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Record W4226485645 · doi:10.5206/fpq/2021.4.13713

Racial Injustice and Information Flow

2021· article· en· W4226485645 on OpenAlexvenueno aff
Eric Bayruns García

Bibliographic record

VenueFeminist Philosophy Quarterly · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsInjusticeFlow (mathematics)SociologyPolitical sciencePsychologyMechanicsSocial psychologyPhysics

Abstract

fetched live from OpenAlex

I submit that the critical epistemology of race and standpoint literature has not explicitly focused on the properties of information about racial or gender injustice in a way similar to how epistemologists have focused on propositions and information when they describe propositional justification. I present an account of information flow in which I describe information in the racial-injustice-information domain in a way similar to how epistemologists describe propositional justification. To this end, I argue (C1) that if subjects in racially unjust societies tend to violate norms that promote a community’s reliable information flow because racial prejudice is widely held in racially unjust societies, then racial injustice can make information flow less reliably in a community. And I argue (C2) that if racial prejudice can make information flow less reliably in a community, then information that nondominant subjects are more likely to have will less reliably flow to community members who lack it.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0030.017
Scholarly communication0.0070.017
Open science0.0010.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.000

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 head0.017
GPT teacher head0.287
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2021
Admission routes1
Has abstractyes

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Same venueFeminist Philosophy QuarterlySame topicSocial Media and PoliticsFrench-language works237,207