Engineering the Skin: Embodied Experiences of Healing from Acne Among YouTube Vloggers
Bibliographic record
Abstract
We examine how 24 adult YouTube vloggers tell their ‘acne stories’ by means of videos posted on YouTube between 2015 and 2020. In doing so, we study the relationship between embodied experiences of acne and health-seeking practices, particularly as they pertain to managing the everyday life of the body, abandoning medical expertise and embracing lay knowledge, living with disability, and engineering an improved self. Overall, we suggest that the vloggers share a general scepticism about the clinical management of their condition, often eschewing medical treatments while advocating for the modification of lifestyle practices. Ultimately, our study shows that vloggers understand healing from acne as both a personal journey that requires individual initiative and a shared pursuit best supported not by doctors and prescription medication but by an online environment that encourages self-engineering through free-market health care options and neoliberal values of working on the body.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| 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".