The 2024-2025 Commonwealth Budget for Mental Health: Funding unproven initiatives and stings in the tail
Bibliographic record
Abstract
We discuss the ramifications of the Commonwealth of Australia Budget allocations for mental healthcare for 2024-2025. There is funding for population-based mental health initiatives for milder anxiety and depression but no direct funding of services for the most severe and disabling forms of mental illness, other than pre-existing state/territory disbursements from the Commonwealth for state-based health services. There are substantial concerns that the Commonwealth funding has potentially been misallocated to ineffective interventions that are unlikely to reduce the population prevalence of mild anxiety and depression in Australia. Funds may have been better allocated to provide effective care for those with the most severe and disabling illnesses including schizophrenia, bipolar disorder and severe depression.
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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 | 0.012 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.022 | 0.029 |
| Insufficient payload (model declined to judge) | 0.020 | 0.014 |
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".