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Record W2124098500 · doi:10.1111/jlme.12020

Evaluating Equity Critiques in Food Policy: The Case of Sugar-Sweetened Beverages

2013· article· en· W2124098500 on OpenAlexaff
Anne Barnhill, Katherine F. King

Bibliographic record

VenueThe Journal of Law Medicine & Ethics · 2013
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsEquity (law)Public economicsDistributive justiceSocial equalityEconomicsBusinessMarketingPolitical scienceLaw

Abstract

fetched live from OpenAlex

Many anti-obesity policies face a variety of ethical objections. We consider one kind of anti-obesity policy - modifications to food assistance programs meant to improve participants' diet - and one kind of criticism of these policies, that they are inequitable. We take as our example the recent, unsuccessful effort by New York State to exclude sweetened beverages from the items eligible for purchase in New York City with Supplemental Nutrition Support Program (SNAP) assistance (i.e., food stamps). We distinguish two equity-based ethical objections that were made to the sweetened beverage exclusion, and analyze these objections in terms of the theoretical notions of distributive equality and social equality. First, the sweetened beverage exclusion is unfair or violates distributive equality because it restricts the consumer choice of SNAP participants relative to non-participants. Second, it is disrespectful or violates social equality to prohibit SNAP participants from purchasing sweetened beverages with food stamps. We conclude that neither equity-based ethical objection is decisive, and that the proposed exclusion of sugar-sweetened beverages is not a violation of either distributive or social equality.

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)0.044
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0440.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.006
Insufficient payload (model declined to judge)0.0010.000

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 head0.528
GPT teacher head0.651
Teacher spread0.122 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations23
Published2013
Admission routes1
Has abstractyes

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