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Record W2047368663 · doi:10.1177/0741713608327370

An Antiracist Feminist Analysis for the Study of Learning in Social Struggle

2009· article· en· W2047368663 on OpenAlexaff
Rachel Gouin

Bibliographic record

VenueAdult Education Quarterly · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsSociologyPatriarchyMarxist philosophyFoleyGender studiesPolitical actionWhite (mutation)PoliticsEpistemologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

This article outlines, critiques, and revises Griff Foley's analytical framework for the study of informal learning in social action. This reformulation is prompted by the author's own research on young women's experiences and learning in social struggle, and by the need to take into account the interdependence of systems of domination underlying their actions. She draws on anticapitalist and antiracist feminist theory to integrate an analysis of White supremacy and patriarchy within a Marxist political economy. This article helps to reconceptualize the study of learning in social movements so that it may contend with the complexity of society, social struggles, and the contexts in which learning takes place.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.006
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.034
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.367
Teacher spread0.350 · 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

Citations42
Published2009
Admission routes1
Has abstractyes

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