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Record W6958911193 · doi:10.71910/supsi.9951

Psychiatric Disorder in Later Life: A Canadian Perspective

2010· other· en· W6958911193 on OpenAlexaboutno aff

Bibliographic record

VenueSUPSI ARIS · 2010
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthPerspective (graphical)Criminal justiceMental health lawPopulationEconomic Justice

Abstract

fetched live from OpenAlex

Canada has long been recognized as a leader in the field of psychiatric epidemiology, the study of the factors affecting mental health in populations. However, there has never been a book dedicated to the study of mental disorder at a population level in Canada. This collection of essays by leading scholars in the discipline uses data from the country's first national survey of mental disorder, the Canadian Community Health Survey of 2005, to fill that gap: Mental disorder in Canada explores the history of psychiatric epidemiology, evaluates methodological issues, and analyses the prevalence of several significant mental disorders in the population. The collection also includes essays on stigma, mental disorder and the criminal justice system, and mental health among women, children, workers, and other demographic groups. Focusing on Canadian scholarship, yet wide-reaching in scope. Mental disorder in Canada is an important contribution to the dissemination and advancement of knowledge on psychiatric epidemiology. (PsycINFO Database Record (c) 2019 APA, all rights reserved)

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.112
Threshold uncertainty score0.814

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.010
Science and technology studies0.0120.006
Scholarly communication0.0060.003
Open science0.0020.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0070.000

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 head0.004
GPT teacher head0.215
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2010
Admission routes1
Has abstractyes

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Same venueSUPSI ARISSame topicGenetic diversity and population structureFrench-language works237,207