Prisoners, Cows and Abattoirs: The Closing of Canada’s Prison Farms as a Political Penal Drama
Bibliographic record
Abstract
In 2009, the Canadian government announced its decision to close six federal prison farms. Although the programme only impacted about 300 prisoners, the decision sparked the creation of a social movement dedicated to fighting to keep the farms operational, and the closures became a sizeable news story in Canada. We argue that actors on both sides of the farm closure issue used it as fuel for staging and capitalizing on a political penal drama. Our findings suggest conservatives do not have a monopoly over using penal dramas to achieve political and social aims and that penal dramas can be extremely productive—well beyond debates over prisoners and prisons. Thus, penal dramas help us capture the nuanced orientation of a particular penal field, which cannot be understood apart from its cast of interested actors or the national, state/provincial or local contexts in which it is embedded.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.039 | 0.020 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".