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Record W2062510446 · doi:10.1300/j029v16n03_05

Can First and Second Grade Students Benefit from an Alcohol Use Prevention Program?

2007· article· en· W2062510446 on OpenAlexaff
Mary Lou Bell, Alison Padget, Tara Kelley‐Baker, Raamses Rider

Bibliographic record

VenueJournal of Child & Adolescent Substance Abuse · 2007
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsAlcohol abusePsychologyAlcoholDrunk drivingSuicide preventionInjury preventionEnvironmental healthPoison controlMedical educationMedicinePsychiatry

Abstract

fetched live from OpenAlex

Protecting You/Protecting Me (PY/PM) is a classroombased, alcohol use prevention and vehicle safety program for elementary students from first through fifth grades developed by Mothers Against Drunk Driving (MADD). PY/PM is one of the first alcohol prevention programs to target children as early as first grade. The focus of this study is on the youngest students receiving PY/PM, the first and second graders, who were surveyed over a three-year period. Results indicate that, relative to comparison students from matched classes, PY/PM students increased their knowledge of vehicle safety, media awareness, growth and development, and dangers of alcohol to young persons. This study demonstrates that despite the inherent difficulties of surveying very young children, these children can benefit from an alcohol use prevention program that is carefully designed, implemented, and evaluated.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.028
GPT teacher head0.319
Teacher spread0.291 · 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 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

Citations7
Published2007
Admission routes1
Has abstractyes

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