Mothers of children with food allergies report poorer perceived life status which may be explained by limited career choices
Bibliographic record
Abstract
Pediatric food allergy is associated with direct, indirect and intangible costs. However, it remains unclear if intangible costs of pediatric food allergy influence parental career choices. Using data from 63 parents whose children had been diagnosed by a pediatric allergist with food allergy, we sought to (a) establish perceived life status of families with a food allergic child, and (b) to describe any career limitations viewed as attributable to food allergy. Compared to responding parents whose children had one to two food allergies, those with three or more food allergies had significantly poorer perceived life status (ß - 0.74; 95%CI - 1.41; - 0.07; p < 0.05). Overall, 14.3% of parents (all mothers) reported career limitations due to food allergy. Two of the 7 mothers (28.6%) who reported career limitations due to their child's food allergy fell below Statistics Canada cut-off for low-income, after tax dollars (LIM-AT). One of the three mothers who had changed jobs because of their child's food allergy was below the LIM-AT. No fathers reported food allergy-related career limitations. In conclusion, mothers of children with multiple food allergies reported worse perceived life status that may be partly explained by food allergy-related career limitations.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".