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Record W3202470755 · doi:10.1177/02632764211039278

Huey Newton’s Lessons for the Academic Left

2021· article· en· W3202470755 on OpenAlexaff
Jim Vernon

Bibliographic record

VenueTheory Culture & Society · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsYork University
Fundersnot available
KeywordsVanguardProletariatDialecticSociologyPoliticsEpistemologyBridge (graph theory)ImperfectLawPolitical scienceHistoryPhilosophy

Abstract

fetched live from OpenAlex

The Black Panther Party was founded to bridge the radical theorizing that swept college campuses in the mid-1960s and the lumpen proletariat abandoned by the so-called ‘Great Society’. However, shortly thereafter, Newton began to harshly criticize the academic Left in general for their drive to find ‘a set of actions and a set of principles that are easy to identify and are absolute.’ This article reconstructs Newton’s critique of progressive movements grounded primarily in academic debates, as well as his conception of vanguard political theory. Newton’s grasp of revolution as a gradual, open, and above all dialectical process, not only provides a corrective to many dominant academic accounts of the nature of progressive change but, more importantly, it also grounds an emancipatory philosophy that can direct collective struggle, precisely because it remains grounded in the imperfect and internally conflicted lives of those whose freedom is to be won through 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)0.004
metaresearch head score (Gemma)0.008
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: Other · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.029
Scholarly communication0.0080.009
Open science0.0010.004
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0090.002

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 head0.031
GPT teacher head0.346
Teacher spread0.316 · 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
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

Citations1
Published2021
Admission routes1
Has abstractyes

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