Bibliographic record
Abstract
This reflection on the academic and practice careers—my own and some notable health promotion professors’—supports my suggestions about what makes good teaching and research faculty members in professional schools seeking to prepare next generations of practitioners for health education and health promotion careers. From the perspective of pedagogy in health promotion, the preparation of students for their roles in practice—in whatever blend of policy, planning, management, delivery, or evaluation of programs—should emanate, where possible, from field experience and reality-tested theoretical and evidence-based precepts. Just as usable evidence-based practices need to include practice-based evidence, so too must usable pedagogy for practitioners be built on periodic exposure and experience of instructors in contemporary practice. The concept of “turnstile careers” is introduced to address this need for periodic immersion of faculty in practice positions with responsibility for programs.
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.
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 | 0.022 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.024 | 0.052 |
| Scholarly communication | 0.025 | 0.019 |
| Open science | 0.003 | 0.046 |
| Research integrity | 0.005 | 0.018 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".