Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate how government employees perceive and react to limits on their right to express public dissent about their employer. Within the context of Canada's federal workplaces, this two‐part project sought first to analyse and clarify the nature of complex government rules on dissent, and then to explore federal employees' understanding of those rules, and the balance between the duty of loyalty owed to their employer, and their protected rights as citizens to criticize their government. The goal was to contribute to further research and improve professional practice within the federal public service in addressing employee dissent. Design/methodology/approach This research is qualitative and exploratory. Documentary and literature analysis was conducted to review Canada's laws, policies and guidelines. These were critically analysed for consistency with each other, and with their stated objectives. Employee views and perceptions were collected through a focus group of communications employees, and three in‐depth interviews. Interviews and focus group results were analysed by inference to explore employee perceptions of their duties and rights, and the authority on which their perceptions are based. Findings Results indicate that respondents base decisions about employee dissent on unconsciously internalized organizational values. Formal policy, training, or legal consequences had less influence on dissent than organizational culture, employee experience, and perceived career and relationship risks. Respondents valued their right to dissent, but were willing to yield it to honour a voluntary moral contract to support a higher cause (public service). The implications are that traditional theories that view employee dissent as largely self‐interested may be less relevant when employees perceive the organization's goals to be value‐driven, and that employee dissent can be minimized by promoting a value‐based organizational culture. Practical implications This paper's findings suggest that organizations might better manage reputation and minimize external employee dissent by focussing on communications that foster a value‐driven organizational culture, rather than by implementing formal limits or policies to control dissent. Originality/value This paper offers policy analysis that fulfills an identified gap in knowledge in terms of general day‐to‐day practise when it comes to advising Canada's federal employees regarding their rights and responsibilities, and offers some challenges to traditional theories that suggest employee choices regarding dissent are primarily based on individual self‐interest or self‐actualization.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".