Mental Health of Employees at a Canadian Animal Welfare Organization
Bibliographic record
Abstract
Abstract Despite numerous benefits, a dark side exists in human and veterinary caregiving professions that can negatively impact caregiver mental health. It was postulated that other nonhuman animal caregivers, animal welfare employees, might experience mental health outcomes similar to those in analogous caregiving occupations. This study investigated employee mental health at a Canadian animal welfare organization using five validated mental health instruments: Perceived Stress Scale (stress), Hospital Anxiety and Depression Scale (anxiety and depression), Professional Quality of Life Scale (compassion satisfaction and compassion fatigue), Maslach Burnout Inventory Scale (burnout), and Connor-Davidson Resilience Scale (resilience). Front-line and support staff tended to have poorer mental health outcomes relative to the study population mean, potential for burnout was a notable concern, and resilience was below normal for most employees. These results shed light on the mental health of an animal caregiving occupation that has largely been ignored. Strategies for building employee resilience are discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".