Governing on the Margins: Exploring the Contributions of Governmentality Studies to Critical Criminology in Canada
Bibliographic record
Abstract
Despite the promise of the 1970s, critical criminology's influence in Canada has diminished in recent years. This paper examines this decline and charts one possible avenue for renewal. It argues that critical criminology has been limited by its emphasis on the state, and state-centred constructions of criminality, and by its failure to come to terms with how social injustices are reproduced through private institutions and modes of expertise constituted on the margins of the state and in the shadow of the law. Based on this critique, it is proposed that a dialogue with governmentality studies may help to overcome these limits, a dialogue that is examined in two substantive contexts: the governance of immigration and the policing of financial disorder. Revealed are not only forms of governance and oppression enacted on law's margins, but also possibilities for the realization of the progressive politics that lies at the heart of the critical criminological enterprise.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.041 | 0.067 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".