Revisiting Representativeness in the Manitoban Criminal Jury
Bibliographic record
Abstract
REPRESENTATIVENESSt has been over twenty years (1991) since the Aboriginal Justice Inquiry of Manitoba (AJI) issued its final report on issues facing Indigenous communities and their involvement with the justice system in Canada.One of the most troubling of its findings was that the jury selection process in Manitoba routinely had problems of inadequate Indigenous representation in the case of Indigenous accused persons.The Canadian jury selection process attempts to select a representative jury.A representative jury is defined as a jury that corresponds to a cross-section of society and the larger or wider community (R v Kokopenace, [2013] ONCA 389).Though the issue of jury representativeness was the basis of a relatively recent appeal in Ontario (R v Kokopenace [2013]), thus far, there is no binding national case law to suggest that an accused can insist that he or she be tried by
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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 | 0.197 | 0.310 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.027 | 0.025 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.006 | 0.013 |
| Research integrity | 0.017 | 0.022 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".