The Determinants of Flexibility and Innovation in the Government Workplace: Recent Evidence from Canada
Bibliographic record
Abstract
This article analyzes the adoption of flexible work design and employee involvement practices in Canadian government workplaces. It uses information from a representative survey of government middle managers. The survey, which was specially designed for the government sector, was carried out in five Canadian jurisdictions. A high incidence of both flexible work design and employee involvement practices, much higher than in the Canadian private‐sector, was found in government workplaces. The most significant correlation between the two sets of practices is perceived public pressure for more better‐quality services and for increased employee involvement in the design and implementation of these services. Budget constraints are important in explaining the adoption and spread of employee involvement techniques. There is also a strong positive association between the adoption of flexible work practices and the extent of managerial autonomy. Various supporting human resource management practices are also complementary to the successful adoption of flexible work practices in Canadian government workplaces. However, the characteristics of the work, the work unit, and the workforce have a rather limited effect on the adoption of these practices. Our findings indicate that there might be differences in the determinants of the adoption of flexible workplace practices in government and private‐sectors, pointing to possible institutional forces at work in government workplaces.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".