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Record W4311569816 · doi:10.32920/21737366

On beginning to become dietitians

2022· preprint· en· W4311569816 on OpenAlexaff
Debbie MacLellan, Jacqui Gingras, Daphne Lordly, Jennifer Brady

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsQueen's UniversityToronto Metropolitan UniversityUniversity of Prince Edward Island
Fundersnot available
KeywordsSocializationIdentity (music)Psychological resiliencePsychologyProcess (computing)NursingMedical educationMedicineSocial psychologyAesthetics

Abstract

fetched live from OpenAlex

This paper explores beginning dietetic practitioners’ perspectives on the process of becoming dietetics professionals through the use of vignettes to illuminate the complex process of professional socialization. Embedded in these vignettes are three themes related to the socialization process that occurs in the early years of dietetic practice: congruence, resilience, and relationships. Our findings indicate that new dietitians struggle to develop their dietitian identity. They feel unprepared for the relational and practice realities of the workplace and find the transition from dietetic intern to dietitian challenging. They seek many ways to cope including seeking support from others and planning for the future but some consider leaving the profession. It is important to understand the professional socialization and identity formation processes that occur during the early years of practice to ensure that dietitians feel prepared and supported as they begin their careers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0110.007
Scholarly communication0.0060.006
Open science0.0010.007
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0090.003

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 head0.126
GPT teacher head0.480
Teacher spread0.354 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2022
Admission routes1
Has abstractyes

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