Ode’imin (Heart Berries): the experience of Indigenous academics in social work programs : engaging Indigenous identity and experience
Bibliographic record
Abstract
[Para. 1 of Introduction] "Encourage people to learn their own indigeneity, whatever that is. And to be encouraged to go into that. That's part of their healing journey. And that is their responsibility in doing social work because they're doing that for their identity, for their space…" (Stacy). Social work has had a tenuous relationship with Indigenous peoples in Canada. Looking at various periods historically and currently, social work has positioned itself as an alleged ally of Indigenous peoples and yet it is a perpetrator of the horrific conditions and strife that Indigenous peoples face. Issues like cultural erosion, the breakup of families and language loss are all traced in part to residential Schools, 60's scoop and the millennial scoop- which social workers have and continue to play a role in executing (Alston-O’Connor, 2010). On one hand, the Canadian Association of Social Workers (CASW) has prioritized "developing stronger connections with Indigenous social workers and communities to better support their issues and pursue shared advocacy goals" (CASW Reconciliation Hub, n.d.). However, Indigenous children continue to be overrepresented in child welfare institutions (Ontario Human Rights Commission, 2018).
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.035 | 0.012 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".