Strategies of job seekers related to age-related stereotypes
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 – Given the increasing diversity in the age of job seekers worldwide and evidence of perceptions of discrimination and stereotypes of job seekers at both ends of the age continuum, the purpose of this paper is to identify how perceptions of age-related bias are connected to age-related identity management strategies of unemployed job seekers. Design/methodology/approach – Data were collected from 129 unemployed job-seeking adults who were participants in a career placement service. Participants completed paper-and-pencil surveys about their experiences of age-related bias and engagement in age-related identity management strategies during their job searches. Findings – Older job seekers reported greater perceptions of age-related bias in employment settings, and perceptions of bias related to engaging in attempts to counteract stereotypes, mislead or miscue about one's age, and avoid age-related discussions in job searching. Individuals who were less anxious about their job search were less likely to mislead about age or avoid the topic of age, whereas individuals with higher job-search self-efficacy were more likely to acknowledge their age during their job search. Older job seekers higher in emotion control were more likely to acknowledge their age. Originality/value – Little is known about how job seekers attempt to compensate for or avoid age-related bias. The study provides evidence that younger and older job seekers engage in age-related identity management and that job search competencies relate to engagement in particular strategies.
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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 | 0.002 | 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) | 0.001 | 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 it