Principles of Practice in Mental Health Assessment with Aboriginal Australians
Bibliographic record
Abstract
In this chapter, concepts and history of assessment and testing in the context of Aboriginal and Torres Strait Islander social and emotional wellbeing and mental health are discussed. Importantly, recently revised diagnostic guidelines and the National Practice Standards for the Mental Health Workforce 20131 and their appropriateness for meeting the distinctive needs of Aboriginal people are reviewed. Various assessment tools and measures that have been validated or proved appropriate for use with particular Aboriginal populations, i.e. youth, women and older people, are described. We conclude that practitioners need to be critically reflective in their role in assessment, and position themselves to play an important transformative role in conducting assessment. This extends to acknowledging and enacting culturally responsive principles, procedures and practices to ensure that Aboriginal people have access to effective, culturally secure mental health care.
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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 | 0.173 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.011 | 0.051 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.008 | 0.019 |
| Research integrity | 0.013 | 0.023 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".