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Record W3192895374 · doi:10.26108/zw62-db51

Rehabilitation programs in Canadian prisons and films: Reality and representation

2013· article· en· W3192895374 on OpenAlexaboutno aff
Hayley Dearman

Bibliographic record

VenueAcadiaU-DEV · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsRepresentation (politics)RehabilitationSociologyPsychologyPolitical scienceMedicinePhysical therapyLawPolitics

Abstract

fetched live from OpenAlex

This thesis examines whether selected films showing rehabilitation of prisoners depict the rehabilitation process realistically. The thesis analyzes four American films that have rehabilitation as a predominant theme and compares the representation of reform in prison to the actual practice of rehabilitation in the Canadian prison system. Media analysis is concerned with decoding the often hidden messages in films that may reflect the dominant or hegemonic ideology. While media effects are controversial in cultural studies, it is important to analyze the messages before you can ask whether they have any effects. The thesis provides a detailed look at the storyline, themes and representation of rehabilitation in the four films. Rehabilitation in Canada is a complex process that includes the accreditation of specific programs and risk/need assessment, which matches inmate needs to specific program opportunities. Using interpretative analysis, I have found that there are more differences than similarities between the Canadian system and rehabilitation shown in films. The Canadian system puts an emphasis on group sessions and education whereas the fictional stories of the films put an emphasis on personal relationships. Films show a glamorized version of rehabilitation that emphasizes the ideology of individual responsibility for personal change.

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 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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score0.223

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.039
GPT teacher head0.331
Teacher spread0.292 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2013
Admission routes1
Has abstractyes

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