Social accountability: The extra leap to excellence for educational institutions
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
More than ever are we facing the challenge of providing evidence that what we do responds to priority health needs and challenges of the ones we intend to serve: patients, citizens, families, communities and the nation at large. Which are those health needs and challenges? Who defines them? How do medical schools organize themselves to address them through their education, research and service delivery functions? Principles of social accountability call for an explicit three-tier engagement: identification of current and prospective social needs and challenges, adaptation of school's programmes to meet them and verification that anticipated effects have benefited society. Measurement tools need to be designed and tested to steer development in this direction, particularly to establish a meaningful relationship between inputs, processes, outputs and impact on health. The Global Consensus on Social Accountability of Medical Schools provides a unique opportunity to foster collaborative research and development in an area of great significance for the future of medical education.
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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.001 |
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