The Telephone Helpline of Persian Medicine: Social Accountability During the COVID-19 Pandemic
Bibliographic record
Abstract
Social accountability serves as an essential factor in improving the quality, efficiency, and responsiveness of health systems (1). Health and medical education policy-makers emphasize social accountability as a measure of medical universities’ commitment with regard to community health priorities (2). In 1995 the World Health Organization (WHO) defined social accountability as: “The obligation of the medical schools to direct their education, research and/or service activities towards addressing the priority health concerns of the community, region, and/or nation they have the mandate to serve. Priority health concerns are to be jointly identified by governments, health care organisations, health professionals, and the public”(3). Social accountability principles oblige education policy-makers to consider costeffectiveness, quality, equity, and relevance in planning, delivering, and evaluation of educational programs, services and research activities (2). Social accountability in medical curriculums would fulfill the target community’s requirements in the health system (4). The Association of Faculties of Medicine of Canada (AFMC) and the Global Consensus for Social Accountability of Medical Schools (GCSA) have emphasized that every medical university’s mission should be based on linking medical education systems with community health requirements.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 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 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".