The Perceived Job Performance of Child Welfare Workers During the COVID-19 Pandemic
Bibliographic record
Abstract
While the evidence on the adverse impact of the COVID-19 pandemic on the well-being of frontline social workers is emerging, the research on the impact of the pandemic on their performance is scarce. The presented study explores how the relationship between work environment predictors and perceived stress explains the job performance of child welfare social workers during the pandemic using survey responses of 878 child welfare social workers. The findings revealed the mechanism through which environment predictors and perceived stress interacted in explaining job performance during a time of large-scale crisis. We found that C.W. social workers who experienced greater COVID-19-related service restrictions reported poorer job performance, that perceived stress disrupted workers' supervision and autonomy, and that supervision and job autonomy protected C.W. social workers from the adverse effects of perceived stress and workload on their job performance. Conclusions included the importance of autonomy and supervision in mitigating job-related stressors and the need to adapt and enhance child welfare supervision during times of national crisis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".