MétaCan
Menu
Back to cohort
Record W4409146577 · doi:10.33137/utmj.v102i1.43104

Moral Reasoning and Development in Medical School: A Literature Review

2025· review· en· W4409146577 on OpenAlexaffvenue
Mina Al Akko, Yashan Chelliahpillai, Aiman Shahid, Parisa Airia

Bibliographic record

VenueUniversity of Toronto Medical Journal · 2025
Typereview
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsWestern UniversityUniversity of Toronto
Fundersnot available
KeywordsMoral reasoningEngineering ethicsPsychologySocial psychologyEngineering

Abstract

fetched live from OpenAlex

Morality is the system of values and standards that provide the ethical foundation for individuals in differentiating between what is right and wrong. The thought process through which individuals apply moral principles in deciding what is morally acceptable or unacceptable is known as moral reasoning. Moral development, on the other hand, is a framework through which individuals internalize and foster their morality and moral reasoning over time. T his review paper explores the moral reasoning and development of medical students during their journey in medical school, and the potential impact of the medical and ethical curricula on moral reasoning. The literature supports the finding that there is a form of moral stagnation and even regression that medical students experience as they progress through their medical training. This regression has been attributed to legalistic oriented ethical education in medical school that does not encourage critical thinking or moral discussion, the decreased emphasis on developing strong reflection skills, and the hidden curriculum that provides values that are often opposite to the ones taught in the formal curriculum.

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)0.002
metaresearch head score (Gemma)0.009
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: Review
Teacher disagreement score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.010
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
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 head0.026
GPT teacher head0.350
Teacher spread0.325 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueUniversity of Toronto Medical JournalSame topicEducation and Critical Thinking DevelopmentFrench-language works237,207