MétaCan
Menu
Back to cohort
Record W2983754140 · doi:10.5539/gjhs.v11n13p1

The Potential Impact of Morality on Medical Student Global Health Participation

2019· article· en· W2983754140 on OpenAlexvenueno aff
Joel Rowe, Stephen G. Post

Bibliographic record

VenueGlobal Journal of Health Science · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsnot available
Fundersnot available
KeywordsEmpathyPsychologySpiritualityCompassionSocial psychologyTypologyMedicinePolitical scienceSociologyAlternative medicine

Abstract

fetched live from OpenAlex

Interest in global health experiences (GHEs) has surged in the last decade throughout undergraduate medical education. Positive clinical and cultural learning impacts are well described; however, the moral and motivational typology of the globally minded medical student are yet to be elucidated. We surveyed 85 US medical students, 41 who participated in a GHE during medical school and 44 who did not, to examine their sense of moral association with local community, Americans, and all of humanity. Measures of empathy and spirituality were also administered, as well as a qualitative prompt to elicit reasons for participating, or not, in a GHE. The results of logic regression analysis suggest that the strongest predictors of GHE participation are strong, geographically non-specific identification with ‘all humanity’ [OR=1.31, P<0.01, 95% CI, 1.07–1.59], as well as participation in an abroad experience prior to medical school [OR 141, P<0.01, 95% CI, 10.1–1960]. While respondent groups did not differ significantly in their association with local community, incremental increase in identification with ‘Americans’ decreased likelihood of IME participation by 20% [P=0.02, 95% CI, 0.67–0.96]. No significant effect was found between participant groups in response to empathy or spirituality scales. This pilot study demonstrates that a global regard for ‘all humanity’ may motivate GHE participation while a strong national association diminishes its likelihood.

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)0.014
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.513
Teacher spread0.467 · 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 designObservational
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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueGlobal Journal of Health ScienceSame topicCultural Competency in Health CareFrench-language works237,207