Implicit and Explicit Alcohol‐Related Cognitions
Bibliographic record
Abstract
This article presents the proceedings of a symposium at the 2001 RSA Meeting in Montreal, Canada organized by Reinout W. Wiers and Alan W. Stacy. The purpose of the symposium was to present recent applications of implicit cognitive processing theory to alcohol research. Basic cognitive research has demonstrated that implicit cognition influences memory and behavior without explicit recall or introspection. The presentations from this symposium show that implicit cognition approaches yield new insights into understanding drinking motivation. The presentations were: (1) An introduction by Alan W. Stacy; (2) Implicit cognition and alcohol use. Involvement of other variables? (Susan L. Ames); (3) Alcohol expectancies and the art of implicit priming (Jane A. Noll); (4) Parental alcoholism and the effects of alcohol on semantic priming (Michael A. Sayette); (5) Implicit arousal and explicit liking of alcohol in heavy drinkers (Reinout W. Wiers); and (6) Negative affective cues and associative cognition in problem drinkers (Martin Zack). Comments were provided by the discussant Marvin Krank. The presented studies demonstrated that: (1) implicit memories of alcohol associations are powerful predictors and cross-sectional correlates of alcohol use; (2) implicit retrieval processes influence alcohol outcome expectancies and alcohol consumption; (3) alcohol consumption influences implicit memory processing; (4) heavy drinkers reveal different affective responses in implicit and explicit tasks; and (5) negative affect exerts an implicit priming effect for alcohol associations in problem drinkers. These findings illustrate the importance of implicit cognition in understanding alcohol abuse and demonstrate the potential of the theoretical framework for more widespread application across a variety of areas of alcohol research, including diagnostics for the risk of alcohol abuse, treatment, and prevention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".