Occupational hazards and population-based prevention strategies for pharmacy workers in Canada
Bibliographic record
Abstract
Pharmacy settings pose various and unpredictable dangers to workers, including biological, chemical, psychosocial hazards. Pharmacy technicians and assistants are a vulnerable and at-risk population. Workers are exposed to unique workplace hazards that impact their physical, mental, and social wellbeing, such as exposure to hazardous medication, violent robberies, and challenges with occupational identity. In this paper, five key areas of hazard are explored: hazardous drug exposure, infections, violence, mental health issues, and social challenges. Each hazard area explored is accompanied with evidence-based recommendations that can be implemented at the population-level to support the wellbeing of pharmacy personnel. Overall, the paper calls for the better protection of pharmacy technicians and assistants from occupational hazards. The population health impact framework is utilized as a guide to create evidence-based recommendations that can benefit whole populations of pharmacy workers at local, provincial, and national scales in Canada, thereby ensuring long-lasting protective interventions that support this vulnerable occupation group. The study concludes by providing future direction for research efforts in this area.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".