Trauma then and now: Implications of adoption reform for First Nations children
Bibliographic record
Abstract
Abstract Currently, Aboriginal children are significantly over‐represented in the out‐of‐home‐care system. Drawing on Aboriginal trauma scholarship and decolonizing methodologies, this paper situates the contemporary state removal of Aboriginal children against the backdrop of historical policies that actively sought to disrupt Aboriginal kinship and communities. The paper draws on submissions to the 2018 Australian Senate Parliamentary Inquiry into Adoption Reform from Aboriginal community controlled organizations and highlights four common themes evident throughout these submissions: (i) the role of intergenerational trauma in high rates of Aboriginal child removal; (ii) the place of children within Aboriginal culture, kinship and identity; (iii) the centrality of the principles of self‐determination and autonomy for Aboriginal communities and (iv) Aboriginal community controlled alternatives to child removal. Acknowledging the failure of both federal and state reforms to address the issues raised in these submissions, the paper reflects on the marginalization of Aboriginal voices and solutions within contemporary efforts to address the multiple crises of the child protection system and the implications for the future of Aboriginal children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.020 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".