Bibliographic record
Abstract
Vitiligo is a skin condition where pigmentation stops developing, leaving people with white spots on their bodies. Vitiligo is likely caused by gene mutation and is hereditary, but it can happen to anyone. From a medical standpoint, it is a physically harmless condition but it has vast socio-cultural impact. This study was conducted at the Annual World Vitiligo Conference in Detroit, Michigan and on the internet (Instagram and Facebook), through participant-observation at the event, textual analysis of blog posts, and interviews online and in-person, respectively. Through these methods, three discourses emerged: 1) Feeling outcast, 2) Vitiligo as beautiful, and 3) Solidarity. I documented the way cultural assumptions about conditions and disabilities shape the identity of those who have it. These interviews suggest that vitiligo is as much a cultural condition as it is a medical condition. Although more research is needed, people living with vitiligo stated that greater representation of individuals with the condition is needed in the media and pop culture to enlighten the public about vitiligo and improve the day to day interactions of individuals with the condition.
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 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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.038 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".