Experiences of Senior Scholars and Professors Emeriti – a mixed methods study
Bibliographic record
Abstract
Universities are unique workplaces with specific positions designed for retirees to continue to contribute. To enable universities to be more age inclusive and age-friendly, this research considers the perspectives of retired academics in these designated positions about their experiences and their needs. In this mixed methods study, an online survey (n = 78) was followed by focus group interviews (n = 11) with Senior Scholars and Professors Emeriti at one Canadian university. Findings revealed the many activities engaged in (e.g. writing, conducting research) as well as challenges experienced (e.g. parking, information technology access). Six themes were identified from the focus group data: commitment, connections, variability, overlooked, clarity, and opportunity. Given the benefits that Senior Scholars and Professors Emeriti see for themselves and their university based on their continued efforts in these roles, changes are imperative to improve the situation for individuals at this career stage to maximise their inclusion and contributions.
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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 | 0.000 |
| 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) | 0.000 | 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".