EXPERIENCES OF SENIOR SCHOLARS AND PROFESSORS EMERITI: FOCUS GROUP RESULTS
Bibliographic record
Abstract
Abstract In this study we were interested in learning about the experiences of Senior Scholars and Professors Emeriti at the University of Manitoba (UM), as part of a larger age-friendly university project on these term and lifetime positions for retired academics. Focus groups were held online with 11 women and men. The interview guide, developed based on earlier findings from a survey of a larger group of individuals in these same positions, included questions on their reasons for attaining the positions, benefits, challenges, and processes. Six themes were identified from the data collected: 1) commitment, 2) connection/access, 3) variability, 4) overlooked, 5) clarity (lack of) and 6) opportunity. 1) Participants indicated they are committed to their departments and colleagues locally, nationally and internationally. 2) Connections to colleagues and resources are important and appreciated (e.g., email, computer technical support, office and lab space). 3) Despite being at the same university, experiences were not consistent in how they acquired and subsequently renewed positions. 4) While there were many positive experiences shared, some respondents expressed disappointment, concern, anger and even fear, as well as having a sense of not being supported or even ignored. 5) There is an apparent misunderstanding of the designations, access to resources, and resulting expectations and roles. 6) Finally, all were positive about the opportunities to make changes to: nurture a sense of belonging of Senior Scholars and Professors Emeriti; acknowledge their efforts and achievements; create opportunities for increased participation; and ultimately foster a model workplace for retired academics.
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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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".