When One Innocent Suffers: Phillip James Tallio and Wrongful Convictions of Indigenous Youth
Bibliographic record
Abstract
This paper examines the causes - sociological, psychological, and legal - for the wrongful conviction of Indigenous persons, and in particular, Indigenous youth, in Canada. The paper includes an overview of research on causes of wrongful conviction, as well as background on the systemic over-incarceration of Indigenous persons in Canada. The paper also includes recommendations on reducing wrongful conviction risk factors, including, inter alia, false confessions, plea bargaining, bias and tunnel vision by police and other state actors, the overlap between the child welfare and criminal justice systems, the prevalence of mental illness and disabilities in the criminal justice system, the legacy of Residential Schools and ongoing marginalization of Indigenous persons, and the evolving philosophy of youth criminal justice. The experience of one Indigenous youth, Phillip James Tallio, is situated against this backdrop.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.036 | 0.021 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".