Satisfaction with work and person–environment fit: are there intergenerational differences? An examination through person–job, person–group and person–supervisor fit
Bibliographic record
Abstract
Purpose Through three dimensions of person–environment (PE) fit, namely person–job (PJ) fit, person–group (PG) fit and person–supervisor (PS) fit, this paper examines generational differences on which dimension is more important to explain Baby Boomers', Generation X's and Generation Y's satisfaction with work. Design/methodology/approach Gathered from a sample of 1,065 employees in the province of Québec, Canada, data were analyzed through one-way ANOVA and structural equation modeling. Findings The findings suggest that Generation X scored lower on satisfaction with work, that there is a difference in the level of PG fit and PS fit between the generations, and that PJ fit explains satisfaction with work for all generations, while PG fit is significant only for Generation Y employees. Practical implications This paper sheds light on the importance for practitioners, when implementing human resource (HR) policies and strategies aiming to increase satisfaction with work, of prioritizing PJ fit and to consider PG fit for Generation Y members. Originality/value This research provides a meaningful contribution to current knowledge on generational diversity in the workplace and its impact on managerial practices by examining different levels of satisfaction with work and of PJ, PG and PS fit for three generations and the importance of each type of fit in explaining satisfaction with work for theses generations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".