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Record W3111144283 · doi:10.32920/cd.v3i1.663

“Gatekeepers to the Profession”: Exploring the Experiences of Ontario Dietetic Internship Coordinators

2016· article· en· W3111144283 on OpenAlexvenueaboutno aff
Amanda Good, Jennifer Brady, Meghan Poultney, Jacqui Gingras

Bibliographic record

VenueJournal of Critical Dietetics · 2016
Typearticle
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsInternshipMedical educationWork (physics)Professional developmentPsychologyBurnoutNursingMedicinePedagogyEngineering

Abstract

fetched live from OpenAlex

Purpose: Dietetic internship coordinators are key players in selecting internship applicants and in shaping their experiences and professional identities throughout the internship. Coordinators’ experiences of their work have not yet been explored in the dietetic literature. Methods: Four current and four previous internship coordinators each participated in a one-on-one, semi-structured telephone interview. Data was analysed using constant comparative analysis. Results: Coordinators had three to nine years of experience. All stated their commitment and concern towards the dietetic training process. Coordinators noted the value of internship as a learning process and a time for intensive and essential practical training. Overall, participants felt gratified with their work, despite their roles requiring extensive time and resources. Other findings revealed that coordinators felt a sense of responsibility for selecting the “right” interns. Conclusions: A heightened sense of responsibility along with limited time and resources has the potential to lead to burnout for this professional group. Future enhancements and changes to the internship process have potential implications for health human resources among coordinators, but more research is required to examine specific implications of such changes on dietetic training and education in Ontario.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.068
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.160
GPT teacher head0.437
Teacher spread0.277 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

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