Policing during a global health pandemic: Exploring the stress and well-being of police and their families
Bibliographic record
Abstract
Law enforcement personnel attend critical incidents that are typically short-lived and geographically confined. However, the recent global health pandemic potentially impacts on every officer, every shift, throughout the world. This research is one of the first survey studies of stress and mental health impacts of COVID-19 on United States police and their families. The study found that the pandemic has created additional stress for police and their families, elevating stress levels in an already highly stressed population. For police officers, sources of stress were predominately associated with the fear of infecting their families and the enforcement of restrictions. The stress created by the pandemic exceeds that of other commonly experienced critical incidents in policing. The current findings indicate that police and their families expect to experience longer-term, harmful mental health impacts. This research provides important insights for police agencies, as well as those who work to support and improve the well-being of police. The pandemic is impacting now on the current stress levels of police and is likely to create a legacy that must be managed into the future.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".