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Development of an Undergraduate Medical Curriculum

2003· review· en· W1980329199 on OpenAlexafffundabout
David Fleiszer, Nancy Posel

Bibliographic record

VenueAcademic Medicine · 2003
Typereview
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsMcGill University
FundersMolson FoundationMcGill University
KeywordsCurriculumMainstreamInteractivityVariety (cybernetics)Medical educationLearning stylesComputer scienceMultimediaMedicineMathematics educationPedagogyPsychologyPolitical science

Abstract

fetched live from OpenAlex

In 1997 the Faculty of Medicine at McGill University received a grant from the Molson Foundation. The primary project deliverable, which the authors describe, was an online, multimedia-enhanced, undergraduate medical curriculum. The decision to develop an electronic curriculum was predicated on the belief that the integration of educational technology within mainstream material delivered a "value added" component to both students and faculty, which would, in turn, facilitate teaching and learning. Pedagogical values were deemed to include: (1) the ability to use the media to implement adult learning principles such as learner-centered, self-directed and guided learning, (2) the inherent interactivity of the technology, (3) the potential of the technology to provide a powerful means for fostering forms of "termless" learning that students will need to practice medicine, (4) recognition that use of multimedia can address, in part, the variety of learning styles evidenced by students in the lecture hall and classroom, and (5) the provision of opportunities for horizontal and vertical curricular integration. In addition, it was anticipated that an electronic curriculum would permit: (1) easy incorporation of informatics within mainstream curricula, (2) centralization and standardization of curricular material, (3) editorial functionality for revisions and updates, (4) wide accessibility of material irrespective of venue, (5) search functionality for faculty and students, (6) the ability to perform curriculum inventory, and (7) the potential for use to compensate for decreased faculty time. The ongoing experience at McGill has shown that the merging of technology and pedagogy requires a substantial commitment of resources and recognition of faculty time and change-management issues.

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)0.004
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0250.006

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 head0.096
GPT teacher head0.459
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.

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

Citations19
Published2003
Admission routes3
Has abstractyes

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