Search results

Social movements are made up of organized groups and individuals working together to accomplish shared objectives. Under what circumstances do active groups build and break their coalitions? Five conditions have been identified in the literature as influencing coalition formation: common identity, resources, organizational structure, historical connection, and institutional setting. Whereas coalition dynamics within a movement wave are best understood in terms of institutional opportunities and threats, further research is needed to determine how and to what extent these contextual elements influence coalitions. This chapter examines how threats posed by indiscriminate and selective repression affect the shape and structure of interorganizational coalitions during the 2019 Anti-Extradition Law Amendment Bill (Anti-ELAB) protests in Hong Kong. The analysis relies on an original political event dataset and an organization-event network dataset. These datasets were produced utilizing syntactic event coding techniques based on Telegram posts, which Hong Kong protesters used to distribute information, plan future actions, and crowdsource news. Furthermore, Telegram provides detailed information about state activities, event-level coalitions, and violent groups, which is difficult to access from other sources. This study investigates the coalition networks across the movement's four stages, each of which was marked by a particular type and degree of repression. The findings indicate that indiscriminate and selective repression have varied effects on coalition networks. A wide coalition disintegrates as a result of indiscriminate repression. Selective repression, however, leads to the formation of coalitions around activist groups targeted by repression.

While social media data are used increasingly in studies of social movements, social media evolves far more rapidly than academic research and publication. This chapter argues that researchers should adopt historical and archival approaches to social media data. Treating social media data as an “instant archive” – one that is self-curated, is co-constituted, and changes rapidly – we caution researchers to pay attention to the features of this archive and their implications for working with the data therein. Applying insights from recent discussions of archival methods for social science research to the specific features of social media data, we explore how platform features, repressive effects, and user innovations affect the content of the instant archive. We then offer strategies for researchers' methodological approaches, including how best to select units of analysis and platforms, how to collect and interpret archival materials, and how to identify silences in the data.

Recent USA police responses to civil rights demonstrations have drawn attention toward the 1033 Program – a military surplus transfer program from the Department of Defense (DOD) to police agencies in the USA – as well as calls for dissolution or reform of the program. However, policy decisions have been sporadic and empirical literature examining the program have relied on public data, which contain information about equipment transfers, but does not show the frequency of agencies' use of this equipment – or contexts of use – once received.

This study presents the findings of a survey of a national sample of law enforcement agencies that used the program to obtain armored vehicles, rifles, and body armor and how these agencies used this equipment in 2019 and 2020. Correlations and binary logistic regression models are tested for 2019 to examine the racial threat hypothesis and additional predictors of equipment use.

A statistically significant correlation is found between perceived percentage of Black and other race residents and the frequency of armored vehicle deployment in 2019 and between the perceived percentage of other race residents and the percentage of special weapons and tactics (SWAT) officers wearing body armor. Perceived increases in drug crimes also significantly increase the likelihood of SWAT officers carrying military rifles, with increased odds of 402.3%.

This study is the first to examine contextual data surrounding law enforcement use of 1033 Program acquisitions with a national sample, assisting in providing greater accuracy in determining predictors and outcomes of the program's use.