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Record W4376132854 · doi:10.9778/cmajo.20210203

Academic half days, noon conferences and classroom-based education in postgraduate medical education: a scoping review

2023· review· en· W4376132854 on OpenAlexaffvenue
Luke Y. C. Chen, Tien T T Quach, Riki Dayan, Dean Giustini, Pim W. Teunissen

Bibliographic record

VenueCMAJ Open · 2023
Typereview
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInclusion (mineral)Reification (Marxism)Medical educationStakeholderCitationPsychologyMEDLINEMedicineComputer scienceLibrary scienceChemistrySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Classroom-based education (CBE) is ubiquitous in postgraduate medical education (PGME), but to date no studies have synthesized the literature on the topic. We conducted a scoping review focusing on academic half days and noon conferences. METHODS: We searched 4 databases (MEDLINE [OVID], Embase [OVID], ERIC [EBSCO] and Web of Science) from inception to December 2021, performed reference and citation harvesting, and applied predetermined inclusion and exclusion criteria to our screening. We used 2 frameworks for the analysis: "experiences, trajectories and reifications" and "description, justification and clarification." RESULTS: We included 90 studies, of which 55 focused on resident experiences, 29 on trajectories and 6 on reification. We classified 44 studies as "description," 38 as "justification" and 8 as "clarification." In the description studies, 12 compared academic half days with noon conferences, 23 described specific teaching topics, and 9 focused on resources needed for CBE. Justification studies examined the effects of CBE on outcomes, such as examination scores (17) and use of teaching strategies in team-based learning, principles of adult learning and e-learning (15). Of the 8 clarification studies, topics included the role of CBE in PGME, stakeholder perspectives and transfer of knowledge between classroom and workplace. INTERPRETATION: Much of the existing literature is either a description of various aspects of CBE or justification of particular teaching strategies. Few studies exist on how and why CBE works; future studies should aim to clarify how CBE facilitates resident learning within the sociocultural framework of PGME.

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)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.818
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.167
GPT teacher head0.523
Teacher spread0.356 · 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 designOther design
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

Citations8
Published2023
Admission routes2
Has abstractyes

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