MétaCan
Menu
Back to cohort
Record W2069353298 · doi:10.15273/dmj.vol40no2.4574

From the Classroom to the Community: Cultivating Social Responsibility in Medical Education

2014· article· en· W2069353298 on OpenAlexaffvenueabout
Kelly Fenn, Stephen Middleton

Bibliographic record

VenueDalhousie Medical Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsDalhousie University
Fundersnot available
KeywordsNarrativeCitizen journalismAction (physics)Participatory action researchMedical educationSocial determinants of healthPsychologySocial responsibilitySociologyPublic relationsPedagogyMedicineNursingPolitical sciencePublic health

Abstract

fetched live from OpenAlex

This paper explores the experiences of two first year medical students through the Local Global Health Elective, a year-long clinical placement program developed through the Dalhousie Global Health Office. The article begins with a narrative exploration of the clinical experiences of the authors during their elective placements in two underserved local Halifax communities. The paper then explores the shifting paradigm in medical education around how learning objectives related to the social determinants of health are met in undergraduate medical education. The article concludes with a discussion about going beyond teaching the social determinants of health in a controlled classroom setting. The authors argue that in order for medical students to translate knowledge about the social determinants of health into behavior and action that reflects the unique needs of each patient, a participatory solution is needed.

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)0.012
metaresearch head score (Gemma)0.012
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 score0.027
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0270.042
Scholarly communication0.0140.007
Open science0.0020.029
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0050.001

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 head0.024
GPT teacher head0.369
Teacher spread0.345 · 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

Citations0
Published2014
Admission routes3
Has abstractyes

Explore more

Same venueDalhousie Medical JournalSame topicInnovations in Medical EducationFrench-language works237,207