MétaCan
Menu
Back to cohort
Record W2320793092 · doi:10.2753/imh0020-7411400203

Taking Our Place

2011· article· en· W2320793092 on OpenAlexfundno aff
Jenna Bateman, Tina Anderson Smith

Bibliographic record

VenueInternational Journal of Mental Health · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
FundersCanadian Mental Health Association
KeywordsMental healthGovernment (linguistics)CommonwealthPrivate sectorPublic sectorDilemmaPublic administrationPublic relationsService providerBusinessEconomic growthPolitical scienceService (business)MedicineEconomicsMarketingPsychiatryLaw

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.788
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.192
GPT teacher head0.476
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Mental HealthSame topicHealthcare innovation and challengesFrench-language works237,207