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Record W4405343071 · doi:10.1515/9780295806396

Power Interrupted

2016· book· en· W4405343071 on OpenAlexaboutno aff
Sylvanna M. Falcón

Bibliographic record

VenueUniversity of Washington Press eBooks · 2016
Typebook
Languageen
FieldSocial Sciences
TopicHistorical Gender and Feminism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Winner of the 2016 Gloria E. Anzaldua Book Prize, sponsored by the National Women's Studies Association In Power Interrupted , Sylvanna M. Falcón redirects the conversation about UN-based feminist activism toward UN forums on racism. Her analysis of UN antiracism spaces, in particular the 2001 World Conference against Racism, Racial Discrimination, Xenophobia, and Related Intolerance in Durban, South Africa, considers how a race and gender intersectionality approach broadened opportunities for feminist organizing at the global level. The Durban conference gave feminist activists a pivotal opportunity to expand the debate about the ongoing challenges of global racism, which had largely privileged men’s experiences with racial injustice. When including the activist engagements and experiential knowledge of these antiracist feminist communities, the political significance of human rights becomes evident. Using a combination of interviews, participant observation, and extensive archival data, Sylvanna M. Falcón situates contemporary antiracist feminist organizing from the Americas—specifically the activism of feminists of color from the United States and Canada, and feminists from Mexico and Peru—alongside a critical historical reading of the UN and its agenda against racism.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.245
Threshold uncertainty score0.818

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0070.007
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.2450.068

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 head0.035
GPT teacher head0.248
Teacher spread0.214 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations32
Published2016
Admission routes1
Has abstractyes

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