The Consortium of Australian Academic Psychiatrists for Independent Policy Research and Analysis (CAPIPRA): Aims, model, outputs, and implications for clinical academic advocacy
Bibliographic record
Abstract
OBJECTIVE: We describe an independent model of clinical academic mental health services research that is able to provide synthesised views for medico-political organisations that are engaged in advocacy for national and state evidence-based policy and planning of mental healthcare. CONCLUSIONS: CAPIPRA focuses on independent research and policy analysis using publicly available datasets on population mental health at national and state/territory levels, published in international and national peer-reviewed journals (>50 papers since 2019). We partner with medico-political organisations in evidence-based advocacy across a wide range of issues.
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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 | 0.566 | 0.506 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.014 | 0.015 |
| Scholarly communication | 0.025 | 0.016 |
| Open science | 0.012 | 0.060 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".