Remote Work in Early Career: Examining the Federal Public Service
Bibliographic record
Abstract
The COVID-19 pandemic disrupted how Canada’s federal public service worked in a significant manner. In March 2020, hundreds of thousands of public servants transitioned to remote work in the National Capital Region and across the country in a matter of days. This thesis explores the effect that this transition had on individual well-being, worker stress, and organizational outcomes with a small sample in the federal public service. Using semi-structured interviews, it examines the responses of fifteen early career public servants (n=15) to questions about changing job demands and resources, social and technical aspects of work, and preferences on the future of work. It interprets these findings in the context of Bakker and Demerouti’s Job-Demands Resources Model (2006), Emery and Trist’s (1960) socio-technical system of job design, and Simon’s (1990) concept of bounded rationality. This work found that work-life balance, focus, connection, rewards, and safety/well-being were job resources that workers could use in a remote format, while technology, environment, role clarity/mentorship, work hours, and overwork were job demands. The technical aspect of work productivity improved while no consensus formed for performance, and the social aspect of work support declined, while no consensus formed for career progression. The findings revealed that in aggregate the technical aspects of work improved, and the social aspects declined. Public servants’ preferences on the future of work were evenly split between continuing remote work indefinitely or transitioning to a hybrid model, with only one interviewee expressing a preference for fully in-person work. Therefore, this thesis found that hybrid work policies should be designed to capitalize on the advantages and limit the downsides of remote work, that the federal public service should not immediately attempt to return to completely mandatory in-person work, and that the limitations of hybrid work should be recognized. In this context, this research provides preliminary insight into the field of remote work.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".