Drinking motives and drinking behaviors in romantic couples: A longitudinal actor-partner interdependence model.
Bibliographic record
Abstract
= 2.4). Actor-partner interdependence models using multilevel path-analysis with indistinguishable dyads were conducted, with each motive predicting drinking quantity and frequency. There were significant actor effects for social and enhancement motives; moreover, changes in a partner's enhancement and social motives predicted change in the individual's drinking quantity during any given week, but only averaged partners' enhancement motives predicted the individual's drinking frequency. Coping-with-anxiety motives had significant actor effects when predicting averaged quantity and frequency; moreover, changes in partners' coping-with-anxiety motives predicted changes in drinking quantity. Enhancement and social motives of the partner influenced the drinking quantity and frequency of the actor by way of influencing the actor's enhancement and social motives. Intervention efforts targeting both members of a romantic dyad on their reasons for drinking should be tested for preventing escalations in either member's drinking behavior. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".