Exploring Vegan Mothers’ Experiences of Making Food Choices for Infants and Young Children
Bibliographic record
Abstract
OBJECTIVE: Our study aimed to explore vegan mothers' experiences and decision-making processes when feeding their children (up to 3 years old). METHODS: We conducted a qualitative photo-elicitation interview study in the United Kingdom. Eight vegan mothers provided 5 photographs of food choices they had made for their children and completed online photo-elicitation interviews to discuss these images. Data were transcribed verbatim and analyzed using reflexive thematic analysis. RESULTS: Five themes were developed: role modeling eating behavior, shared decision-making, nutritional guidance for vegan parents, fear of judgment for being vegan, and desire for convenience. CONCLUSIONS AND IMPLICATIONS: Findings illustrate the complexity of the decision-making process and highlight the need for targeted resources for vegan parents. There is a need for awareness raising and training for health care professionals and the development of vegan-specific child-feeding resources to facilitate the provision of evidence-based nutritional guidance for vegan parents.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".