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Record W2897632130 · doi:10.1186/s13223-018-0273-6

The law of food allergy and accommodation in Canadian schools

2018· review· en· W2897632130 on OpenAlexafffundvenueabout
Blake Murdoch, Eric M. Adams, Timothy Caulfield

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2018
Typereview
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsUniversity of Alberta
FundersAllerGenFood Allergy CanadaUniversity of AlbertaMcMaster University
KeywordsLegislationCharterReasonable accommodationHuman rightsPolitical scienceLawFood allergyMedicineAllergy

Abstract

fetched live from OpenAlex

BACKGROUND: There is ongoing controversy surrounding the appropriate standards and limits of accommodation of children with food allergies in schools. We identify and explain how relevant Canadian common law, legislation, constitutional law and human rights policy can inform future school policy around allergy, disability and food bans. MAIN BODY: applies to governmental laws or policies, including the policies of schools, and grants every individual the right to freedom from discrimination based on, among other things, disability. Canadian constitutional and human rights law define disability broadly including perceived disabilities. Provincial human rights tribunals in both Ontario and BC have explicitly found allergy to be a disability requiring accommodation, even in cases not involving anaphylaxis risk. However, the cases most pertinent to the scenarios faced by schools have found that food bans may not be required, due to recent scientific evidence that they do not render allergy sufferers safer. CONCLUSION: and human rights legislation, despite the fact that higher courts have not definitively ruled on the matter. Accordingly, schools must make careful decisions about how to deal with life-threatening allergies among their students. Food bans are generally not legally necessary, and, in the absence of new legislation, are only likely to become so if sufficient scientific evidence demonstrates that they increase safety for students. School policies should be substantially informed by evidence-based research in order to ensure ongoing congruence with human rights law.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.320
Threshold uncertainty score0.643

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0020.005
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.059
GPT teacher head0.389
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations11
Published2018
Admission routes4
Has abstractyes

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