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Record W2536962680 · doi:10.3148/cjdpr-2016-026

Food and Culinary Knowledge and Skills: Perceptions of Undergraduate Dietetic Students

2016· article· en· W2536962680 on OpenAlexafffundvenueabout
Marcia Cooper, Leanne Mezzabotta

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2016
Typearticle
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsOttawa HospitalHealth Canada
FundersHealth Canada
KeywordsPerceptionMedical educationPsychologyFood scienceMedicineChemistry

Abstract

fetched live from OpenAlex

PURPOSE: The objective of the current study was to examine food and culinary skills and knowledge of dietetic students. METHODS: to explore the skills, knowledge, and perceptions of undergraduate dietetic students regarding food and cooking. Chi-square and logistic regression analyses were used to compare skills and knowledge of food and culinary concepts. RESULTS: The final sample included second- (n = 22) and third-year (n = 22) students within the Baccalauréat specialisé en sciences de la nutrition program at the University of Ottawa. There were no significant differences (P > 0.05) on 3 of 4 skills (preparing a cake, whipping egg whites, or baking a yeast bread) or knowledge concepts (fold, baste, braise, grill, and poach) amongst second- and third-year students. Third-year students perceived more skill in preparing a béchamel sauce. There was a trend for third-year students (59%) to have higher food and cooking skills and knowledge compared with second-year students (32%). CONCLUSIONS: Perceived knowledge and confidence was proportional with the academic year, whereas overall knowledge and skills of food and culinary concepts were moderate among both groups of students. This research suggests that more dedicated time may need to be spent on food and cooking competencies in undergraduate dietetic education.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.113
GPT teacher head0.502
Teacher spread0.388 · 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 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

Citations4
Published2016
Admission routes4
Has abstractyes

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Same venueCanadian Journal of Dietetic Practice and ResearchSame topicDietetics, Nutrition, and EducationFrench-language works237,207