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Record W4282984404 · doi:10.5070/cj86157755

A Bandage on A Broken System: Moving Beyond Peremptory Challenges To Increase Indigenous Juror Representation In Canada

2022· article· en· W4282984404 on OpenAlexaffabout
Kona Keast-O'Donovan

Bibliographic record

VenueUCLA Criminal Justice Law Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicJury Decision Making Processes
Canadian institutionsUniversity of GuelphWestern University
Fundersnot available
KeywordsJuryIndigenousDismissalAcquittalLawJury selectionWhite (mutation)Political scienceGovernment (linguistics)SociologyCriminology

Abstract

fetched live from OpenAlex

In 2016, Colten Boushie, a 22-year-old Indigenous man, was fatally shot by Gerald Stanley, a white farmer. Stanley was later acquitted of second-degree murder and manslaughter by an all-white jury. Peremptory challenges became the major legal focus, with the all-white jury attributed to the defense attorney’s peremptory dismissal of five Indigenous individuals from the final jury panel. Following a raucous public debate, just two months after Stanley’s acquittal, Canada’s Government quickly introduced Bill C-75, eliminating peremptory challenges. While some legal actors view the ban on peremptory challenges as a step toward improving Indigenous juror participation, others argue that this elimination decreases Indigenous representation. As the insular debate endures, it continues to distract from numerous substantial issues with more profound implications on Indigenous juror representation. Through an analysis of the Jury Acts of Ontario, Saskatchewan, and Manitoba, this Article highlights how provincial jury pool selection and summoning policies continue to encourage Indigenous exclusion. For more representative juries, Canada must move past peremptory challenges and acknowledge that sustained efforts made in partnership with Indigenous communities are desperately needed. Examples are offered of structurally-oriented, deeper reform actions to begin the process of addressing root causes of white-washed criminal juries in Canada.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.124
Threshold uncertainty score0.900

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.018
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0390.008
Scholarly communication0.0070.002
Open science0.0050.007
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.069
GPT teacher head0.354
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2022
Admission routes2
Has abstractyes

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