A New Approach to the Link between Identity and Relative Deprivation in the Perspective of Ageism and Retirement
Bibliographic record
Abstract
Although the work force is aging, views regarding older workers remain negative. As a result, complaints of discrimination on the basis of age have increased. This situation prompts the following questions: what leads aging workers to acknowledge disparities between younger workers and themselves, and what are the consequences for aging workers of integrating into their self-image some of the characteristics commonly associated with their cohort? These questions are examined in light of a new approach to the link between identity and relative deprivation. The following hypotheses were included in a predictive model: the more individuals include characteristics of their group into their self-descriptions, the more they experience personal deprivation when comparing their own situation to that of younger workers. These feelings, in turn, affect them during retirement in terms of lowered self-esteem and decreased satisfaction with their life. This model was tested among 149 young retirees. Hypotheses were confirmed, and it was shown that end-of-career experiences have an impact on the situation of young retirees. The more individuals integrated characteristics of aging workers, the more they felt personally deprived as a result of invidious comparisons with young co-workers. The latter also had a negative impact on self-esteem and life satisfaction. Implications of results and new avenues of research are discussed herein.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".