Job Attributes and Mental Health: A Comparative Study of Sex Work and Hairstyling
Bibliographic record
Abstract
A growing literature advocates for using a labor perspective to study sex work. According to this approach, sex work involves many of the costs, benefits, and possibilities for exploitation that are common to many jobs. We add to the field with an examination of job attributes and mental health. Our analysis is comparative and uses data from a panel study of people in sex work and hairstyling. We examined job attributes that may differ across these occupations, such as stigma and customer hostility, as well as those that may be more comparable, such as job insecurity, income, and self-employment. Our analysis used mixed-effects regression and included an array of time-varying and time-invariant variables. Our results showed negative associations between mental health and job insecurity and stigma, for both hairstyling and sex work. We also found two occupation-specific relationships: for sex work, limited discretion to make decisions while at work was negatively related to mental health, whereas for hairstyling, mental health was positively associated with self-employment. Our results highlight the usefulness of an inter-occupational labor perspective for understanding the mental health consequences of being in sex work compared to hairstyling.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".