A Qualitative Study of Pandemic-Induced Telework: Federal Workers Thrive, Working Parents Struggle
Bibliographic record
Abstract
This study examines the forced transition to telework during the COVID-19 pandemic using qualitative data from two open surveys administered by the Federal News Network in 2020: in the first two months and, then, 10 months into the pandemic. We provide in-depth analysis of 1,969 open-ended comments from 1,589 federal employees collected seven months apart, telling the story of how they continued performing their responsibilities under a full-time telework schedule. Federal employees perceive the transition to full-time telework during the pandemic had a positive effect on organizational performance, work productivity and work-life balance for most federal employees. An exception is working parents, who faced significant hardships due to the pandemic. Additionally, results show pandemic-induced telework was credited with mixed successes for job satisfaction and social integration, and had not been successful in terms of supervisor support and organizational trust, which puts the success of the social contract theory in these situations in jeopardy. Finally, results suggest that federal employees envision more work will become telework-eligible in the new normal and welcome this shift.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.009 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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, 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".