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Record W7097934951

National Symposium on Immigrant Health in Canada An

2004· article· en· W7097934951 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationCensusEthnic groupPopulationHealth careNew immigrants
DOInot available

Abstract

fetched live from OpenAlex

Ethnicity and migration are recognized as factors that determine health due to biolog-ical, cultural, social, and lifestyle factors.1-3 The most recent census results show thatthe ethnocultural profile of Canada is increasingly diverse. In 2001, approximately 5.4 million Canadians, or 18.4 % of the total population, were born outside of the country, an increase from 17.4 % in 1996. This proportion is higher than most other countries worldwide, with the exception of Australia where, in 2001, about 22 % of the total popula-tion was foreign-born. In the United States, immigrants represent about 11 % of the total population.4 Immigrants represent a very diverse population in terms of ethnicity, cultural and sociodemographic characteristics. Immigrants to Canada come from all parts of the world, although a large proportion of more recent immigrants come from Asia and the Middle East in the last decade (58 % in 1991-2001).4,5 Knowledge of the unique patterns of health and health care needs of immigrants is cur-rently somewhat limited in Canada. Considering the very diverse ethnocultural profile of the Canadian population, as well as the size of the immigrant population, national consen-sus is needed on current knowledge and research priorities with respect to determinants of health, health status, and health services utilization among immigrants in Canada. These efforts would help develop more targeted policies and programs aimed at reducing existing health disparities. In light of this need, a National Symposium on Immigrant Health was

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.185
Threshold uncertainty score0.372

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0110.002
Scholarly communication0.0040.001
Open science0.0020.005
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0230.003

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 head0.021
GPT teacher head0.323
Teacher spread0.302 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2004
Admission routes1
Has abstractyes

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