‘I don’t have time’: issues of fragmentation, prioritisation and motivation for education scholarship among medical faculty
Bibliographic record
Abstract
OBJECTIVES: Although lack of time has been frequently cited as a barrier to scholarship, there has been little inquiry into what specific factors medical faculty staff perceive as contributing to this dilemma. The purpose of the present study was to explore, in greater detail, lack of time as a barrier for faculty interested in pursuing education scholarship. METHODS: In 2004, as part of a cross-sectional, mixed-methods needs assessment, 73 (67.6%) medical faculty completed a questionnaire probing areas related to education scholarship. Additionally, one year later, 16 respondents (60% of those invited) each participated in one of three focus groups. RESULTS: Despite their interest and regardless of their background training in education, faculty were able, on average, to devote only negligible amounts of time to education scholarship. The most commonly reported barrier to these pursuits was lack of protected time. Further analysis revealed that the time-related factor appeared to involve three themes: fragmentation (where opportunities to work on education projects are sporadic); prioritisation (where work responsibilities including after-hours work and administrative workload complete for time, and where there is difficulty in securing financially remunerated time), and motivation (where the degree of recognition and support for education work by both the department and colleagues is limited). CONCLUSIONS: With respect to education scholarship, the dilemma caused by lack of time involves a complex, multi-faceted set of issues which extends beyond the number of hours available in a day. Personal interest and having background training in education do not appear to be sufficient to encourage involvement. Multiple institutional support mechanisms are necessary.
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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 | 0.020 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".