Motivation and engagement of public health inspectors: a Canadian perspective for the 21st century
Bibliographic record
Abstract
Organizational leaders are measured on the success of meeting goals and objectives, and their success is greatly dependent on the level of motivation and engagement of their employees. The dynamic climate of the 21st century is forcing a shift in leadership strategies. What may have worked at one time may no longer be as effective with the current workforce. Today’s labour market is dynamic and competitive, and organizational leaders are required to manage, engage, motivate, and retain a multi-generational workforce. This study reviews the literature and uses qualitative and quantitative survey responses to explore (i) the generational breakdown currently influencing the Canadian Public Health Inspection (PHI) workforce; (ii) the impact direct supervisors have on PHI motivation, engagement, and job satisfaction; and (iii) the strategies that PHI leaders can consider to engage their current workforce. The generational breakdown of the PHI workforce generally aligns with the current Canadian labour market. PHI motivation and engagement is influenced more from intrinsic motivators than extrinsic motivators, and managers and supervisors are a significant influencer of PHI motivation and engagement. Consequently, with today’s labour market shifting, public health leaders must rethink their management and leadership strategies for success. In leading the current multi-generational workforce, it is recommended leaders take a more transformational approach to leadership versus a sole focus on the traditional transactional approach.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| 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".