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  1. Preventing Violence: Insights from Micro-Sociology

    Micro-sociology of violence looks at what happens in situations where people directly threaten violence, but only sometimes carry it out. This process and its turning points have become easier to see in the current era of visual data: cell-phone videos, long-distance telephoto lenses, CCTV cameras. New cues and instruments are on the horizon as we look at emotional signals, body rhythms, and monitors for body signs such as heart rate (a proxy for adrenaline level).
  2. CASM: A Deep-Learning Approach for Identifying Collective Action Events with Text and Image Data from Social Media

    Protest event analysis is an important method for the study of collective action and social movements and typically draws on traditional media reports as the data source. We introduce collective action from social media (CASM)—a system that uses convolutional neural networks on image data and recurrent neural networks with long short-term memory on text data in a two-stage classifier to identify social media posts about offline collective action. We implement CASM on Chinese social media data and identify more than 100,000 collective action events from 2010 to 2017 (CASM-China).
  3. The Meaning of 'Theory'

    ‘Theory’ is one of the most important words in the lexicon of contemporary sociology. Yet, their ubiquity notwithstanding, it is quite unclear what sociologists mean by the words ‘theory,’ ‘theoretical,’ and ‘theorize.’ I argue that confusions about the meaning of ‘theory’ have brought about undesirable consequences, including conceptual muddles and even downright miscommunication. In this paper I tackle two questions: (a) what does ‘theory’ mean in the sociological language?; and (b) what ought ‘theory’ to mean in the sociological language? I proceed in five stages.

  4. The Purposes of Refugee Education: Policy and Practice of Including Refugees in National Education Systems

    This article explores the understood purposes of refugee education at global, national, and school levels. To do so, we focus on a radical shift in global policy to integrate refugees into national education systems and the processes of vernacularization accompanying its widespread implementation. We use a comparative case study approach; our dataset comprises global policy documents and original interviews (n = 147) and observations in 14 refugee-hosting nation-states.
  5. Collective Social Identity: Synthesizing Identity Theory and Social Identity Theory Using Digital Data

    Identity theory (IT) and social identity theory (SIT) are eminent research programs from sociology and psychology, respectively. We test collective identity as a point of convergence between the two programs. Collective identity is a subtheory of SIT that pertains to activist identification. Collective identity maps closely onto identity theory’s group/social identity, which refers to identification with socially situated identity categories. We propose conceptualizing collective identity as a type of group/social identity, integrating activist collectives into the identity theory model.
  6. Analyzing Meaning in Big Data: Performing a Map Analysis Using Grammatical Parsing and Topic Modeling

    Social scientists have recently started discussing the utilization of text-mining tools as being fruitful for scaling inductively grounded close reading. We aim to progress in this direction and provide a contemporary contribution to the literature. By focusing on map analysis, we demonstrate the potential of text-mining tools for text analysis that approaches inductive but still formal in-depth analysis.
  7. Intersubjectivity, Normativity, and Grammar

    Interactants depend on background knowledge and commonsense inferences to establish and maintain intersubjectivity. This study investigates how the resources of language—or more specifically, of grammar—can be mobilized to address moments when such inferences might risk jeopardizing understanding in lieu of promoting it. While such moments may initially seem to undermine the normative commonsensicality of the particular inference(s) in question, the practice examined here is shown to legitimize those inferences through the very act of setting them aside.

  8. How Do We “Do Gender”? Permeation as Over-Talking and Talking Over

    Gendered expectations are imported from the larger culture to permeate small-group discussions, creating conversational inequalities. Conversational roles also emerge from the negotiated order of group interactions to reflect, reinforce, and occasionally challenge these cultural patterns. The authors provide a new examination of conversational overlaps and interruptions. They show how negotiated conversational roles lead a status distinction (gender) to shape conversational inequality.

  9. Trouble in Tech Paradise

    The structures of the tech industry, with its dependence on highly skilled immigrant workers, and the H-1B visa, with its dependence on sponsoring companies, bind tech workers in a cycle of legal violence.

  10. Are Robots Stealing Our Jobs?

    The media and popular business press often invoke narratives that reflect widespread anxiety that robots may be rendering humans obsolete in the workplace. However, upon closer examination, many argue that automation, including robotics and artificial intelligence, is spreading unevenly throughout the labor market, such that middle-skill occupations that do not require a college degree are more likely to be affected adversely because they are easier to automate than high-skill occupations.