<i>Building a Vision of Dietitian Services</i> In Primary Health Care
Bibliographic record
Abstract
PURPOSE: Primary health care (PHC) reform, especially efforts to implement interdisciplinary teams, has implications for dietetic practice. A consistent, clear vision of the registered dietitian's (RD's) role in PHC is needed to develop a successful advocacy agenda. METHODS: The Dietitians of Canada (DC) Central and Southern Ontario Primary Health Care Action Group organized a four-step process to engage dietitians in developing an advocacy agenda for RD PHC services in Ontario. Two facilitated workshops brought together dietitian opinion leaders to enhance the understanding of current roles, find common ground, and develop a shared vision. All DC members were invited to review the draft vision, and feedback was integrated into a revised vision. RESULTS: Registered dietitians saw PHC reform through many lenses, and were uncertain about how reforms would affect their practices. In a national review, the majority of reviewers (approximately 85% of 270) supported the draft vision; additional clarity was needed on resources and the breadth of services that RDs would provide. CONCLUSION: Development of a PHC vision for RDs should be helpful in advocating for dietitian services in PHC.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.066 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.014 | 0.024 |
| Scholarly communication | 0.024 | 0.012 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".