Accountability insights from the devolution of Indigenous child welfare in <scp>M</scp>anitoba
Bibliographic record
Abstract
Abstract This article examines how language and discourse have framed the issue of accountability in Indigenous child welfare devolution in Manitoba. Devolution has been officially presented by the province as a structure and process of collaborative governance – a form of governing that requires horizontal accountability among equal partners. Our examination of the accountability structures and processes reveals that, despite the rhetoric, there is continuing heavy insistence on vertical accountability to the provincial government. At best, the idea of collaborative governance is an illusion; at worst, it has serious negative impacts on Indigenous autonomy and on standards of accountability. Sommaire Cet article examine comment le langage et le discours ont formulé la question de la responsabilisation dans le transfert des responsabilités de la protection de l'enfance autochtone au Manitoba. Le transfert des responsabilités aux autorités locales a été officiellement présenté par la province comme une structure et un processus de gouvernance collaborative – une forme de gouvernance qui exige une responsabilisation horizontale entre partenaires égaux. Notre examen des structures et processus de responsabilisation révèle qu'en dépit de la rhétorique, on continue à insister lourdement sur la responsabilisation verticale envers le gouvernement provincial. Dans le meilleur des cas, l'idée de gouvernance collaborative est une illusion; au pire, elle a de sérieuses répercussions négatives sur l'autonomie des Autochtones et sur les normes de responsabilisation.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.019 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".