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Record W1483527774 · doi:10.4103/1357-6283.109785

The Social Accountability of Medical Schools and its Indicators

2012· article· en· W1483527774 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEducation for Health · 2012
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAccountabilitySocial accountingBusinessPolitical scienceAccountingLaw

Abstract

fetched live from OpenAlex

CONTEXT: There is growing interest worldwide in social accountability for medical and other health professional schools. Attempts have been made to apply the concept primarily to educational reform initiatives with limited concern towards transforming an entire institution to commit and assess its education, research and service delivery missions to better meet priority health needs in society for an efficient, equitable an sustainable health system. METHODS: In this paper, we clarify the concept of social accountability in relation to responsibility and responsiveness by providing practical examples of its application; and we expand on a previously described conceptual model of social accountability (the CPU model), by further delineating the parameters composing the model and providing examples on how to translate them into meaningful indicators. DISCUSSION: The clarification of concepts of social responsibility, responsiveness and accountability and the examples provided in designing indicators may help medical schools and other health professional schools in crafting their own benchmarks to assess progress towards social accountability within the context of their particular environment.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.557
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.479
Teacher spread0.442 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it