Social work's colonial past with Indigenous children and communities in Australia and Canada: A cross‐national comparison
Bibliographic record
Abstract
Abstract This article offers a cross‐national comparison of social work in two countries, Australia and Canada, about the care of Indigenous children within the context of colonization and the evolving profession. The discussion is based on data from two empirical studies that examined professional discourse relating to the removal of Indigenous children from their families and Indigenous peoples more broadly within key historical time frames. The studies involved a content analysis of the flagship journals of the Australian and Canadian professional associations. It is argued that a critical interrogation of professional discourse within these historical and national particularities provides insights that can inform a broader understanding of how practices and constructions of social work are shaped within contemporary practice contexts. The studies revealed that very little attention was paid to problematizing colonial policies and practices, including the state‐sanctioned forcible removal of countless Indigenous children from their biological families, while the professions in both countries were complicit in the oppressive treatment of Indigenous peoples that have left a legacy of intergenerational trauma. The findings suggest a way of understanding social work as a discipline beyond the historical specificities of the two countries that has relevance to social work across the globe.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.032 | 0.015 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".