“I want to really crack this nut”: an analysis of parent-perceived policy needs surrounding food allergy
Bibliographic record
Abstract
BACKGROUND: In Canada, anaphylaxis-level food allergy constitutes a legal disability. Yet, no nationwide policies exist to support families. We sought to understand what parents of children with food allergy perceive as the most pressing food allergy-related policy concerns in Canada. METHODS: Between March-June 2019, we interviewed 23 families whose food allergic children (N = 28mean age 7.9 years) attending an allergy clinic in Winnipeg, Canada. Interviews were audio-recorded, transcribed and analyzed using content analysis. RESULTS: Over 40% of children had multiple food allergies, representing most of Health Canada's priority allergens. We identified four themes: (1) High prevalence. High priority?. (2) Food labels can be misleading, (3) Costs and creative ideas, and (4) Do we have to just deal with the status quo around allergies? CONCLUSION: Food allergy ought to be a national policy priority, to improve the process for precautionary labelling, to improve funding, educational tools access to care, and knowledge of current allergy guidelines.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".