Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this study is to identify antecedents of intentions to unretire among a group of retirees that included both those who had not returned to the workforce since their retirement and those who had previously unretired. Design/methodology/approach A cross‐sectional survey collected data from 460 recent retirees between the ages of 50 and 70. Findings Results of hierarchical regression indicated that retirees are more likely to remain retired if they feel financially secure and have a positive retirement experience. Conversely, they are more likely to intend to return to the workforce if they experience financial worries, wish to upgrade their skills or miss aspects of their former jobs. Practical implications Aging boomers who anticipate early retirement have created a dwindling labor pool. Simultaneously, the global pension crisis has impacted on the financial decisions of retirees. A trend to abolish mandatory retirement and/or increase mandatory age in various countries provides individuals with more freedom in their retirement decisions. Accordingly, managers must be creative in their HR planning strategies to retain or recruit skilled retirees. Originality/value Previous research has addressed retirement as a final stage, however, given simultaneous global demographic changes and economic concerns, this study provides new knowledge regarding the factors that push and pull retirees to participate in the labor market.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it