Effect of Personal and Occupational Characteristics on Attitudes to an Obligatory Retirement Age—A Content Analysis Investigation
Bibliographic record
Abstract
This study is a pioneer study examining the effects of personal and occupational background variables on the attitude of faculty members to an obligatory retirement age in academia. Previous studies on performance measures of academic faculty in research, teaching, academic administration, and contribution to the community, testified to associations between faculty member achievements and their personal characteristics (gender, age) as well as features related to their academic field of occupation (faculty, academic rank, tenure). Hence, these quality measures of academic faculty have meaning for and influence on research, even after the customary retirement age. Obligatory retirement age is a well-known issue and it is arousing much interest in general, and in academia in particular. Academic work includes activity focused on research, teaching, advisory work, participation in academic committees and conferences—namely, activities that require human thinking. This leads to the question of whether and to what degree personal and occupational characteristics are associated with the attitude of faculty members to retirement age. One hundred and eight questionnaires administered to senior faculty were collected in a case study of a single university. Qualitative and statistical research tools were employed, with the aim of creating a model that expresses the association between faculty members’ personal and occupational characteristics and their attitude to retirement age in academia. The research findings show that the background variables affecting the attitude of faculty members to retirement are age and tenure—faculty members’ age and status as tenured faculty determine their objection to the obligatory retirement age.
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How this classification was reachedexpand
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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".