Ageism in the Workplace and Labour Market: The Experiences of Older Adults
Bibliographic record
Abstract
The traditional career arc is often organized around the assumption that the most productive “work years” are before the age of 65. As such, workplaces have the potential to engage in harmful age discrimination. As scholarly literature based in the Canadian context has been quite limited, this study aimed to gain a qualitative understanding of older Ontario workers’ lived experiences of ageism. Semi-structured interviews with 10 older adults (55+) who were either currently employed, recently retired, or looking to gain re-entry into the labour market were conducted. Using Braun and Clarke’s (2006) six-stage framework for thematic analysis, five key themes that each mediate the varying experience of ageism in the workplace and labour market were identified. Participants highlighted the complex nature of the ageist interactions as well as the gamut of psycho-social consequences that they have faced. Participants also discussed several different types of preferred coping mechanisms. Intersections with other forms of discrimination and the degree to which COVID-19 has impacted participants were also central in shaping the experiences of ageism in the workplace. The findings from this research shed light on the lived experiences of those who have faced age-based discrimination in the labour market, an area of research that is currently lacking. Additionally, results have the ability to inform employers’ equity, diversity and inclusion practices and policies that often do not include age-related issues. The findings from this thesis are positioned in terms of their implications for future research and policy. The results of this thesis contribute substantively to the current social gerontological literature. This work provides insight into the importance of age in the workplace and labour market, as well as the role that age segregation throughout the life course plays in the perpetuation of ageist attitudes and behaviours throughout one’s working life.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".