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HERO <i>AND</i> INMATE: WORK, PRISONS, AND PUNISHMENT IN CALIFORNIA'S FIRE CAMPS

2012· article· en· W1918405442 on OpenAlex
Philip Goodman

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.

Bibliographic record

VenueWorkingUSA · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPrisonPunishment (psychology)Work (physics)CriminologyHEROState (computer science)SociologyPolitical sciencePsychologySocial psychologyEngineeringArt

Abstract

fetched live from OpenAlex

The debate over penal labor has been a vociferous one, as advocates and proponents have, for at least a century, made their case for or against the practice of putting prisoners to work. Nonetheless, conspicuously absent from this discussion have been the very people who most directly and intimately experience that work: prison inmates. In this article, I examine penal labor as it unfolds in one particular carceral site, namely California's prison fire camps in which state prisoners do manual labor and fight fires. The results reveal that binaries in which prison labor is positioned as either entirely good or entirely exploitative do not mesh well with the multifaceted experiences of those on the ground, who find elements of both at play. The fire camps are, therefore, an atypical case study that will hopefully serve as impetus for more research into the experiences of prisoner workers, as well as a starting point for deepening and complicating the existing debate over work and punishment.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.878

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.285
Teacher spread0.266 · 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