Describing economic benefits and costs of nonstandard work hours: A scoping review
Bibliographic record
Abstract
BACKGROUND: The benefits of nonstandard work hours include increased production time and the number of jobs. While for some sectors, such as emergency services, around-the-clock work is a necessary and critical societal obligation, work outside of traditional daytime schedules has been associated with many occupational safety and health hazards and their associated costs. Thus, organizational- and policy-level decisions on nonstandard work hours can be difficult and are based on several factors including economic evaluation. However, there is a lack of systematic knowledge of economic benefits and costs associated with these schedules. METHODS: We conducted a scoping review of the methodology and data used to examine the economic benefits and costs of nonstandard work hours and related interventions to mitigate risks. RESULTS: Ten studies met all our inclusion criteria. Most studies used aggregation and analysis of national and other large datasets. Costs estimated include health-related expenses, productivity losses, and projections of future loss of earnings. Cost analyses of interventions were provided for an obstructive sleep apnea screening program, implementation of an employer-based educational program, and increased staffing to cover overtime hours. CONCLUSIONS: A paucity of studies assess nonstandard work hours using economic terms. Future studies are needed to expand economic evaluations beyond the employer level to include those at the societal level because impacts of nonstandard work go beyond the workplace and are important for policy analysis and formulation. We pose the opportunity for researchers and employers to share data and resources in the development of more analyses that fill these research gaps.
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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: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.023 | 0.140 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.028 | 0.026 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".