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Record W2249755711

Paternalistic Manipulation through Pictorial Warnings: The First Amendment, Commercial Speech, and the Family Smoking Prevention and Tobacco Control Act

2012· article· en· W2249755711 on OpenAlexaboutno aff
Stephanie Bennett

Bibliographic record

VenueSSRN Electronic Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicLaw, Rights, and Freedoms
Canadian institutionsnot available
Fundersnot available
KeywordsCommercial speechScrutinyTobacco controlSupreme courtTobacco productBusinessAdvertisingSmokeless tobaccoPaternalismLawSurgeon generalPolitical scienceFirst amendmentMedicineEnvironmental healthPublic health
DOInot available

Abstract

fetched live from OpenAlex

Beginning in 2012, the Family Smoking Prevention and Tobacco Control Act will require pictorial warning labels on both regular and smokeless tobacco products. The warnings contain textual statements encouraging smoking cessation as well as graphic images depicting cadavers, crying children, and cancerous lesions. As presently required by the U.S. Food and Drug Administration, the warnings both unconstitutionally compel and suppress commercial speech. The warnings violate the First Amendment under every existing Supreme Court standard for evaluating commercial speech regulations: the “reasonable relation” standard of Zauderer v. Office of Disciplinary Counsel; the strict scrutiny standard of Wooley v. Maynard; and the intermediate scrutiny standard for commercial speech disclosure and suppression expressed in Central Hudson Gas & Electric Corporation v. Public Service Commission. Rather than tax tobacco products, ban tobacco products, use removable warnings already adopted by many countries including Canada, or implement educational programs to inform consumers about the dangers of using tobacco products, the FDA has instead resorted to paternalistic manipulation of consumers and infringement upon the First Amendment rights of tobacco manufacturers.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.278
Teacher spread0.257 · 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.

Study designTheoretical or conceptual
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

Citations0
Published2012
Admission routes1
Has abstractyes

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