Bibliographic record
Abstract
The seventh chapter focuses more directly on a third assemblage of these variously integrated powers – biopolitics. Colonial biopolitics generated and worked through categories that located individuals within divisive population groups (Swiffen and Paget 2022). Revealing an imagined normative social hierarchy, colonial criminal accusation assigned individuals to economic, racialized, and gendered population groups that congealed with white, male, possessive relational orderings. A remarkable assembly of Cree leaders perceptively challenged dispossessing colonial law and order in a translated public letter submitted to a local newspaper. Without political processes to manage conflicts between opposing legal fields, lawless violence could quickly descend around accusatory thresholds – as revealed by a case involving the police inspector Dickens (one the famous author’s sons). Through this example we glimpse the struggles by which colonial theatres of criminal accusation tried to assert monopolistic jurisdiction – highlighting how violence and force were the currency of lawless, biopolitical battles to declare law. As is outlined, such powers have left enduring legacies of inequality within criminal justice systems today.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".