Bibliographic record
Abstract
The Mental Health Coordinating Council (MHCC) welcomes the opportunity to contribute to this special edition on the Australian mental health service system. This paper discusses the experiences of the non-government community-managed mental health sector. The mental health sector in Australia consists of a complex and increasingly fragmented mix of public/government, private for-profit and not-for-profit non-government community-managed organization (NGO/CMO) service providers with multiple layers of commonwealth and state/territory government policy, planning, and funding levers. The development of the community-managed mental health sector in Australia has been defined by both organic and government funded strategic growth at different points in its history. Despite strong evidence for the effectiveness of recovery-oriented approaches and the clear role of the community sector in promoting and applying the recovery principles and supporting social inclusion for mental health consumers and carers, the dilemma for the sector in the large majority of the eight Australian states and territories lies in its struggle to fully take its place as an integral and contributing part of the mental health system in its own right.
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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.018 | 0.014 |
| Open science | 0.003 | 0.027 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.223 | 0.126 |
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".