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Record W7098534518

Barbie Meets the Bindi: Discursive Constructions of Health among

2016· article· en· W7098534518 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSlime Mold and Myxomycetes Research
Canadian institutionsnot available
Fundersnot available
KeywordsHeteronormativityDisadvantagedRace (biology)Ethnic groupPopulationInequalitySocial inequalitySocial classSocial constructionism
DOInot available

Abstract

fetched live from OpenAlex

emphasizing passivity, docility and uncleanliness all contribute to cultural (mis)understandings of Canadian women of South-Asian background. Such understandings are a part of dominant racist discourses, including “bodily ” discourses related to health. This paper focuses on the discursive constructions of health among ten young, second-generation South-Asian Canadian women from the Ottawa and Toronto areas. In this qualitative study, feminist postcolonialism and poststructuralism are used as a lens through which we analyse and interpret the transcripts of conversations with these women. The results highlight these young women’s discursive constructions of health and particularly how racialized and gendered notions of ‘looking good ’ constitute a crucial element in their understanding of what it is to be ‘healthy. ’ We discuss and conclude on how these young women locate themselves as un/healthy subjects within larger cultural discourses of traditional (white) femininity, heteronormativity and consumption. While recognition of the heterogeneity of women’s lives is becoming more apparent in the health literature, research examining the social and cultural patterning of health, illness and well-being among women is still insipient (Janzen, 1998). Yet, the life experiences of some groups of women seem to differ markedly from those of others and of the female population as a whole. For instance, class position, race and ethnicity intersect with gender to produce variations in gender inequality and social variability in health status among women (Bolaria & Dickson, 2002). Racial minority women are doubly disadvantaged because they may encounter inequality due to their race in addition to sex discrimination. In brief, while we do not know much about the situation, we note that the social and economic differentiation of women tends to produce subgroup differences in health effects and outcomes (Bolaria &

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.469

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 studies0.0000.000
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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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