Bibliographic record
Abstract
There is little information available regarding barriers to return-to-work (RTW) in workers with contact dermatitis. The purpose of this study was to survey occupational health and safety personnel to determine their perceptions regarding RTW barriers for workers with contact dermatitis. The study was conducted during an occupational health and safety research conference attended by stakeholders from labour, management, injured workers, government, safety associations, occupational health and safety practitioners and researchers. The attendees were presented with 3 pictures of varying degrees of work-related hand contact dermatitis and were asked to list the 3 key barriers or challenges in RTW for individuals with contact dermatitis. 21 individuals completed the survey. Issues identified in descending order of frequency were concern of ongoing dermatitis, ability to do the job safely, appearance, ability to accommodate, personal protective equipment, fear that the rash was contagious, workplace attitudes and pain. While some of these issues are potentially common to RTW situations in general, others are more specific to health problems which have a visible manifestation. Increased awareness of and attention to these possible barriers to RTW may lead to better RTW outcomes.
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.005 | 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".