The Challenge for Cause Procedure in Canadian Criminal Law
Bibliographic record
Abstract
There is a longstanding presumption in Canadian law that jurors will act impartially in carrying out their duties, but this presumption may be challenged when the defendant is a member of a racialized minority group. In those circumstances, the defence may initiate a challenge for cause procedure, wherein potential jurors are questioned about their ability to set aside any racial prejudice and judge the case solely on the evidence. Although the challenge for cause procedure has been in place for some time, little attention has been given to the process and whether it in fact effectively screens for juror bias. This article provides an overview of the challenge for cause procedure, with particular attention to race-based challenges, as well as psychological research assessing the effectiveness of the procedure. Reference is made to the authors’ analysis of actual jury selection proceedings in which the challenge procedure was invoked. The data revealed that, although only a small percentage of potential jurors admitted to potential prejudice in open court, many more were excluded by triers and counsel. En el derecho canadiense existe la presunción antigua de que los jurados actúan de forma imparcial al desarrollar sus funciones. Sin embargo, esta presunción se puede cuestionar cuando el acusado pertenece a una minoría racial. En esas circunstancias, la defensa puede iniciar un procedimiento de impugnación del jurado en el que se interroga a los potenciales miembros del jurado sobre su capacidad para dejar de lado cualquier prejuicio racial y basarse únicamente en evidencias para juzgar el caso. A pesar de que la impugnación del jurado es un tema que ha estado de actualidad durante algún tiempo, se ha prestado poca atención al proceso y si realmente se detectan de forma efectiva sesgos dentro del jurado. Este artículo proporciona una visión general del procedimiento de impugnación del jurado, prestando especial atención a las impugnaciones basadas en la raza, así como de la investigación psicológica para evaluar la eficacia del procedimiento. Se hace referencia al análisis de las autoras de los procesos de selección del jurado en los que se invocó la impugnación del jurado. Los datos revelaron que, aunque sólo un pequeño porcentaje de los posibles miembros de jurado admitieron un prejuicio potencial de forma pública, jueces y abogados excluyeron a muchos más. DOWNLOAD THIS PAPER FROM SSRN: http://ssrn.com/abstract=2756034
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 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 | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.026 | 0.017 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".