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Record W4406326996 · doi:10.61869/ufss3027

Humane alternatives: Co-operative education at Stony Mountain Institute

2021· article· en· W4406326996 on OpenAlexaboutno aff
Judi Harris, Lui Tam

Bibliographic record

VenueJournal of Co-operative Studies · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsArchaeologyPolitical scienceHistory

Abstract

fetched live from OpenAlex

Although the International Covenant on Economic, Social and Cultural Rights states that education is a human right, there is limited access to university education at either provincial or federal carceral institutions in Canada. Inspired by the Inside-Out Prison Exchange Programme in the USA, the Walls to Bridges programme in Canada offers courses that bring campus enrolled and incarcerated students together to study behind the prison walls. In 2014, the University of Winnipeg faculty began teaching courses for credit at correctional facilities in the surrounding areas of Winnipeg as part of this programme. Two of the courses offered are focused on co-operatives. Based on a case study of higher education at Stony Mountain Institution (Manitoba), we support the claim that education on co-operatives in prison could shift the prison culture from “maintenance mode” to a “community correctional mode” and would facilitate the development of co-operatives that support people inside the prison and in the community, post-release.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.952
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.004
Scholarly communication0.0050.002
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0310.001

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 head0.048
GPT teacher head0.371
Teacher spread0.323 · 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 designQualitative
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
Published2021
Admission routes1
Has abstractyes

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