Retirees’ motivational orientations and bridge employment: Testing the moderating role of gender.
Bibliographic record
Abstract
Bridge employment refers to the labor force participation after people retire from career jobs. It is becoming a prevalent phenomenon for retirees transitioning from employment to complete work withdrawal. Building on existing literature on retirement transition and older adults' work motivation, the present study examined the effects of 3 motivational orientations (i.e., status striving, communion striving, and generativity striving) in relating to retirees' bridge employment participation (i.e., bridge employment status and bridge employment work hours). This study also applied the social gender role theory to examine the effect of gender in moderating the effects of motivational orientations. Data from 507 Chinese retirees in Beijing revealed that communion striving and generativity striving were positively related to bridge employment participation. Further, gender moderated the effect of status striving such that status striving was positively related to bridge employment participation for male retirees but not for female retirees. In addition, exploratory analysis was conducted to examine the effects of the same set of motivational orientations on postretirement volunteering activities. Results showed that status striving was negatively related to volunteering after retirement. The findings are discussed in terms of their theoretical implications for the bridge employment literature and practical implications for recruiting and retaining older workers.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".