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Record W4391439175 · doi:10.21083/surg.v15i1.7526

Supporting Dietitians in Practice: Professional Development Activities of Dietitians of Canada in the Past 30 Years

2024· article· en· W4391439175 on OpenAlexaffvenueabout
Sophia Hou, Rebecca Krieger, Manseerat Uppal, Marlene Wyatt, Linda Dietrich, Paula Brauer, Janis Randall Simpson

Bibliographic record

VenueSURG Journal · 2024
Typearticle
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMedical educationPsychologyProfessional developmentMedicineNursing

Abstract

fetched live from OpenAlex

Dietitians of Canada (DC) was established in 1997 from the Canadian Dietetic Association and the provincial associations. This project is part of a larger program of work to document the recent history of Canadian dietetic practice, including the professional development (PD) initiatives DC has provided since its inception. The aims of the present study are to synthesize a timeline of PD events since 1993, understand the context that led to their development, and understand their impact on the profession. 13 key informants were recruited by email, of which 11 semi-structured interviews were conducted, and 8 participants provided written contributions. Interview transcripts and written contributions were analyzed thematically, and a final timeline of events was developed. Six themes were found: 1) the use of technology in PD tools, e.g. online courses, Learning on Demand; 2) conferences and workshops , e.g. national conference, Coast-to-Coast workshops; 3) initiatives that placed DC as a leader in health and nutrition, e.g. Practice-based Evidence in Nutrition (PEN); 4) informal discussion about emerging issues in dietetics, e.g. PEN Current Issues, Practice Blog; 5) DC actively sought member input to inform PD strategy, e.g. members issues forums; and, 6) DC PD events demonstrated their support for research and dietetic education, e.g. relationship with CFDR, public health online course. Key concerns for the future included: declining DC membership and funding, and dietetics not keeping pace with other professions on PD. The successes and failures of initiatives in this time period can inform the development of DC’s PD strategy for the coming decades.

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)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.960
Threshold uncertainty score0.287

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0150.004
Scholarly communication0.0040.001
Open science0.0020.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.034
GPT teacher head0.415
Teacher spread0.381 · 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 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

Citations0
Published2024
Admission routes3
Has abstractyes

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