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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.

Food choices profoundly affect one's dietary, nutritional and health outcomes. Using alcoholic beverages as a case study, the authors assess the potential of genetic data in predicting consumers' food choices combined with conventional socio-demographic data.

A discrete choice experiment was conducted to elicit the underlying preferences of 484 participants from seven provinces in China. By linking three types of data (—data from the choice experiment, socio-demographic information and individual genotyping data) of the participants, the authors employed four machine learning-based classification (MLC) models to assess the performance of genetic information in predicting individuals' food choices.

The authors found that the XGBoost algorithm incorporating both genetic and socio-demographic data achieves the highest prediction accuracy (77.36%), significantly outperforming those using only socio-demographic data (permutation test p-value = 0.033). Polygenic scores of several behavioral traits (e.g. depression and height) and genetic variants associated with bitter taste perceptions (e.g. TAS2R5 rs2227264 and TAS2R38 rs713598) offer contributions comparable to that of standard socio-demographic factors (e.g. gender, age and income).

This study is among the first in the economic literature to empirically demonstrate genetic factors' important role in predicting consumer behavior. The findings contribute fresh insights to the realm of random utility theory and warrant further consumer behavior studies integrating genetic data to facilitate developments in precision nutrition and precision marketing.

This article analyses the structure of hypertext and the world wide web through the contrasting metaphors of the network and the rhizome and applies that analysis to the epistemic challenge presented by fake news.

The paper is a critical and theoretical study of the development of concepts in information science. It outlines the limitations of the network metaphor and analyses the ways in which it has influenced both the development and critical understanding of the World Wide Web and its wider social and cultural consequences. The paper develops an alternative description of the ontological structure of the Web in terms of interrupted and dissipated energy flows.

The paper argues that the Web is better described as a dynamic reorganization of the socio-cultural system that has no determinate boundaries and which is constituted properly in the spaces between technologies and the spaces between persons.

The paper contributes to and extends research into the rhizomic nature of hypertext and the Word Wide Web and in understanding the role of metaphor in descriptions of hypertext and the web.

This study aims to establish a comprehensive understanding of the intricacies of how individuals engage with deepfakes, focusing on limiting adverse effects and capitalizing on their benefits.

This study conducted a meta-synthesis of qualitative studies on deepfakes, incorporating study-specific analysis followed by a cross-study synthesis.

Based on the meta-synthesis, the study developed an integrated conceptual framework based on the perspectives from the social shaping of technology theory embedding deepfake-related assertions, motivations, the subtleties of digital platforms, and deepfake-related repercussions.

The study offers crucial insights into the evolving nature of deepfakes as a socio-technical phenomenon and the significance of platform dynamics in deepfake production. It enables researchers to comprehend the cascading effects of deepfakes and positions them to evaluate deepfake-related risks and associated mitigation mechanisms.

The framework that emerges from the study illustrates the influence of platforms on the evolution of deepfakes and assists platform stakeholders in introducing effective platform governance structures to combat the relentless proliferation of deepfakes and their consequences, as well as providing guidance for governments and policymakers to collaborate with platform leaders to set guardrails for deepfake engagement.

Deepfakes have been extensively contested for both their beneficial and negative applications and have been accused of heralding an imminent epistemic threat that has been downplayed by some quarters. This diversity of viewpoints necessitates a comprehensive understanding of the phenomenon. In responding to this call, this is one of the first to establish a comprehensive, theoretically informed perspective on how individuals produce, process, and engage with deepfakes through a meta-synthesis of qualitative literature on deepfakes.

The authors explore the hypothesis that some movements in commodity prices are anticipated (news shocks) and can trigger aggregate fluctuations in small open emerging economies. This paper aims to discuss the aforementioned objective.

The authors build a multi-sector dynamic stochastic general equilibrium model with endogenous commodity production. There are five exogenous processes: a country-specific interest rate shock that responds to commodity price fluctuations, a productivity (TFP) shock for each sector and a commodity price shock. Both TFP and commodity price shocks are composed of unanticipated and anticipated components.

The authors show that news shocks to commodity prices lead to higher output, investment and consumption, and a countercyclical movement in the trade-balance-to-output ratio. The authors also show that commodity price news shocks explain about 24% of output aggregate fluctuations in the small open economy.

Given the importance of both anticipated and unanticipated commodity price shocks, policymakers should pay attention to developments in commodity markets when designing policies to attenuate the business cycles. Future research should investigate the design of optimal fiscal and monetary policies in SOE subject to news shocks in commodity prices.

This paper contributes to the knowledge of the sources of fluctuations in emerging economies highlighting the importance of a new source: news shocks in commodity prices.

This chapter addresses the potential for knowledge, learning, and collaboration (KLC) cultures in public sector organizations. Public sector organizations are among the most complex for introducing or nourishing a KLC approach because there are multiple levels of cultures with varying levels of influence. We describe these complex cultures as tiers. First, we define public sector organizations’ business goals, purpose, and strategies. Then, the authors translate and interpret all five levels of culture for public sector organizations. The chapter also details the nature of cultural complexity, namely the four tiers of public sector cultures: (1) the company culture (Tier 1); (2) the public service culture (Tier 2); (3) the culture of the external environment (Tier 3); and (4) the internal KLC cultures (Tier 4). This chapter establishes a framework for describing an organization’s complex culture and determining the best KLC approach for the context.

School violence can cause or exacerbate individual and collective trauma. Trauma-informed school approaches offer schools and educators guidance for how to respond. In this chapter, we provide an overview of trauma-informed school approaches and their contributions to healing individual and collective trauma. We begin this chapter by addressing the complex intersection of disability and trauma, and the unique implications of school-based violence for students with disabilities and their teachers. We then define trauma-informed care, describe current short- and long-term trauma-informed school approaches, and explain the aims of these approaches at individual and collective levels. Next, we locate trauma-informed responses to school violence in a context of systemic trauma and share considerations for disrupting the systemic conditions that perpetuate trauma and school violence. We discuss critiques of the trauma-informed care movement and conclude with recommendations for scholars pursuing research in this area.

Despite long-standing evidence that the use of exclusionary discipline practices is both ineffective and even potentially harmful, these policies continue to be used in educational settings across the country. In this chapter, we discuss the problems associated with exclusionary discipline, with an emphasis on zero tolerance approaches. We begin our discussion with a brief history of the origin of zero tolerance policies, a presentation of data that contradict the effectiveness of such policies, and examples of the continued and egregious application of this exclusionary approach. We discuss problems of disproportionality associated with the use of zero tolerance policies, including how this approach exacerbates learning problems for students with and at risk for disabilities, especially if that risk is related to emotional and behavioral disorders (EBD). We conclude by offering alternatives to a zero tolerance approach in the form of positive and preventative approaches for improving student behavior across various levels of intensity within a tiered system of support framework.