Characterization of Chemical Exposures in Hairdressing Salons
Bibliographic record
Abstract
Workers in hairdressing salons are exposed to several hundred chemicals, of which a few are possibly detrimental to pregnant workers or their fetuses. In Quebec, a government program provides protective reassignment for exposed pregnant workers. This study was set up to assist public health physicians by describing the exposure levels for ingredients that were measurable (i.e., airborne), selected from a list of possibly detrimental hairdressing ingredients. Twenty-six salons were sampled in Montreal, Canada, between June 1996 and December 1997. At the time of sampling, information on certain work conditions (e.g., chemical services offered, number of clients, average CO(2) level during the day) was also noted. Fifty percent of the salons provided additional services other than hairdressing, such as manicures, pedicures, or beauty treatments. Almost half of the salons were quite small, with less than 5 employees. Average temperature ranged between 17 and 26 degrees C, relative humidity between 18 and 59 percent and average CO(2) concentrations from 583 to 4301 mg/m(3). Duration of samples varied between 15 minutes and 8 hours. The most prevalent chemicals were alcohols: ethanol, at an average personal concentration of 39.9 mg/m(3), and isopropanol at an average personal concentration of 3.1 mg/m(3). Acetone, toluene, and acetates, all related to manicure services, were also measured in small quantities. An empirical mathematical model brought in evidence that CO(2) levels explained 46 percent of variation in the concentration of ethanol; when number of permanent waves done during the day and relative humidity and temperature were added, the resulting model explained 68 percent of the variations in ethanol. Thus, although the measured concentrations of chemicals were fairly low in this study, it appears possible that on very busy days, especially if other chemical services are performed in the salon, the total mixture of airborne chemicals could reach significant concentrations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".