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Record W2511129601 · doi:10.1097/acm.0000000000001367

Working Definitions of the Roles and an Organizational Structure in Health Professions Education Scholarship: Initiating an International Conversation

2016· article· en· W2511129601 on OpenAlexaffabout
Lara Varpio, Larry D. Gruppen, Wendy Hu, Bridget C. OʼBrien, Olle ten Cate, Susan Humphrey‐Murto, David M. Irby, Cees van der Vleuten, Stanley J. Hamstra, Steven J. Durning

Bibliographic record

VenueAcademic Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsScholarshipTerminologyConversationPublic relationsTransferabilityOrganizational structureField (mathematics)Political scienceSociologyComputer science

Abstract

fetched live from OpenAlex

PROBLEM: Health professions education scholarship (HPES) is an important and growing field of inquiry. Problematically, consistent use of terminology regarding the individual roles and organizational structures that are active in this field are lacking. This inconsistency impedes the transferability of current and future findings related to the roles and organizational structures of HPES. APPROACH: Based on data collected during interviews with HPES leaders in Canada, Australia, New Zealand, the United States, and the Netherlands, the authors constructed working definitions for some of the professional roles and an organizational structure that support HPES. All authors reviewed the definitions to ensure relevance across multiple countries. OUTCOMES: The authors define and offer illustrative examples of three professional roles in HPES (clinician educator, HPES research scientist, and HPES administrative leader) and an organizational structure that can support HPES participation (HPES unit). These working definitions are foundational and not all-encompassing and, thus, are offered as stimulus for international dialogue and understanding. NEXT STEPS: With these working definitions, scholars and administrative leaders can examine HPES roles and organizational structures across and between national contexts to decide how lessons learned in other contexts can be applied to their local contexts. Although rigorously constructed, these definitions need to be vetted by the international HPES community. The authors argue that these definitions are sufficiently transferable to support such scholarly investigation and debate.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.057
GPT teacher head0.397
Teacher spread0.340 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
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

Citations33
Published2016
Admission routes2
Has abstractyes

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