Kookum Knew ... Exploring Historical Contexts: Aboriginal People, the Justice System, and Child Welfare
Bibliographic record
Abstract
This paper concerns the inclusion of a “Gladue Report” in Aboriginal child welfare cases in Canada. A Gladue Report is named after a criminal trial in Nanaimo, Vancouver Island, British Columbia, involving a Cree/Métis woman, Jamie Gladue. During the trial, the defence referred the court to Section 718.2(e) of the Criminal Code that allows a judge to take into consideration the historical context pertaining to an accused Aboriginal person. This section was added to the Code in 1996 in response to the gross overrepresentation, as a percentage of the Canadian population, of Aboriginal people in the justice system. Using this section as an additional tool of analysis, the judge and the court can consider the unique experiences, context, and circumstances of the Aboriginal person’s life, factors that may have played a role in bringing this person before the court. Providing valuable historical context in the life of a child, family or community, the Gladue Report is quickly evolving into an important assessment tool in criminal sentencing, as well as in child welfare cases. Often, the wisdom keepers – the grandmothers and grandfathers in a community – keep these historical memories and stories. They are proving invaluable in supplying insight, information, and understanding, not only in court cases, but in relating the story of the broader dynamic of human interaction and discourse that has clashed and thundered on this land for the past 300 years.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.031 | 0.011 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".