A CROSS-GENERATIONAL PERSPECTIVE OF WORKERS’ EXPECTATIONS IN THE CANADIAN PUBLIC SERVICE SECTOR
Bibliographic record
Abstract
The public service sector is faced with sharp demographic shifts which have an effect on employees' perspectives on job satisfaction.Relationships between workers belonging to different age groups are perceived as uneasy, especially since the "mentoring" approach, aimed at bridging the gap between younger and older staff, yielded mixed results.This problem is compounded by gender related differential expectations regarding work.The aim of this research was to study the individual and combined effects of gender and age on work-related expectations and overall job satisfaction.The sample included 182 165 public service employees from various government agencies representing approximately 70% of the entire canadian federal work force.Data was collected using the PSES (Public Service Employee Survey), a questionnaire measuring a variety of constructs such as job satisfaction, social support, stress, harassment, fairness, social climate, demands, control and so forth.The sample took part in the study in 2009 and 2014.Participants were included in a 3 X 2 factorial design (age groups X gender) with various indicators of work perception used as dependent variables.MANOVAs and ANOVAs were computed and significant effects were decomposed using Scheffé post hoc tests.A significant multivariate effect of the factors was found [F(multi) = 16.56 ; p. <.0001].Subsequent univariate and post hoc tests indicated that expectancies gradually shift from being centered on task related variables to more social and interactive variables from the younger age group to the older.No significant interaction effects with gender were observed.Implications of these results on the career outlook of public service employees are discussed.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".