Verbal Microaggressions as Hyper‐implicatures*

Gomez, Javiera Perez

doi:10.1111/jopp.12243

Cited by 12 publications

(4 citation statements)

References 32 publications

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“…Prejudiced language reflects and perpetuates social inequalities and stereotypical beliefs (Beukeboom and Burgers, 2019). As argued by Perez Gomez (2021), when accepting subtly prejudiced statements as true, we inherently accept the underlying stereotype as true. Therefore, the harmful implications of hate speech must be challenged to mitigate the spread of such beliefs.…”

Section: Language and Stereotypesmentioning

confidence: 98%

Beyond Denouncing Hate: Strategies for Countering Implied Biases and Stereotypes in Language

Mun,

Allaway,

Yerukola

et al. 2023

Findings of the Association for Computational Linguistics: EMNLP 2023

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Counterspeech, i.e., responses to counteract potential harms of hateful speech, has become an increasingly popular solution to address online hate speech without censorship. However, properly countering hateful language requires countering and dispelling the underlying inaccurate stereotypes implied by such language. In this work, we draw from psychology and philosophy literature to craft six psychologically inspired strategies to challenge the underlying stereotypical implications of hateful language. We first examine the convincingness of each of these strategies through a user study, and then compare their usages in both human-and machine-generated counterspeech datasets. Our results show that human-written counterspeech uses countering strategies that are more specific to the implied stereotype (e.g., counter examples to the stereotype, external factors about the stereotype's origins), whereas machine-generated counterspeech uses less specific strategies (e.g., generally denouncing the hatefulness of speech). Furthermore, machinegenerated counterspeech often employs strategies that humans deem less convincing compared to human-produced counterspeech. Our findings point to the importance of accounting for the underlying stereotypical implications of speech when generating counterspeech and for better machine reasoning about antistereotypical examples.

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Section: Language and Stereotypesmentioning

confidence: 98%

Beyond Denouncing Hate: Strategies for Countering Implied Biases and Stereotypes in Language

Mun,

Allaway,

Yerukola

et al. 2023

Findings of the Association for Computational Linguistics: EMNLP 2023

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show abstract

“…This is strange, especially considering how prominent social condemnation is within John Stuart Mill's reflections on freedom of speech (2008). There are many instances of how such prejudices manifest within all sorts of interactions we have on a daily basis; recently, these have been described as 'microaggressions' (Ridge 2021).…”

Section: What Is Wrong With What Is Demandedmentioning

confidence: 99%

Retheorising Civil Disobedience in the Context of the Marginalised

Stevens

2024

Theoria

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This article proposes a retheorisation of Rawlsian civil disobedience through examining the burdens we expect people to bear when they practice civil disobedience, focussing specifically on marginalised groups. First, I consider public concerns over civil disobedience, to elicit the idea of an ‘authentic civil disobedience’. I then assess the claim that civil disobedience occurs within a ‘nearly just’ society in order to recognise the more complex position of marginalised civil disobedients. This allows me to frame any criteria we theorise for civil disobedience as a wicked problem. Next, I examine one particular criterion dominant within the literature: that to be interpreted as civil disobedience, disobedients must show a willingness to suffer the legal consequences – and so, must not act anonymously. I claim that this asks too much of civil disobedients in a marginalised context and conclude civil disobedience theory needs retheorising to consider when and why anonymity is acceptable.

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“…For racial microaggressions, behavioral microaggressions are subtle but racially biased and hostile actions toward racial minorities that signal exclusion and scorn [16,22,23]; verbal microaggressions are "derogatory racial slights and insults" [23 , p. 273]. These actions are directed toward a minority population to convey otherness and judgement [24]. For discrimination, workplace discrimination signifies discriminatory practices and prejudices at workplaces toward people of color, and institutional racism refers to "racially discriminatory policies or practices ingrained in institutional mechanisms and processes" [10 , p. 6].…”

Section: Introductionmentioning

confidence: 99%

The Association Between Discriminatory Experiences and Self-Reported Health Status among Asian Americans and Its Subethnic Group Variations

2021

J. Racial and Ethnic Health Disparities

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Purpose Using distinct measures for racial microaggressions and discrimination, this article explored the association between discriminatory experiences and self-reported health status among Asian populations in the USA and its subethnic group variation. Methods This article investigated 4393 Asian American adults from the 2016 Post-Election National Asian American Survey (NAAS). Binary measure of self-reported health (not good/good) was accounted for. Two measures of racial microaggressions included (1) verbal microaggression and (2) behavioral microaggression. Two measures of discrimination encompassed (1) workplace discrimination and (2) institutional racism. Ethic groups were classified to (1) East Asian (n=1491), (2) Southeast Asian (n=1758), or (3) South Asian (n=1144). Results Findings from logistic regression analyses showed that increased workplace discrimination and institutional racism yielded decreased odds of reporting good health status. The association between racial microaggressions, discrimination, and self-reported health status varied across ethnic subgroup, indicating that the verbal aggression score was more predictive for the East Asian group while institutional racism was most harmful to Southeast Asians. Discussion Findings highlighted the racialized interpretation and its variations in self-reported health status among Asian populations. Relating to variations in experiences of racialization and attainment of socioeconomic status, disproportionate relationships of discriminatory experiences and health among Asian populations were further discussed.

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Verbal Microaggressions as Hyper‐implicatures*

Cited by 12 publications

References 32 publications

Beyond Denouncing Hate: Strategies for Countering Implied Biases and Stereotypes in Language

Beyond Denouncing Hate: Strategies for Countering Implied Biases and Stereotypes in Language

Retheorising Civil Disobedience in the Context of the Marginalised

The Association Between Discriminatory Experiences and Self-Reported Health Status among Asian Americans and Its Subethnic Group Variations

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