A Framework for Indigenous Adoptee Reconnection: Reclaiming Language and Identity.
Bibliographic record
Abstract
Canadian society is ascribing increasing importance to the large numbers of Indigenous children who have – and continue to live – in the child welfare system. An unexplored aspect of this phenomenon is how such children rebuild their Indigenous identities once they become adults and are no longer in care. Recent estimates suggest up to 20,000 First Nations, Metis, and Inuit children were removed from their families during what was known as the Sixties Scoop (Sixties Scoop Survivors, 2015). The Sixties Scoop is part of Canada’s colonial story in which the prevalent assimilative force has been disconnecting Indigenous children from their families and understandings of the world. To date, there is little research on how transracially adopted Indigenous adults reconnect with their Indigeneity. Identity reclamation is a personal and intimate process. I begin by summarizing the scholarly literature on the Sixties Scoop, and describe a proposed theoretical framework of Indigenous adoptee identity reclamation emerging from my reflexive process in writing a critical personal narrative. I emphasize the importance of shifting from ‘othering’ hegemonic discourses to a spirit-based discourse of healing and wholeness. Finally, I engage in a broader dialogue on decolonizing education from Indigenous perspectives.
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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 | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.021 | 0.106 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.005 | 0.008 |
| 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".