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Record W2121469261 · doi:10.1111/eje.12065

Evaluating the students' perspectives of a clinic mentoring programme

2013· article· en· W2121469261 on OpenAlexaff
Barry Schwartz, M. N. Saad, David Goldberg

Bibliographic record

VenueEuropean Journal Of Dental Education · 2013
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsWestern University
Fundersnot available
KeywordsSWOT analysisMedical educationIntervention (counseling)Strengths and weaknessesPsychologyQualitative researchQualitative analysisMedicineNursingSociology

Abstract

fetched live from OpenAlex

The purpose of this article is to describe and examine the effectiveness of a mentoring program for third and fourth year clinical dental students. This is an educational intervention for the pre-doctoral students at the Schulich School of Dentistry. We have recently instituted this program and have developed a questionnaire to assess the student perspectives using a SWOT analysis of the strengths, weaknesses, opportunities and threats of this intervention by analyzing the quantitative and qualitative responses of the students towards their clinical education and patient management. Our findings, both quantitative and qualitative, indicated that the mentoring program was well received by most students who would like to see the program expanded. The majority of students felt that the mentoring program aligned well with comprehensive care of their patients while enhancing their clinical experience. One of the strongest areas of agreement involved the ability to discuss cases in a non-threatening environment. The SWOT analysis identified key areas for future improvements. We offer steps to successfully implement a similar program based on our findings. It is our hope that our results might be instrumental for other schools wishing to adopt a similar model which supports patient-based comprehensive care.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.895
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.059
GPT teacher head0.450
Teacher spread0.391 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designQualitative · Other design
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

Citations13
Published2013
Admission routes1
Has abstractyes

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