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Record W4401365436 · doi:10.3148/cjdpr-2024-008

Exploring Student Perspectives of the Dietetics Profession Using a Professional Socialization Lens

2024· article· en· W4401365436 on OpenAlexaffvenue
Natalie D. Riediger, Anne Waugh, Barbara Parker, Constance Russell, Andrea E. Bombak

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2024
Typearticle
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsUniversity of New BrunswickLakehead UniversityUniversity of Manitoba
Fundersnot available
KeywordsSocializationLens (geology)Medical educationThrough-the-lens meteringPsychologyPedagogyMedicineSocial psychologyEngineering

Abstract

fetched live from OpenAlex

Purpose: We aimed to explore student perspectives of the dietetics profession using a professional socialization lens. Methods: We conducted qualitative semi-structured interviews, virtually or by phone, with 25 dietetic undergraduate/graduate students or interns in 2020/21. Transcripts were thematically analyzed. Results: All participants identified as female, averaged 25 years old at the time of the interviews, and were in different stages of their education. Two themes captured their perspectives of the profession: dietitians have technical expertise and professional identities are evolving. Technical expertise was focused on scientific understandings of how individuals consume and utilize food, and how (mostly Western) food should be prepared for safety and maximum nutrition. Participants perceived dietetics as a white, feminized profession with dietitians’ role to aid in weight loss; participants actively sought to resist these stereotypes, notably through social media. Conclusions: While holding technical expertise continues to be embedded as a key component of dietetics identity, student professional socialization is also being shaped by social media, racial justice, and body positivity movements. This socialization process is likely to influence changes to the profession as students enter practice.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
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 head0.475
GPT teacher head0.564
Teacher spread0.089 · 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 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

Citations2
Published2024
Admission routes2
Has abstractyes

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