THE COMMITMENT GAP: LESSONS LEARNED ABOUT EMPLOYEE COMMITMENT IN THE PARKS CANADA AGENCY
Bibliographic record
Abstract
Understanding how committed employees are within an organization is a valuable tool for managing and fostering a successful work environment. A continued appreciation of employee commitment is especially beneficial following organizational change as it has been shown that change inevitably impacts commitment levels to some degree. This study investigated organizational commitment within a subpopulation of the newly restructured Parks Canada Agency using an established survey instrument. The results of this study were based upon a 62.6 % response rate from a population of 300 employees in the Ontario region. The findings revealed that an employee’s tenure and work location influences commitment levels among the sample that was surveyed. This study also found that a commitment gap exists between the expressed commitment to the current state of the organization and commitment toward the mandate. An effort to improve the moderate levels of organizational commitment would reduce the commitment gap and enhance the employer-employee relationship. Six lessons for maintaining employee commitment within a protected area organization are learned from the Parks Canada experience and their adoption would contribute to the positive effects of the organizational change.
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| 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".