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Record W3088624986 · doi:10.1111/spc3.12568

Under lying conditions of gender‐based violence—Decolonial feminism meets epistemic ignorance: Critical transnational conversations

2020· article· en· W3088624986 on OpenAlexaboutno aff
Puleng Segalo, Michelle Fine

Bibliographic record

VenueSocial and Personality Psychology Compass · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipFeminismGender studiesSociologyIntersectionalityDignitySilenceConversationPolitical scienceAestheticsLaw

Abstract

fetched live from OpenAlex

Abstract This article engages a doubled conversation, between South Africa and the United States, about gender‐based violence and the curious epistemic silence, even in critical psychology, about gendered and racialized violence as a deep sedimentary, transnational and transhistoric, layer of (in)human(e) existence. In this article, we lift up the long history of underlying conditions of state‐sponsored and socially enacted violence, and we also problematize how social science scholarship has been designed, underlying conditions, such that anti‐Black violence and gender‐based violence are routinely (mis)represented as if idiosyncratic ruptures—microaggressions or battered women—in an otherwise smooth social fabric. Through the lens of decolonial feminism, we examine how the COVID‐19 crisis makes public the gendering of violence, especially against Black women, as if it were a spike, obscuring how pervasive and enduring it is—a constant moan in South Africa, India, the United States, among native women in Canada, and other places around the globe. We end by calling for critical scholarship that peels back the symptom of gender‐based violence, recognizes the history and ongoing structural enactment of racialized and gendered violence, and excavates the bold and relentless heartbeat of resistance narrated in quiet and loud demands for dignity, liberation, and desire.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.677
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.166
GPT teacher head0.427
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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