A literature review and annotated bibliography on aspects of Aboriginal child welfare in
Bibliographic record
Abstract
We would like to acknowledge the memory and spirit of our ancestors … especially those who survived the abuses of residential schools; who lived to tell about them and the many Elders of the vast cultures and nations across this country now called Canada, who silently, vigilantly and defiantly kept the threads of our diverse cultures, values and principles alive so that we, this generation and into the next, have something viable to live for, call our own, which continually plays a part in shaping our various identities and nations, complete with strong spirits of resilience and cultural pride and faithful convictions for who we were, where we have been, who we are now and the nations we might become yet again … Despite what our collective ancestors and relatives have experienced, although many have now left mother earth for the spirit world, they have passed unto us, a generational memory of endurance so strong that it will continue to be felt by the next seven generations and beyond … We continue to be proud descendents of collective nations whose spirits cannot be broken in light of the devastating impacts of the colonizing forces of the past, the present and what may be (but we wish not), still a part of our collective futures. Contemporary Acknowledgements: We are not islands unto ourselves, therefore, many thanks are due numerous individuals and organizations that helped make this publication a reality. Thank you to Richard De La Ronde who assisted in the enormous task of grouping the literature by theme areas. This literature
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.023 | 0.049 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".