Shielding Self-Esteem through the Adoption of Psychological Disengagement Mechanisms: The Good and the Bad News
Bibliographic record
Abstract
The fact that Canada's working population is aging and will continue to do so is no surprise to anyone. What is surprising though is what many of these aging workers are experiencing in the late years of their career: They continue to be the target of negative stereotypes which in turn, reinforce discrimination and marginalization practices. The present study was aimed at understanding the consequences of differential treatment based on age (measured by relative deprivation) from the theoretical perspective of psychological disengagement. A total of 117 Canadian civil servants over the age of 45 participated in this study. According to hypotheses, it was found that feelings of relative deprivation were associated with discounting which in turn led to a decrease in self-esteem. This chain of reactions generated instabilities, fluctuations in self-esteem and through this, questioned the protective role of psychological disengagement. It is only by devaluing their non-prestigious domain of activity that participants seemed to regain stability of their self-esteem. Theoretical and practical implications of these results are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".