for non-street public goods. Reductions in requests for future street repairs are primarily driven by the mechanical improvement paving brings to street quality. On the other hand, results for non-street public goods are consistent with the notion that top-down local public goods provision sends a positive signal to citizens about both government effectiveness and responsiveness.Public Polic
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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