Bibliographic record
Abstract
Purpose Almost 20 years after the Royal Commission on Aboriginal Peoples, indigenous peoples living in Canada continue to pursue their legitimate aspirations for greater control over factors affecting their lives. The purpose of this paper is to summarize two major policies (the Royal Commission on Aboriginal Peoples and the Truth and Reconciliation Commission (TRC)) that aimed to create equity for indigenous peoples’. Design/methodology/approach Commentary and rapid communication to inform and clarify evolving high-priority policy and governance issues related to indigenous peoples’ of Canada. Findings A need exists to create a platform for implementing the TRC actions to protect and promote education, language and culture, justice, youth programming, and professional training and development. Research limitations/implications Innovative intervention research needs to develop solutions to multi-generational disparities in health and well-being for indigenous peoples of Canada and globally. Practical implications Failure to implement longstanding changes to improve indigenous health and well-being will result if a growing burden of premature morbidity and mortality among indigenous population of Peoples’ of Canada, the fastest growing population group with the most challenging health status in Canada. Social implications Indigenous peoples continue to experience profound health vulnerability leading to high health risks, growing health disparities and unequal access to health care services. Originality/value Connecting policy over two decades, for implementation to proceed, sharing of knowledge is essential to formulate innovative approaches, to engage research and build capacity to implement policy actions related to closing educational gaps, to developing culturally appropriate curricula acknowledging and protecting Aboriginal languages, as well as skills-based training in intercultural competency, conflict resolution and respect for human dignity and human rights equality in settings of anti-racism and free of all forms of prejudice and discrimination.
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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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.045 | 0.004 |
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".