“That Colour Won’t Suit Me”: A Qualitative Inquiry of Colourism and Colonialism
Bibliographic record
Abstract
This research is focused on interrogating the social issue of colourism within the South Asian community and particularly grappling with the discrimination and social ideations surrounding darker skin tones. The MRP centers the stories of self-identified South Asian women who have immigrated to or been raised in the settler state of Canada. My research question asks, what are stories of colourism in the lives of South Asian women in Toronto? Findings in this research touch upon concepts of race, colour, class, gender, socio-economic status, and how it relates to colonialist ideologies. Using a narrative approach to inquiry through interviewing, this research is centered in life stories which examine individuals’ lived experiences and is theoretically framed by critical race feminist and post-colonial lenses. The co-creation of this narrative brings forth the voices of silenced South Asian women who have been hurting for generations, challenging the idea that dark skin is not beautiful.
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How this classification was reachedexpand
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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.034 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".