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Record W2066539338 · doi:10.15288/jsad.2012.73.839

Assessing the Protective Value of Protective Behavioral Strategies

2012· article· en· W2066539338 on OpenAlexaff
Christine Frank, Jennifer Thake, Christopher G. Davis

Bibliographic record

VenueJournal of Studies on Alcohol and Drugs · 2012
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsCarleton University
Fundersnot available
KeywordsHarmMedicineEnvironmental healthConsumption (sociology)Injury preventionPoison controlHuman factors and ergonomicsOccupational safety and healthSuicide preventionAlcohol consumptionHarm reductionPsychologyClinical psychologySocial psychologyAlcoholPublic healthPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: Many students report using strategies believed to reduce risk of harm from consumption of alcohol. The effectiveness of these strategies was tested in this study. METHOD: A sample of 442 undergraduate students (50.5% female) was asked to report how many alcoholic drinks they consumed on a recent drinking occasion, which protective strategies were used, and which harms were experienced. RESULTS: Although reported use of more protective strategies was associated with less consumption, it appeared to be unrelated to harmful consequences. More detailed analyses suggested that only a small subset of strategies (primarily those concerning the manner of drinking) was consistently associated with reduced consumption and/or harms. CONCLUSIONS: The findings cast doubt on the efficacy of protective strategies or at least the validity of the self-report instruments used to assess these strategies.

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)0.003
metaresearch head score (Gemma)0.018
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 score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.091
GPT teacher head0.409
Teacher spread0.318 · 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

Citations36
Published2012
Admission routes1
Has abstractyes

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