Alex Hanna

The authors describe protest patterns at U.S. and Canadian universities in the 2010s. The research draws on a new dataset, the Higher Ed Protest Event Dataset, which combines machine learning and sociological hand coding of 16,069 campus newspaper articles. The sample consists of 5,553 higher ed protests involving 584 universities and colleges between 2012 and 2018. The dataset also includes university and police responses to a subset of protests. The authors find that protest frequency is patterned by the academic calendar. The top issue in both U.S. and Canadian higher education protests was university administration and governance. The comparative analysis reveals distinctive patterns in other issues raised and protest intensity. In the United States, the periods of greatest protest activity were waves of mass mobilization across the country on often racialized issues with a national dimension: racist police violence, racially hostile campus climates, and Donald Trump’s presidency. In Canada, protest activity was most intense during provincial or local campaigns led by formal student organizations and unions on issues of economic security: public tuition, austerity, and labor conditions. Across both countries, university administrations and police usually avoided extensive intervention during protests. The findings contribute to social movements research through methodological innovations and new empirical insights on movements in higher education.

The authors describe protest patterns at U.S. and Canadian universities in the 2010s. The research draws on a new dataset, the Higher Ed Protest Event Dataset, which combines machine learning and sociological hand coding of 16,069 campus newspaper articles. The sample consists of 5,553 higher ed protests involving 584 universities and colleges between 2012 and 2018. The dataset also includes university and police responses to a subset of protests. The authors find that protest frequency is patterned by the academic calendar. The top issue in both U.S. and Canadian higher education protests was university administration and governance. The comparative analysis reveals distinctive patterns in other issues raised and protest intensity. In the United States, the periods of greatest protest activity were waves of mass mobilization across the country on often racialized issues with a national dimension: racist police violence, racially hostile campus climates, and Donald Trump’s presidency. In Canada, protest activity was most intense during provincial or local campaigns led by formal student organizations and unions on issues of economic security: public tuition, austerity, and labor conditions. Across both countries, university administrations and police usually avoided extensive intervention during protests. The findings contribute to social movements research through methodological innovations and new empirical insights on movements in higher education.

Information access research (and development) sometimes makes use of gender, whether to report on the demographics of participants in a user study, as inputs to personalized results or recommendations, or to make systems gender-fair, amongst other purposes. This work makes a variety of assumptions about gender, however, that are not necessarily aligned with current understandings of what gender is, how it should be encoded, and how a gender variable should be ethically used. In this work, we present a systematic review of papers on information retrieval and recommender systems that mention gender in order to document how gender is currently being used in this field. We find that most papers mentioning gender do not use an explicit gender variable, but most of those that do either focus on contextualizing results of model performance, personalizing a system based on assumptions of user gender, or auditing a model’s behavior for fairness or other privacy-related issues. Moreover, most of the papers we review rely on a binary notion of gender, even if they acknowledge that gender cannot be split into two categories. We connect these findings with scholarship on gender theory and recent work on gender in human-computer interaction and natural language processing. We conclude by making recommendations for ethical and well-grounded use of gender in building and researching information access systems.

We call for a relational approach to constructing protest event data from news sources to provide tools for detecting and correcting errors and for capturing the relations among events and between events and the texts describing them. We address two problems with most protest event datasets: (1) inconsistencies and errors in identifying events and (2) disconnect between data structures and what is known about how protests and media accounts of protests are produced. Relational data structures can capture the theoretically important structuring of events into campaigns and episodes and media attention cascades and cycles. Relational data structures support richer theorizing about the interplay of protests and their representations in news media discourses. We present preliminary illustrative data about Black protests from these new procedures to demonstrate the value of this approach. Preprint of a paper that has been accepted for publication in Mobilization: An International Quarterly. The published version will be edited to meet publication formatting guidelines. This paper is a substantial revision of “Constructing Theory-Informed Relational and Verifiable Protest Event Data” posted to SocArXiv https://osf.io/preprints/socarxiv/spzgx/ in September 2021.

Using novel data, we provide the first panoramic view of US Black movement protest events as reported in US newswires between 1994 and 2010 and put our quantitative data into dialog with qualitative accounts. Struggles during these years presaged the Black Lives protest waves of 2014-2016 and 2020. Protests increased after the 1995 Million Man March into 2001, but dropped abruptly after the 9/11 attacks. Collective action increased again at the end of the 2000s. Protests in response to police violence and other criminal legal issues were major arenas of struggle and news coverage. Also common were issues of national identity including celebrations of Black history and Black solidarity, protests about Confederate symbols, and protests about White hate groups and hate crimes. While Black people protested about a wide variety of issues, newswires focused disproportionately on incidents of police violence and perceived threats of Black violence. There is substantial continuity in issues, organizations, and activism between this earlier period and the Black Lives Movement of 2014-2020. Content warning: parts of this article describe incidents of police violence.This is a preprint of an article forthcoming in Sociological Science.

Protest event data are both undertheorized and riddled with inconsistencies and errors. We call for modifying standard practices in the collection and construction of protest event data from electronic archives of news sources to both improve verifiability of data and integrate theory with data construction. The key change is a relational data structure that maintains strong links between events identified by coders and the underlying textual sources. This allows study of the relation between events and news coverage of those events. An additional change is to record data on the relations among events, including both recognition of complex events involving multiple actors, dates, action forms, or locations and explicit acknowledgement of the connection of events to specific protest campaigns or episodes of contention. We present preliminary illustrative data about Black protests from these new procedures to demonstrate the value of this approach. NOTE: This is a working paper. Comments and feedback are appreciated.

Scholars are increasingly concerned about social biases in facial analysis systems, particularly with regard to the tangible consequences of misidentification of marginalized groups. However, few have examined how automated facial analysis technologies intersect with the historical genealogy of racialized gender—the gender binary and its classification as a highly racialized tool of colonial power and control. In this paper, we introduce the concept of auto-essentialization: the use of automated technologies to re-inscribe the essential notions of difference that were established under colonial rule. We consider how the face has emerged as a legitimate site of gender classification, despite being historically tied to projects of racial domination. We examine the history of gendering the face and body, from colonial projects aimed at disciplining bodies which do not fit within the European gender binary, to sexology's role in normalizing that binary, to physiognomic practices that ascribed notions of inferiority to non-European groups and women. We argue that the contemporary auto-essentialization of gender via the face is both racialized and trans-exclusive: it asserts a fixed gender binary and it elevates the white face as the ultimate model of gender difference. We demonstrate that imperialist ideologies are reflected in modern automated facial analysis tools in computer vision through two case studies: (1) commercial gender classification and (2) the security of both small-scale (women-only online platforms) and large-scale (national borders) spaces. Thus, we posit a rethinking of ethical attention to these systems: not as immature and novel, but as mature instantiations of much older technologies.

A recent editorial in Nature Methods, “Giving Software its Due”, described challenges related to the development of research software and highlighted, in particular, the challenge of software publication and citation. Here, we call attention to a system that we have developed that enables community-driven software review, publication, and citation: The Journal of Open Source Software (JOSS) is an open-source project and an open access journal that provides a light-weight publishing process for research software. Focused on and based in open platforms and on a community of contributors, JOSS evidently satisfies a pressing need, having already published more than 500 articles in approximately three years of existence.