The Post-tenure Apex: Unrewarding, Unproductive, Unhappy. Is Continuing Learning a Remedy for Mid-Career Misery?
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
Academics who are in mid-to late-stages of their career are often overlooked as participants when leaders of higher education are planning continuing learning opportunities. The reasons are varied but typically originate from a lack of understanding about this long and important phase in an academic's career. Prior research has reported that a crisis can happen at this career apex, illustrating a need for continuing learning. Many academics who move into midcareer encounter issues such as plateauing (e.g., no longer finding new research results), career disappointments (e.g., no longer able to attain research funding), and changing perspectives about their priorities (e.g., publication outputs are no longer a priority). The purpose of this study was to extend our understanding of the value of continuing learning for mid-to late-career faculty. We conducted a study on the perceived value and impact of continuing learning for mid-to late-career academics. Our findings indicate that when development centres are planning activities for mid-to late-career faculty, it will have the greatest value when (a) based on careerstage appropriate needs (e.g., high priority areas identified); and (b) activities are directed to mid-to late-career academics. While prior research has shown that interaction and collaboration are important for mid-to late-career academics, findings from this study indicate technical and practical knowledge are a higher priority.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 it