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Record W3111808203 · doi:10.32920/cd.v2i1.780

“Forgetting the Pain”: Successful Applicants’ Experiences of Attaining a Dietetic Internship Position in Ontario

2014· article· en· W3111808203 on OpenAlexaffvenueabout
Olivia Siswanto, Jennifer Brady, Patrícia Alvarenga, Ahuva Magder, Jordana Riesel, Nazima Qureshi, Jacqui Gingras

Bibliographic record

VenueJournal of Critical Dietetics · 2014
Typearticle
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsInternshipMedical educationTelephone surveyPsychologyTelephone interviewWork experienceMedicineWork (physics)SociologyEngineering

Abstract

fetched live from OpenAlex

This study seeks to explore the lived experience of students who applied to an Ontario-based dietetic internship program and were successful upon their first application attempt. A 32-item online survey was distributed via email to all students who graduated from Brescia University College, Guelph University, and Ryerson University between 2006 and 2011 and to members of the Dietitians of Canada Student Network, Toronto Home Economics Association, and Ontario Home Economists in Business. The final survey item invited respondents to participate in one-on-one interview. The semi-structured interviews focused on participants’ experience of applying to and receiving an internship position. Interviews were conducted either in person or by telephone and were audio recorded, transcribed verbatim, and thematically analyzed by the research team. Of the 82 participants who completed the online survey, 17 respondents participated in a one-on-one interview. Even students who were successful at attaining an internship are negatively impacted by having to compete with peers for an internship spot in Ontario. This research serves as a comparison to previous work examining the experiences of not attaining an internship. Both studies point directly to the changes urgently required to enhance the current model of education and training 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)0.004
metaresearch head score (Gemma)0.006
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 score0.268
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.073
GPT teacher head0.415
Teacher spread0.342 · 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
Published2014
Admission routes3
Has abstractyes

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