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Record W2993082937 · doi:10.1097/acm.0000000000003095

14 Years Later: A Follow-Up Case-Study Analysis of 8 Health Professions Education Scholarship Units

2019· article· en· W2993082937 on OpenAlexaffabout
Susan Humphrey‐Murto, Bridget C. OʼBrien, David M. Irby, Cees van der Vleuten, Olle ten Cate, Steven J. Durning, Larry D. Gruppen, Stanley J. Hamstra, Wendy Hu, Lara Varpio

Bibliographic record

VenueAcademic Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsScholarshipThematic analysisUnit (ring theory)Public relationsSet (abstract data type)Medical educationPolitical scienceSociologyPsychologyMedicineQualitative researchSocial scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

PURPOSE: Internationally, health professions education scholarship units (HPESUs) are often developed to promote engagement in educational scholarship, yet little is known about how HPESUs change over time or what factors support their longevity. In hopes of helping HPESUs thrive, this study explored factors that shaped the evolution of 8 HPESUs over the past 14 years. METHOD: This study involved retrospective case-study analysis of the 8 American, Canadian, and Dutch HPESUs profiled in a 2004 publication. First, the research team summarized key elements of HPESUs from the 2004 articles, then conducted semistructured interviews with the current unit directors. In the first set of questions, directors were asked to reflect on how the unit had changed over time, what successes the unit enjoyed, what enabled these successes, what challenges the unit encountered, and how these challenges were managed. In the second set of questions, questions were tailored to each unit, following up on unique elements from the original article. The team used Braun and Clarke's 6-phase approach to thematic analysis to identify, analyze, and report themes. RESULTS: The histories of the units varied widely-some had grown by following their original mandates, some had significant mission shifts, and others had nearly disappeared. Current HPESU directors identified 3 key factors that shaped their HPESU's longitudinal development: the people working within and overseeing the HPESU (the need for a critical mass of scholars, a pipeline for developing scholars, and effective leadership), institutional structures (issues of centralization, unit priorities, and clear messaging), and funding (the need for multiple funding sources). CONCLUSIONS: Study findings offer insights that may help current HPESU directors to strategically plan for their unit's continued development. Tactically harnessing the factors identified could help directors ensure their HPESU's growth and contend with the challenges that threaten the unit's success.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.993
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0100.003
Scholarly communication0.0030.003
Open science0.0030.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.072
GPT teacher head0.435
Teacher spread0.363 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainEvaluation
GenreEmpirical

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

Citations15
Published2019
Admission routes2
Has abstractyes

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