The effect of downsizing on organizational practices targeting older workers
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the association between organizational downsizing and the extent to which organizations are engaging in human resource practices tailored to the needs of older workers (Study 1) and are providing a supportive training and development climate for older workers (Study 2). Design/methodology/approach Study 1 data were obtained from 449 employed individuals aged 50 to 68 years. Study 2 data were obtained from 395 employed individuals aged 50 to 70 years. Respondents were from a broad cross‐section of occupations and organizations across Canada. Findings Respondents in downsized organizations indicated that their organizations were significantly less likely to be engaging in human resource practices tailored to older workers and that their organizations had a less supportive training and development climate than their counterparts whose organizations had not downsized. Research limitations/implications The findings are based on older workers' perceptions of organizational practices, which may or may not be an accurate reflection of what organizations actually have in place. Practical implications Organizations, especially those that have downsized, will be at a disadvantage if they continue to ignore the needs of older workers. Employers will have to change how they view older workers and put in place organizational practices geared to older workers such as those examined in the paper. Ensuring that older workers have the requisite skills and competencies to extend their working lives may require government involvement. Originality/value The paper illustrates that downsizing is detrimental to organizational practices that the aging workforce literature identifies as especially important to 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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".