It's the colour of my skin: race and beauty discourse with Fenty beauty captions and user comments on Instagram
Bibliographic record
Abstract
People of colour have long endured a lack of makeup products formulated for melanated skin. In 2017, Fenty Beauty released 40 shades of its foundation and concealer products and expanded its selection in 2019 to match 50 distinct skin tones. These events inspired a new industry standard, labelled “The Fenty Effect”, that prompted other makeup brands to practice greater inclusivity toward darker skin tones. This Major Research Paper (MRP) uses a narrative approach to examine discourses around race and beauty. With a theoretical perspective on power and hegemony, it interprets the intersections of representation, colourism, identity, consumption, and counterpublics through an analysis of Fenty Beauty captions and user comments on Instagram. The results of this study provide preliminary knowledge toward a larger investigation on the shift in racial representations in the beauty industry. Keywords: race; representation; colourism; beauty; social media; identity; consumption
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".