Health professions education as a discipline: Evidence based on Krishnan’s framework
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
Health professions education (HPE) emerged as a specific domain of higher education in the 1960s. The interim decades brought the development of advanced training in health professions education and the implementation of HPE offices at many institutions of healthcare and education across the world. Despite these advancements, organizations considering the establishment of HPE offices, or advanced HPE training programs are still challenged by approving authorities to demonstrate that HPE is a discipline and not simply a branch of higher education. Although other scholars have proposed defined characteristics to guide the recognition of study fields as separate academic disciplines, Krishnan's framework is easily operationalized and its use has been broadly reported in the management, education, and intelligence studies literature, among others. Krishnan contends that an academic discipline generally presents the following characteristics: (1) an object of study and research that, although particular to the discipline, can be common to others; (2) a body of specialized knowledge, relative to the subject of study and research, typically unique to the discipline; (3) theories and concepts that frame and organize the specialized knowledge of the discipline; (4) specific terminologies or technical language related to the subject of study and research; (5) research methods adapted to the particular demands of the discipline; and (6) an institutional presence demonstrated by teaching at the graduate level of subjects specific to the discipline, and by the existence of academic departments and professional associations. The purpose of this paper is to present arguments in support of the status of HPE as an academic discipline using Krishnan's framework. It is our hope that these arguments will facilitate the efforts of organizations planning for the establishment of HPE offices or advanced HPE training programs at their institutions.
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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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