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Record W2158294219 · doi:10.7870/cjcmh-2013-003

Creating Comprehensive Children's Mental Health Indicators for British Columbia

2013· article· en· W2158294219 on OpenAlex
Charlotte Waddell, Cody A. Shepherd, Alice Chen, Michael H. Boyle

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2013
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsMcMaster UniversitySimon Fraser University
Fundersnot available
KeywordsMental healthUnderpinningSample (material)Public healthEnvironmental healthHealth indicatorPopulation healthPopulationPsychologyMedicineEngineeringNursingPsychiatry

Abstract

fetched live from OpenAlex

Canada urgently requires a population health approach to children's mental health—promoting health and preventing disorders, in addition to providing treatment. Underpinning this approach, indicators could enable population monitoring, thereby informing ongoing public investments. To investigate potential indicators for British Columbia, we developed a comprehensive population health framework, established selection guidelines, reviewed data sources, and identified sample indicators. While 15 survey and administrative sources yielded 90 indicators, there were significant imbalances in coverage of the framework. To create truly comprehensive children's mental health indicators, we therefore recommend collecting new data, enhancing existing data sources, and evaluating existing programs.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.634
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0120.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.039
GPT teacher head0.361
Teacher spread0.322 · 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