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Record W289594670

Ending the Isolation: An Introduction to the Special Volume on Human Rights and Solitary Confinement

2015· article· en· W289594670 on OpenAlexaffabout
Debra Parkes

Bibliographic record

VenueeYLS (Yale Law School) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSolitary confinementLawIsolation (microbiology)Political scienceVariety (cybernetics)Resistance (ecology)Face (sociological concept)Human rightsCriminologySociologyLaw and economicsSocial scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

Prisoners and their advocates in Canada and around the world have been calling attention to the harms and impact of solitary confinement for some time. What is significant about the current moment is that these calls seem to be achieving some traction, even as the use of solitary confinement grows across jurisdictions. This short piece introduces a special volume of the Canadian Journal of Human Rights which collects the writing of advocates and scholars from a range of disciplines (criminology, law, philosophy) who bring a variety of perspectives and methodologies to bear on the opaque correctional systems that hold human beings in isolation for prolonged periods of time. The work in this special volume examines experiences of solitary and prisoner resistance to it. Attending to points of continuity, as well as specificity of this practice across jurisdictions, contributors discuss and critique the persistence of solitary confinement in the face of reform efforts. In considering the potential for change through litigation, law reform, social movements, and acts of resistance, they envision a future without solitary confinement.

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: Commentary · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0070.006
Scholarly communication0.0060.004
Open science0.0020.004
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0170.003

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 head0.313
Teacher spread0.278 · 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
GenreCommentary

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

Citations3
Published2015
Admission routes2
Has abstractyes

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Same venueeYLS (Yale Law School)Same topicCriminal Justice and Corrections AnalysisFrench-language works237,207