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Record W272287309 · doi:10.24095/hpcdp.28.4.03

Ethnicity and mental health: Conceptualization, definition and operationalization of ethnicity from a Canadian context

2008· article· en· W272287309 on OpenAlexafffundvenueabout
Diana E. Clarke, Angela Colantonio, Anne E. Rhodes, Michael Escobar

Bibliographic record

VenueChronic diseases in Canada · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsInstitute for Clinical Evaluative SciencesToronto Rehabilitation InstituteSunnybrook Health Science CentreSt. Michael's HospitalWomen's College HospitalUniversity of Toronto
FundersJohns Hopkins Bloomberg School of Public HealthUniversity of TorontoToronto Rehabilitation InstituteOntario Ministry of Health and Long-Term CareJohns Hopkins University
KeywordsConceptualizationOperationalizationCINAHLEthnic groupPsycINFOMedicineMental healthCLARITYContext (archaeology)Health services researchComparabilityMEDLINEPublic healthSociologyPsychiatryNursingPolitical scienceEpistemology

Abstract

fetched live from OpenAlex

The current study provides a critical review of Canadian studies on ethnicity and mental health with respect to the definition, conceptualization and operationalization of ethnicity. It provides a discussion on the methodological issues related to these factors and their implications to guide future research and enable comparability of results across studies. Sociological Abstracts, PsycINFO, MEDLINE and CINAHL were used to identify relevant Canadian articles published between January 1980 and December 2004. The review highlights a number of key issues for future researchers to consider such as the need for: 1) clear rationales as to why ethnicity is important to their outcome of interest; 2) clarity on the definition of ethnicity, which affects its conceptualization and operationalization; 3) a theoretically driven conceptualization of ethnicity, which should be related to the research question of interest; and 4) clear rationales for the decisions made regarding the data source used, the operationalization of ethnicity, and the ethnic categories included in their studies.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.046
GPT teacher head0.318
Teacher spread0.272 · 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 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

Citations22
Published2008
Admission routes4
Has abstractyes

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