Knowledge and Perceptions of Plant-Based Diets among Competitive and Recreational Athletes
Bibliographic record
Abstract
Little is known about athletes’ perceptions of emerging dietary guidance on plant-based diets (PBD). To explore knowledge and perceptions of PBD among competitive and recreational athletes, an online survey was developed, pilot tested, and sent via email to athletes recruited from 2 Canadian post-secondary institutions. Survey questions explored athletes’ understanding and views of the proposed Canadian dietary guidelines emphasizing plant-based proteins. Data were analyzed using grounded theory approaches. Forty-eight athletes participated in the survey. Two major themes emerged: (i) athletes had mixed perceptions of plant-based eating (PBE) and (ii) athletes associated PBE with broader food system concerns. Athletes have the potential to be important advocates of healthy and sustainable eating among peer groups and the general public. For effective promotion of PBE, the unique nutrient requirements and performance goals of athletes should be considered. Messaging to encourage a flexible rather than strict view of PBD may be a more feasible and acceptable approach when working with athletes.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".