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Record W2616948816 · doi:10.36834/cmej.36817

Resetting the compass: exploring the implicit messages of orientation to a community-engaged medical school

2017· article· en· W2616948816 on OpenAlexaffvenueabout
Rachel Ellaway, Tim Dubé, Gerry Cooper, Lisa Graves

Bibliographic record

VenueCanadian Medical Education Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsWestern UniversityMcGill UniversityNOSM UniversityUniversity of Calgary
Fundersnot available
KeywordsCurriculumOrientation (vector space)Hidden curriculumConfusionMedical educationMedical schoolPsychologyPedagogyMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Although students' transition into medical school is a critical step in their professional journey, orientation has been relatively under-researched, particularly with regard to its intersections with schools' social missions. This paper reports on a study looking at the implicit messages of orientation to the Northern Ontario School of Medicine's undergraduate program. METHODS: An extended mixed methods study was conducted to look at different aspects of the School's Orientation Week. The term "hidden curriculum" was used to shape inquiry, both in its broad sense of implicit educational experiences and messages and in its more specific sense of the educational messages sent by a medical school's culture and activities. Data were collected using participant surveys, focus groups, and interviews. Transcripts and free-text survey responses were analyzed to identify underlying themes. RESULTS: Orientation Week was generally well received and was generally perceived by different stakeholders (such as students, school leaders, and community members) as a positive and necessary undertaking. However, there were points of contention and confusion that created a hidden curriculum with respect to participants' identities, both as students and as future health professionals. CONCLUSION: Orientation to undergraduate medical training can be successfully linked to a school's social mission, but in doing so it can send complex and unintended messages to the participants that may be perceived quite differently based on their circumstances and expectations.

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)0.014
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.038
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.013
Scholarly communication0.0060.004
Open science0.0020.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.067
GPT teacher head0.396
Teacher spread0.329 · 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 designQualitative
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

Citations3
Published2017
Admission routes3
Has abstractyes

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