MétaCan
Menu
← Back to cohort
Record W7095719892

Immigrant Refugee

2010· article· en· W7095719892 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeImmigrationIncidence (geometry)Cancer incidenceMajestyCancer
DOInot available

Abstract

fetched live from OpenAlex

Her Majesty the Queen in Rights of Canada 2010 Abstract Canadian immigrants have lower overall cancer risk than the Canadian-born population. Less is known about risks for immigrant subgroups and site-specific cancers. Linked administrative data sets were used to compare cancer incidence between subgroups of immi-grants to Canada and the general Canadian population. The study involved 128,962 refugees and 241,010 non-refu-gees. Standardized incidence ratios (SIRs) were calculated for all-site and site-specific cancers by immigration categories and regions of birth. Relative to the general Canadian population, incidence of all-site cancer was lower among immigrants overall, by sex and refugee status (non-refugee SIRs 0.25: men, 0.24: women; refugee SIRs 0.31: both). Significantly higher SIRs resulted for liver,

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score0.201

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0020.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0600.004

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 head0.016
GPT teacher head0.335
Teacher spread0.319 · 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.

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
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicMigration, Health and Trauma→French-language works237,207→