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Record W2101532367 · doi:10.1177/1059840510364844

Ethical Principles as a Guide in Implementing Policies for the Management of Food Allergies in Schools

2010· article· en· W2101532367 on OpenAlexaff
Jason Behrmann

Bibliographic record

VenueThe Journal of School Nursing · 2010
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsConfidentialityContext (archaeology)Public relationsBusinessPublic healthAnaphylaxisEmpowermentFood allergyPreparednessBioethicsPublic policyEnvironmental healthPolitical scienceMedicineAllergyNursingImmunologyLaw

Abstract

fetched live from OpenAlex

Food allergy in children is a growing public health problem that carries a significant risk of anaphylaxis such that schools and child care facilities have enacted emergency preparedness policies for anaphylaxis and methods to prevent the inadvertent consumption of allergens. However, studies indicate that many facilities are poorly prepared to handle the advent of anaphylaxis and policies for the prevention of allergen exposure are missing essential components. Furthermore, certain policies are inappropriate because they are blatantly discriminatory. This article aims to provide further guidance for school health officials involved in creating food allergy policies. By structuring policies around ethical principles of confidentiality and anonymity, fairness, avoiding stigmatization, and empowerment, policy makers gain another method to support better policy making. The main ethical principles discussed are adapted from key values in the bioethics and public health ethics literatures and will be framed within the specific context of food allergy policies for schools.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.405
Teacher spread0.347 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations35
Published2010
Admission routes1
Has abstractyes

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