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Record W1991256201 · doi:10.1080/01421590701602079

Mission Statement Day: the impact on medical students of an early exercise in professionalism

2007· article· en· W1991256201 on OpenAlexaff
Cynthia Kenyon, Judith Belle Brown

Bibliographic record

VenueMedical Teacher · 2007
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsWestern University
Fundersnot available
KeywordsThematic analysisStatement (logic)Medical educationFocus groupTheme (computing)CompassionMission statementPsychologyProfessional developmentQualitative researchMedicinePedagogyPublic relationsSociology

Abstract

fetched live from OpenAlex

BACKGROUND: The development of professional attitudes in medical students is an important aspect of medical education. AIMS: This qualitative study describes medical students' experience of Mission Statement Day. METHOD: The study was conducted using focus groups and key informant interviews. Thematic analysis identified key words, phrases, and concepts. The data was condensed into major themes and key quotes were identified to illustrate each theme. RESULTS: The process of creating a Mission Statement was more important than the Mission Statement. Three themes were identified; the central role of patients, bonding and group formation, and student ownership and valuing of the Mission Statement. Patient involvement was critical to exploring the disease and illness experience, and to stimulating discussion about compassion and professional relationships. Role modelling by faculty highlighted the value placed on this experience by the medical school. The experience was memorable, prompting the medical students to reflect on their personal values and their decision to enter medical school. CONCLUSIONS: Creation of a Mission Statement is a powerful way to introduce students to their future professional role, identify their values, and begin to develop a sense of professional identity. This memorable experience could be expanded to help students continue their professional growth.

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)0.012
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.040
GPT teacher head0.476
Teacher spread0.437 · 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

Citations20
Published2007
Admission routes1
Has abstractyes

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