The Nature of Competition in Dietetics Education: A Narrative Review
Bibliographic record
Abstract
The impact on student development associated with being part of a competitive program is an emerging finding in dietetics research. As such, a narrative review of relevant literature was conducted pertaining to competition in post-secondary programs and the educational experience of students with respect to developing a career in dietetics. The review was guided by 2 questions: How is competition experienced by students? What strategies can reduce competition among dietetics students within the educational experience? A refined literature screening process justified including 32 articles in the review. The overall review findings suggested that, across dietetics programs, the outcomes of competition negatively impacted students' personal identity, motivation in the learning process, and involvement behaviours, including collaboration among students, participation in academic opportunities, and student relationships with faculty. The implementation of strategies conducive to addressing the effects of excessive competition and building a supportive academic environment, for example increasing collegiality and engaging students in intrinsic learning, are important for continued growth of the dietetics profession. Educators can reflect on the complex nature of competition and how the effects of excessive competition may be in opposition with the competencies that students are expected to develop as professionals.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".