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Record W2109069890 · doi:10.3148/68.1.2007.36

<i>Performance Issues of Dietetic Interns:</i>A Dietetic Educator's Perspective

2007· article· en· W2109069890 on OpenAlexaffvenueabout
Daphne Lordly

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2007
Typearticle
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsPerspective (graphical)Medical educationMedicinePsychologyEngineering ethicsComputer scienceEngineering

Abstract

fetched live from OpenAlex

PURPOSE: Dietetic internships provide practical experience leading, in most cases, to the attainment of entry-level dietetic competence. Problematic intern performance issues were examined, as were how educators resolve these issues and the supports they require to manage them. METHODS: A survey was electronically distributed to all Dietitians of Canada internship/university course directors (n=57). The response rate was 40% (n=23). RESULTS: Annually, 61% of internships involve challenging performance issues related to intern knowledge, skills, attitude, and behaviour. These issues manifest themselves individually or in combination as an intern's inability to apply/demonstrate appropriate knowledge/skill, a view/approach to the profession that is not in keeping with the organizational view, an attitude that is in conflict with program values, a negative response to feedback, an inability to relate to others, work habits that are in conflict with program values, and personal attributes that detract from the ability to meet program expectations. Educators respond to these issues by modifying their communications, the learning environment, and the program. CONCLUSIONS: Educators' strategies could be enhanced through consultation with other educators, mentor training, and the development of formal procedures.

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)0.009
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation 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 score0.349
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.146
GPT teacher head0.520
Teacher spread0.374 · 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.

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

Citations9
Published2007
Admission routes3
Has abstractyes

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