The Matter of Penal Standards: The Material Politics of Penal Government in Haiti and Nunavut
Bibliographic record
Abstract
This dissertation examines the role of the prison within projects of state formation by way of the instrumentalization of punishment in accordance with penal standards: these aim to measure, manage, and steer the conduct of penal governments, practitioners, and prisoners.My research contributes to the fields of governmentality studies, critical criminology, and post-colonial studies through an analysis of penal standardization as the primary means through which states enact moral sovereignty, or the manufacturing of democratic penal institutions.By using penal standards as an analytic of government, and an amalgam of critical document analysis, semistructured interviews, and participant observation, this study examines the application of penal standards within two cases of penal government intervention: Canada's role within the penal aid and justice reconstruction effort in Haiti; and the investigation into sub-standard penality in Nunavut, Canada.The unique contribution of my dissertation, emerging from my empirical focus on the material politics of penal standards, is that penal standards matter as evidenced by the matter (or materiality) of penal standards.In studying the matter of penal standards my research makes three core arguments: first, that penal standards promote technicization in penalty (or penal technē), rather than the actualization of ethical punishment or prisoner human rights; second, that penal standardization aims to disembed a penal government's relationship from a specific locality or culture, recasting this relationship as a universal, normalized, and primarily carceral response to punishment; third, in both of the cases of penal standardization that I study (in Haiti and in Nunavut) penal agents must contend with the paradox of punishing inequalityhow to maintain the monopoly over the authority to punish, or penal legitimacy, without subjecting prisoners to patently inhumane conditions and practices within contexts of significant " i marginalization and inequality.I argue that penal standards, as they are currently imagined, are part of the problem rather than a solution to abnormal forms of punishment, and that the only failures within penal standardization are those ideas and practices which are systematically discounted by the normative assumptions ingrained within penal standards-the failure to imagine punishment as anything other than carceral.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.033 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".