‘Arrested Justice’ framed within a black feminist perspective of activism and resistance is an excellent read. In search of social justice for low-income black (African American) women, the text is...

Arrested justice: black women, violence and America's prison nation

/pdf/the-lancet-commission-on-lessons-for-the-future-from-the-3b11rs1e.pdf

The Lancet Commission on lessons for the future from the COVID-19 pandemic

In this article, we consider how, due to a spike in anti-Asian hate crimes, Asians might face a disproportionate mental health impact of the COVID-19 pandemic. Analyzing data from the University of...

https://www.tandfonline.com/doi/pdf/10.1080/01419870.2020.1851739

Anti-Asian discrimination and the Asian-white mental health gap during COVID-19

http://www.thelancet.com/article/S0140673622015859/pdf

The spread of COVID-19 has sparked racism, hate, and xenophobia in social media targeted at Chinese and broader Asian communities. However, little is known about how racial hate spreads during a pandemic and the role of counterhate speech in mitigating the spread. Here we study the evolution and spread of anti-Asian hate speech through the lens of Twitter. We create COVID-HATE, the largest dataset of anti-Asian hate and counterhate spanning three months, containing over 30 million tweets, and a social network with over 87 million nodes. By creating a novel hand-labeled dataset of 2,400 tweets, we train a text classifier to identify hate and counterhate tweets that achieves an average AUROC of 0.852. We identify 891,204 hate and 200,198 counterhate tweets in COVID-HATE. Using this data to conduct longitudinal analysis, we find that while hateful users are less engaged in the COVID-19 discussions prior to their first anti-Asian tweet, they become more vocal and engaged afterwards compared to counterhate users. We find that bots comprise 10.4% of hateful users and are more vocal and hateful compared to non-bot users. Comparing bot accounts, we show that hateful bots are more successful in attracting followers compared to counterhate bots. Analysis of the social network reveals that hateful and counterhate users interact and engage extensively with one another, instead of living in isolated polarized communities. Furthermore, we find that hate is contagious and nodes are highly likely to become hateful after being exposed to hateful content. Importantly, our analysis reveals that counterhate messages can discourage users from turning hateful in the first place. Overall, this work presents a comprehensive overview of anti-Asian hate and counterhate content during a pandemic. The COVID-HATE dataset is available at this http URL.

Racism is a Virus: Anti-Asian Hate and Counterhate in Social Media during the COVID-19 Crisis

Coronavirus Disease 2019 (COVID-19) is believed to have emerged in Wuhan, China in late December 2019 and began rapidly spreading around the globe throughout the spring months of 2020. As COVID-19 proliferated across the United States, Asian Americans reported a surge in racially motivated hate crimes involving physical violence and harassment. Throughout history, pandemic-related health crises have been associated with the stigmatization and “othering” of people of Asian descent. Asian Americans have experienced verbal and physical violence motivated by individual-level racism and xenophobia from the time they arrived in America in the late 1700s up until the present day. At the institutional level, the state has often implicitly reinforced, encouraged, and perpetuated this violence through bigoted rhetoric and exclusionary policies. COVID-19 has enabled the spread of racism and created national insecurity, fear of foreigners, and general xenophobia, which may be related to the increase in anti-Asian hate crimes during the pandemic. We examine how these crimes – situated in historically entrenched and intersecting individual-level and institutional-level racism and xenophobia – have operated to “other” Asian Americans and reproduce inequality.

/pdf/anti-asian-hate-crime-during-the-covid-19-pandemic-exploring-4etm0vrxon.pdf

Anti-Asian Hate Crime During the COVID-19 Pandemic: Exploring the Reproduction of Inequality

Women in the United States are more likely to be killed by an intimate partner than anyone else, and prior, severe domestic violence (DV) is typically involved in such intimate partner homicides (IPH). Black women experience disproportionately high rates of DV and IPHs, severe injury, and abuse with weapons. Distinct patterns of escalating DV are associated with impending risk of re-victimization and lethal violence. One of the most common predictors associated with formal DV help-seeking is severity of physical violence. The current study uses semi-structured interviews with 11 severe abuse survivors to answer the following research questions: (1) How do women experiencing severe abuse make sense of DV resources across the course of their abusive relationships? (2) How do women experiencing severe abuse make sense of services when fear of death/homicide risk is present? Approximately 91% of the sample is comprised of women of color (WOC) survivors. Results demonstrate that WOC survivors navigated complex journeys toward formal DV help-seeking that involved resisting help-seeking when the abuse still felt manageable; delaying help-seeking to protect themselves from escalating violence; and hastening help-seeking when breaking points were reached and the risk of death felt tangible. DV resources took on a different meaning in participants' lives as abuse became more severe across the abuse lifecourse, and in relation to life circumstances and patterns of abuse, and personal perceptions of homicide risk. WOC participants also often experienced multiple structural barriers to formal help-seeking and waited until the violence was severe and/or life-threatening to make first contact, which highlights the necessity of immediate risk assessment with responsive service offerings that address the link between DV and poverty, as well as regular follow-up and ongoing support.

“I'm Just Like, You Know What, It’s Now or Never”: Exploring How Women of Color Experiencing Severe Abuse and Homicide Risk Journey Toward Formal Help-Seeking:

Specialized domestic violence courts (DVCs) have been a popular judicial option for processing domestic violence (DV) offenders since the 1990s. While DVCs vary in structure, common core components...

Courting Justice: Tracing the Evolution and Future of Domestic Violence Courts:

This study examines the relationship between structural characteristics and homicide trajectories in South Korean neighborhoods utilizing the systemic model of social disorganization theory as an a...

Testing the Systemic Model of Social Disorganization Theory in South Korean Neighborhoods: A Latent Class Growth Analysis Approach to Specifying Pathways to Homicide:

https://link-springer-com-443.webvpn.jmu.edu.cn/content/pdf/10.1007%2F978-3-319-62122-7_203-1.pdf

Shannon B. Harper

Papers

Anti-Asian Hate Crime During the COVID-19 Pandemic: Exploring the Reproduction of Inequality

“I'm Just Like, You Know What, It’s Now or Never”: Exploring How Women of Color Experiencing Severe Abuse and Homicide Risk Journey Toward Formal Help-Seeking:

Courting Justice: Tracing the Evolution and Future of Domestic Violence Courts:

Testing the Systemic Model of Social Disorganization Theory in South Korean Neighborhoods: A Latent Class Growth Analysis Approach to Specifying Pathways to Homicide:

A Feminist Perspective on the Criminal Justice System Response to Domestic Violence