Ethnic Ancestry, Culture, Identity, and Health: Using Ethnic Origin Data from the 2001 Canadian Census
Bibliographic record
Abstract
ABSTRACT/RESUME This analytic paper explores the use of ethnic origin census data in policy- and practice-relevant health research. It begins with a definition of key terms, outlines the importance of ethnicity and health research, and provides a summary overview of the existing research literature. This is followed by a review of the changing formulation and format of the ethnic origin question itself through time, and a consideration of the implications thereof for data usage. The paper next examines the use of ethnic origin data in health research, considers data linkages with various health status indicators, and explores linkages with other health-related surveys; it also outlines the use of ethnic origin information in health policy development, programme planning, and service delivery. The discussion then turns to an identification of core issues, the provision of concrete suggestions for addressing the conceptual and methodological challenges identified, and the presentation of key recommendations for future directions. Ce document analytique scrute l'utilisation des donnees sur l'origine ethnique tirees du recensement de 2001 dans la recherche en sante pertinente sur le plan des politiques et des pratiques. L'auteure definit d'abord les termes cles, souligne l'importance de l'appartenance ethnique et de la recherche en sante pour la societe canadienne, et fait un survol des recherches dans le domaine. L'auteure examine ensuite brievement la formulation de la question sur l'origine ethnique, ainsi que son format et sa transformation au fil du temps, et elle se penche sur l'incidence de ces facteurs pour I'utilisation des donnees. Le document traite par la suite de l'utilisation des donnees dans la recherche sur la sante, aborde la question du couplage des donnees avec divers indicateurs de sante, et examine les liens avec d'autres sondages lies a la sante; il explique egalement l'utilisation des renseignements sur l'origine ethnique dans la recherche sur la sante, l'elaboration des politiques, la planification des programmes et la prestation de services. Le document cerne ensuite les enjeux fondamentaux et fournit plusieurs suggestions concretes pour resoudre les problemes conceptuels et methodologiques mentionnes ainsi que quelques recommandations cles pour les orientations futures. INTRODUCTION Research in the area of ethnicity and health is of growing strategic importance given Canada's rapidly increasing ethno-cultural diversity. Over the past four decades, Canada has undergone a fundamental demographic shift attributable largely to changing immigration trends. Since 1901 it has welcomed 13.4 million new immigrants, a number equivalent to 45% of its current population. In both the 1960s and 1970s, 1.4 million new immigrants arrived, with an additional 1.3 million newcomers admitted in the 1980s; this increased to 2.2 million immigrants between 1991 and 2000. According to Statistics Canada, flows this high have not been seen since the beginning of the century (2003:6). Between 230,000 and 250,000 immigrants and refugees currently arrive in Canada each year. In 1957, the top ten immigrant source countries were all European; four decades later eight of the top ten were non-European (Kessel 1998) reflecting a major change in primary sending countries. Whereas prior to 1961, European borns made up 90% of all immigrants coming to Canada, between 1981 and 1991 they constituted only 25% of new immigrants (Badets 1993). In 1996 the top three regions of origin were Asia and the Pacific (51%), Europe and the United Kingdom (21%), followed by Africa and the Middle East (18%). Approximately 15% of new immigrants came from India, Pakistan, and Sri Lanka (Citizenship and Immigration Canada 1999), and 30% were from China, Korea, Taiwan, Hong Kong, and the Philippines. The more recent census indicates that 58% who arrived between 1991 and 2001 came from Asia (including the Middle East), 20% from Europe, 11% from the Caribbean and Central and South America, 8% from Africa, and 3% from the United States. …
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this metaresearch. It is in the settled core of the field.
Analytic paper on the use of Canadian census ethnic origin data in health research: how the question is formulated, the conceptual and methodological challenges for data usage, and recommendations for future research.
It examines the definition, linkage, and methodological use of ethnicity data in health research.
Analyzes methods and uses of Canadian ethnic-origin census data as inputs to health research.
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".