MétaCan
Menu
Back to cohort
Record W2076701563 · doi:10.1353/aad.2007.0024

Do Deaf and Hard of Hearing Youth Need Antitobacco Education?

2007· article· en· W2076701563 on OpenAlexaboutno aff
Barbara Berman, Leanne Streja, Coen Bernaards, Elizabeth Eckhardt, Heidi B Kleiger, Lauren Maucere, Glenn Wong, Shari L. Barkin, Roshan Bastani

Bibliographic record

VenueAmerican annals of the deaf · 2007
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Ethnic groupTobacco usePeer pressureYouth smokingMedicinePsychologySmoking preventionAudiologyEnvironmental healthTobacco controlPublic healthSocial psychologyPopulationNursingGeography

Abstract

fetched live from OpenAlex

Little research has focused on tobacco use among deaf and hard of hearing youth. Findings are reported from a first-ever tobacco-related survey, completed by 226 California middle and high school students using either a written questionnaire or the Interactive Video Questionnaire, an interactive multimedia computer video technology. Rates for current smoking (3.1%), ever smoking (45.1%), and multiple types of tobacco use (10.6%) were found to be lower than among high school students generally; mainstreamed students were likelier to have ever tried smoking than their deaf school peers (57.8% vs. 31.8%). No statistically significant associations were found between ever smoking and race/ethnicity, gender, school performance, or prelingual vs. postlingual deafening; a quarter of the sample experienced occasional peer pressure to use tobacco products. Tobacco use covariates, exposure to cigarette marketing and antismoking programming, and tobacco education needs of deaf and hard of hearing youth are discussed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.088
GPT teacher head0.392
Teacher spread0.304 · 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

Citations12
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueAmerican annals of the deafSame topicHearing Impairment and CommunicationFrench-language works237,207