Nonhiring and Dismissal of Senior Workers: Is It All About the Money?
Bibliographic record
Abstract
Recent studies have shown that while most employers value the experience and expertise of senior workers, many employers are unlikely to hire or retain them. It seems that cost considerations are central to their decision-making. Many employers believe that senior workers are more expensive than their younger counterparts. Facing financial difficulties and pressures to maintain market competitiveness and profitability, employers may elect to dismiss or to not hire senior workers to maximize cost savings. This paper examines whether nonhiring or dismissal of a senior worker due to cost considerations amounts to age discrimination, and if so, whether this age discrimination is justified. It first critiques the current analyses of cost considerations in age discrimination cases in the U.S., the U.K. and Canada. Unpacking the costs associated with senior workers, the paper then argues that a decision to dismiss or not to hire senior workers due to cost considerations might be motivated by inaccurate generalization and ageist stereotypes or might result in a disproportionate impact on senior workers. Furthermore, determining whether senior workers are more expensive is a complex task which requires a careful individualized assessment. Next, the paper illustrates how a ready acceptance of cost considerations in age discrimination cases significantly undermines the fundamental purposes of anti-age discrimination law. Advancing a proportionality analysis, the paper then outlines the limited circumstances in which cost considerations should be allowed. Finally, it advocates a process of procedural fairness prior to any decision to dismiss or not to hire senior workers due to cost considerations. While the paper focuses on Canadian law, its findings are of great importance to other jurisdictions.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".