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Record W3216966184 · doi:10.1177/10398562211057069

Is there a missing-middle in Australian mental health care?

2021· article· en· W3216966184 on OpenAlexaff
Jeffrey CL Looi, Steve Kisely, Stephen Allison, Tarun Bastiampillai

Bibliographic record

VenueAustralasian Psychiatry · 2021
Typearticle
Languageen
FieldDecision Sciences
Topicdemographic modeling and climate adaptation
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMental healthGovernment (linguistics)Health carePublic healthMental health serviceLong-term careMental healthcareQualitative researchPsychologyMedicinePublic relationsNursingPolitical sciencePsychiatrySociologySocial science

Abstract

fetched live from OpenAlex

OBJECTIVE: The term 'missing-middle' has been prominent in discourse relating to provision of mental health care in Australia, particularly by proponents of non-governmental youth mental health services such as headspace and related adult services. We investigate whether there is an empirical basis for use of the 'missing-middle' term, founded on qualitative and quantitative research. CONCLUSIONS: Despite the widespread use of the term 'missing-middle' for advocacy in Australia, there is a lack of research characterising the epidemiological characteristics of the group. The validity of advocacy predicated on the basis of the 'missing-middle' care-gap should be reconsidered. Research, such as systematic service mapping and health needs assessment, is a necessary foundation for evidence-based mental healthcare policy, planning and implementation. Without such research, vital government funds may be deployed to 'missing-middle' programmes that may not improve Australian public health outcomes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.097
GPT teacher head0.392
Teacher spread0.295 · 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.

Study designObservational
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

Citations5
Published2021
Admission routes1
Has abstractyes

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