Bibliographic record
Abstract
In Lynn M. Thomas’s Beneath the Surface: A Transnational History of Skin Lighteners, South Africa (and the African continent in general) is a case study for understanding the historical consumption of skin lighteners and the transnational consumer economy that was engendered via local media industries and the pharmaceutical and manufacturing sectors. The book unpacks the questions: Why would people want to alter the color of their skin, and why would they endure harmful health effects to do so? As an outgrowth of global US-American capitalism, skin lighteners have been and remain big business. Sales for skin lightening products are expected to reach over $31 billion USD by 2024. While these products are sold in the Americas, Asia, Europe, and the Middle East, the book focuses on South Africa because, as Thomas explains, the United States’ historical capitalist investment in the country was unparalleled compared to other regions through ventures such as the skin lightener company Ambi, a brand that arrived in southern Africa in 1963. The United States not only exported skin lightening products but also, according to this book’s thesis, influenced the advertising, celebrity culture, and product development that featured heavily in South African newspapers and photo magazines.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".