DUAL PERSPECTIVES ON BETTER TELEWORKING IN THE PUBLIC SECTOR: A MIXED METHODS APPROACH
Bibliographic record
Abstract
This research followed a sequential mixed-methods approach, including an analysis of Twitter data to gauge employee and employer perspectives on teleworking, a review of contemporary Canadian public administration perspectives on managing teleworking in the COVID era to capture employer’s perspective, a web-deployed survey of Canadian public servants, and interviews with public servants to probe these perspectives more deeply. The research is aimed at understanding employee and employer perspectives of teleworking. Founded on an alignment of socio-technical theory (Trist, 1993), bounded rationality theory (Simon, 1957), and the Theory of Planned Behavior (Ajzen, 1991), these theoretical frameworks serve as the basis for developing a theoretical framework that considers the benefits and drawbacks of teleworking, the factors that contribute to better teleworking arrangements, and potential government policy initiatives that can address the barriers to and opportunities for teleworking success in the Canadian public sector.
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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 | 0.115 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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, 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".