EXPERIENCES OF SENIOR SCHOLARS AND PROFESSORS EMERITI AT THE UNIVERSITY OF MANITOBA: ONLINE SURVEY FINDINGS
Bibliographic record
Abstract
Abstract Universities are unique in providing specific positions for retired academics to continue to work without pay. At the University of Manitoba (UM) in Winnipeg, Canada, there are two types of retiree positions: Senior Scholar (term) or Professor Emerita/Emeritus (lifetime/honorary). These positions allow retirees to engage in activities like supervising graduate students and conducting research. Supports (e.g., office or lab space) may be provided. However, anecdotal information and faculty consultations have suggested that new policies/procedures and initiatives may be needed to enhance their experiences and overall benefits for the university. An exploratory, online survey designed by age-friendly university committee members was completed by 78 current and past Senior Scholars and Professors Emeriti. Results revealed the many activities engaged in (most commonly reported: 78.7% writing, 70.7% research) as well as challenges experienced (e.g., parking, transitions resulting in temporary losses of email or other computer-related resources). While most (83.8%) indicated that they felt connected to the University, others indicated that they felt cut-off. Some also expressed the sentiment that “…the university/faculty does not initiate action to take advantage of my wisdom, experience and talents.” Respondents further indicated their acceptance of several possible recommendations for improvements for individuals in their positions, with the most popular being a website to highlight their work and accomplishments. Given the many benefits that they see for themselves and the University based, on their continued efforts in their retiree roles, changes are imperative to improve the age inclusivity for individuals at this career stage at UM.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".