Pandemic transition to online for healthcare profession education: A webscrape seeking perspectives of innovation and digital equity
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
The pandemic caused a sudden and rapid transition to online of health profession education programs, in an attempt to maintain the critical supply of new graduates during a pandemic. A gap existed pre-pandemic between technology mediated pedagogy and digital health literacy; a gap that was forced to narrow. Health education educators considered digital equity for students and the resultant impact of the digital divide in online environments for competency attainment related to digital health literacy and quality patient care. This team engaged in an emancipatory action research webscrape of the immediate pivot period to online in winter 2020 to summarize the expertise being shared over social media platforms or teaching and learning excellence podcasts and blogs. The search criteria for the webscrape covered three areas including changes in 1) healthcare profession education, 2) innovations, and 3) diversity, equity and inclusion. The results, in relation to pre-pandemic reflections, were on the future of education and maintaining innovative momentum found during the pandemic, the future of healthcare and being attuned to patient needs despite virtual care delivery, along with the future society and ensuring students attain digital wisdom. This webscrape speaks to what health profession education values going forward, reducing the digital divide for students and patients.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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