Social Responsiveness: The Key Ingredient to Achieve Social Accountability in Education and Health Care
Bibliographic record
Abstract
While social accountability (SA) is regarded as an obligation or mandate for medical school administration, it runs the danger of becoming a bureaucratic checkbox. Compassion which leads to social responsiveness (SR), in contrast, is often recognized as an individual characteristic, detached from the public domain. The two, however, complement each other in practice. Institutions must be truly socially accountable, which is possible if there is spontaneous SR to the needs, and is fueled by compassion. Compassion in this article is defined as a "feeling for other people's sufferings, and the desire to act to relieve the suffering." Compassion has a long history, whereas SA is more recently described concept that follows the historical development of social justice. SR is the moral or ethical duty of an individual to behave in a way that benefits society. Not everyone feels the need to do something for others. Even if the need is felt, there may be a lack of will to act for the needs or to act effectively to fulfill the needs of society. The reasons are many, some visible and others not. SR provides the basis for being compassionate; hence, medical schools need to include SR as a criterion in their admissions process for student recruitment and inculcate compassion in health professions education and health care. By fostering SR and engaging compassion and self-compassion to achieve SA, we can humanize medical education systems and health care.
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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 | 0.027 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.042 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.001 | 0.018 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".