MétaCan
Menu
← Back to cohort
Record W3156126344 · doi:10.1097/acm.0000000000003993

In Reply to Brown

2021· letter· en· W3156126344 on OpenAlexaff
Eric G. Meyer, David Taylor, Sebastian Uijtdehaage, Steven J. Durning

Bibliographic record

VenueAcademic Medicine · 2021
Typeletter
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsQueen's University
Fundersnot available
KeywordsCore competencyContext (archaeology)HarmCurriculumMedical educationTask (project management)PsychologyCore curriculumCore KnowledgeMedicineEngineering ethicsPedagogyComputer scienceSocial psychologyKnowledge management

Abstract

fetched live from OpenAlex

We appreciate Dr. Brown’s thoughtful concerns regarding our recent evaluation of the Association of American Medical Colleges’ Core Entrustable Professional Activities (Core EPAs) for Entering Residency. We agree that a medical school curriculum must include instruction on retrieving evidence, collaborating, and prioritizing patient safety. These domains are not, however, what we do (EPAs) as much as they are how we do it (competencies). Although they are important competencies, they are not tasks that can be entrusted. If entrustable tasks and competencies are conflated, the Core EPAs will not live up to their promise of realizing competency-based medical education. Fortunately, reconciling this problem remains feasible. First, we must acknowledge that EPAs cannot subsume all that is medicine. Medicine requires a wide range of knowledge (e.g., an understanding of glucose metabolism), skills (e.g., the ability to retrieve evidence and to collaborate), and attitudes (e.g., “do no harm”). Even though these competencies are not EPAs, they are all paramount to the art of medicine. Second, EPAs must map to the competencies that underpin each activity. If a student is told they are only allowed to observe a task, they will reasonably ask, “Why?” The answer will require a reference to the competencies that the student must possess to participate in the activity. This explicit connection will provide context to fundamental competencies that may otherwise appear abstract. The curricular mapping of competencies to each EPA ensures competencies have a clear and meaningful role in day-to-day assessments and, critically, in providing actionable feedback to the learner. Improving the quality and safety of health care will not be achieved by rebranding such competencies as EPAs, but by linking those competencies to the routine and repeated assessment of EPAs. For example, if Core EPA 13 was redefined as “identifying and reporting patient safety concerns,” it would be an essential task that could be entrusted to a student. Additionally, the enhanced clarity of this task, combined with mapping to related competencies, would better inform curricular development, helping determine where and how students acquire the competencies required to ensure patient safety. Core EPA 9 (collaborate as a member of an interprofessional team), on the other hand, would be difficult to fix, as it describes a skill that is a means to an end. In medicine, we do not collaborate just to collaborate—we do so to deliver health care. Fortunately, most of the other Core EPAs require interprofessional collaboration and should provide ample opportunities to assess this important competency. The AAMC Core EPAs are a well-informed and thoughtfully crafted first draft of what is needed to start residency. The promise is still there. The time for revision is now.

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)0.008
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.024
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.067
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0060.009
Open science0.0040.005
Research integrity0.0240.060
Insufficient payload (model declined to judge)0.0200.012

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 head0.043
GPT teacher head0.378
Teacher spread0.335 · 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.

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

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAcademic Medicine→Same topicInnovations in Medical Education→French-language works237,207→