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Record W2191685500 · doi:10.3109/0142159x.2015.1112894

A critical hybrid realist-outcomes systematic review of relationships between medical education programmes and communities: BEME Guide No. 35

2015· review· en· W2191685500 on OpenAlexaff
Rachel Ellaway, Laurel O’Gorman, Roger Strasser, David C. Marsh, Lisa Graves, Patricia Fink, Catherine Cervin

Bibliographic record

VenueMedical Teacher · 2015
Typereview
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of TorontoLaurentian UniversityUniversity of CalgaryNOSM University
Fundersnot available
KeywordsMedical educationCommunity engagementSociologyMedicinePolitical sciencePublic relations

Abstract

fetched live from OpenAlex

BACKGROUND: The relationships between medical schools and communities have long inspired and troubled medical education programmes. Successive models of community-oriented, community-based and community-engaged medical education have promised much and delivered to varying degrees. A two-armed realist systematic review was undertaken to explore and synthesize the evidence on medical school-community relationships. METHOD: One arm used standard outcomes criteria (Kirkpatrick levels), the other a realist approach seeking out the underlying contexts, mechanisms and outcomes. 38 reviewers completed 489 realist reviews and 271 outcomes reviews; 334 articles were reviewed in the realist arm and 181 in the outcomes arm. Analyses were based on: descriptive statistics on both articles and reviews; the outcomes involved; the quality of the evidence presented; realist contexts, mechanisms, and outcomes; and an analysis of underlying discursive themes. FINDINGS: The literature on medical school-community relationships is heterogeneous and largely idiographic, with no common standards for what a community is, who represents communities, what a relationship is based on, or whose needs are or should be being addressed or considered. CONCLUSIONS: Community relationships can benefit medical education, even if it is not always clear why or how. There is much opportunity to improve the quality and precision of scholarship in this area.

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.

How this classification was reachedexpand

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)0.015
metaresearch head score (Gemma)0.220
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.361
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.220
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.132
GPT teacher head0.475
Teacher spread0.343 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations34
Published2015
Admission routes1
Has abstractyes

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