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Record W4323666593 · doi:10.1080/07393148.2023.2181538

Power from Below: An Interview with Nargess Mustapha, Co-Founder of Hoodstock (2022 Cloward & Piven Award Recipients)

2023· article· en· W4323666593 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNew Political Science · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsMcGill University
Fundersnot available
KeywordsCaucusPoliticsPower (physics)SociologyInterviewPolitical scienceGender studiesMedia studiesPublic administrationManagementLawAnthropology

Abstract

fetched live from OpenAlex

Abstract Every year, the caucus for critical political science of the American Association of Political Science grants the Richard Cloward and Frances Fox Piven Award to an activist group in the region of the annual meeting of the American Political Science Association (APSA). In 2022, APSA took place in Montreal, Quebec, Canada. This year’s recipient of the award is Hoodstock, a movement-based organization that aims to eliminate systemic inequalities and build supportive, inclusive, safe, and vibrant communities. The author and interviewer is a graduate student in Political Science at McGill University where she conducted fieldwork on people power and intersectional organizing in Montreal. In the following piece, she interviews one of the cofounders of Hoodstock.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.390
Teacher spread0.321 · 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