Students in Jeopardy: An Agenda for Improving Results in Band-Operated Schools
Bibliographic record
Abstract
The performance of band-operated, on-reserve schools, while much better than the residential schools they replaced, remains very weak in comparison with provincial schools. Among young adults aged 20-24, nine of 10 non-Aboriginals have at least high school, as do eight of 10 Métis and seven of 10 First Nation living off-reserve. In stark contrast, only four in 10 First Nation young adults living on-reserve graduated from high school. The most recent attempt to negotiate major reserve school reform was initiated in 2011 by Shawn Atleo, then National Chief of the Assembly of First Nations (AFN), and Chuck Strahl, then Minister of Indigenous and Northern Affairs (INAC). It culminated in April 2014 with the tabling in Parliament of the First Nations Control of First Nations Education Act (C-33) and the accompanying federal budget promising significantly increased education funding. However, the bill was not enacted. It fell victim to conflicts within the AFN and to adamant partisan opposition in Parliament. While Bill C-33 failed, the crisis in reserve schools remains. In this Commentary, Barry Anderson and John Richards make the case that the core problem in reserve schools is low-quality results on both core academic and culturally relevant subjects, which in turn lead to low high-school completion rates. To address this core problem, they outline, at a broad level, the elements of a reform agenda: a feasible strategy to address national budgeting for reserve schools; an emphasis on outcomes over inputs; affirmation of band responsibilities; regionalization of INAC’s professional capacity; and an emphasis on incremental as opposed to encompassing reforms. Each year sees another cohort of students who have passed through a failing system and another new cohort of students entering the same system. Reconciliation and common sense require that improvements be made – and made quickly.
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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 | 0.094 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.019 | 0.042 |
| Scholarly communication | 0.029 | 0.035 |
| Open science | 0.009 | 0.024 |
| Research integrity | 0.064 | 0.062 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".