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Record W4232069536 · doi:10.32920/ryerson.14664144

Skin colour dissatisfaction in South Asian-Canadian women

2021· preprint· en· W4232069536 on OpenAlexaffabout
Shaila Kumbhare

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicColor perception and design
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBeautySkin colourNarrativeColonialismGender studiesSkin colorSouth asiaQualitative researchPsychologyRace (biology)White (mutation)FeminismAsian americansSociologyEthnic groupArtGeographyMedicineAestheticsAnthropologyDermatology

Abstract

fetched live from OpenAlex

The intent of this qualitative research study is to highlight the experiences of second-generation South Asian-Canadians with skin colour dissatisfaction and shadeism. Using a narrative approach of inquiry interviews were conducted with 2 South Asian-Canadian women to better understand the effects of colonial beauty standards and whiteness on their satisfaction with the colour of their skin. Findings were that participants felt very negatively toward their skin and often felt inferior to white women. They disclose that skin dissatisfaction has a discernible impact on their everyday lives and decisions. Data analysis draws critical race feminism and post-colonial theory. Keywords: South Asian, Canadian, women, skin-colour, shadeism, colourism, beauty, colonization, self-esteem, whiteness

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.076
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0160.006
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.034
GPT teacher head0.312
Teacher spread0.278 · 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 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
Published2021
Admission routes2
Has abstractyes

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