Beliefs and behaviours associated with vegetarian, vegan, and gluten-free diets among Canadians capable of bearing children
Bibliographic record
Abstract
There is increased interest in self-selected exclusionary diet patterns, specifically vegetarian, vegan, and gluten-free (GF) diets, but there is a lack of research exploring the beliefs and behaviours surrounding these diets in Canadians capable of bearing children (CCBC). The goal of this study was to explore the beliefs and behaviours of CCBC who follow vegetarian, vegan, and/or GF diets using mixed methods. A self-administered online Qualtrics™ survey containing 102 questions was conducted using open text and closed format questions. Continuous variables were summarized using mean and standard deviation while percentages were used to summarize categorical variables. Qualitative data was analysed using thematic analysis. A total of 271 CCBC between 18-45 years of age were analysed, with 27%, 22%, and 3.7% indicating they followed a vegan, vegetarian, and/or GF diet, respectively. Three main themes emerged that influenced CCBC beliefs about their chosen diet. The belief that these diets are healthy or could impart health in some way, was the main reason for following their chosen diet, especially in those who identified as vegetarian. Ethical/moral concerns, primarily around animal welfare and the environment, was the second theme for following their chosen dietary pattern, especially amongst those who identified as vegan. Perception of social judgement in the forms of criticism, guilt, and isolation were noted by some CCBC, with family, friends, and colleagues interacting differently with them because of their dietary choices. These findings serve to enhance our understanding of the beliefs and behaviours of CCBC who choose to follow exclusionary diets.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".