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Record W2581003054 · doi:10.20381/ruor-18292

Fusion, confusion, or illusion: Discursive constructions of health and fitness among second-generation South Asian Canadian women

2004· article· en· W2581003054 on OpenAlexaboutno aff
Tammy George

Bibliographic record

VenueuO Research (University of Ottawa) · 2004
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsnot available
Fundersnot available
KeywordsConfusionGender studiesSociologyIllusionPolitical scienceSocial psychologyPsychology

Abstract

fetched live from OpenAlex

Stereotypes emphasizing passivity, docility, and uncleanliness all contribute to cultural (mis)understandings of Canadian women of South Asian background. Such understandings feed dominant racist discourses, including "bodily" discourses related to fitness and health. In turn, such discourses have "effects" in terms of how women approach bodily practices. This study focuses on the constructions of health and fitness among ten 20--25 year old second generation South-Asian Canadian women who now reside in Ottawa or Toronto. Based on conversations with these women, the study focuses on how they construct health and fitness as well as the types of institutional and cultural discourses they draw from. Results show how these women struggle to construct an identity that speaks to their experience of being South Asian Canadian in that they often unsettle, contest, negotiate and resist normative constructions of both "South Asian" and "Canadian" identities. Results also highlight the impact of these negotiations on the young women's constructions of health, and on their position as un/fit and un/healthy subjects within cultural discourses. Insights from this study fill an important gap in the Canadian literature on health and fitness as well as inform contemporary debates regarding health policy and health education programs for South-Asian Canadian women.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.496

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0340.031
Scholarly communication0.0090.002
Open science0.0020.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.104
GPT teacher head0.398
Teacher spread0.294 · 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 designQualitative
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

Citations2
Published2004
Admission routes1
Has abstractyes

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