Nonverbal Displays of Shame Predict Relapse and Declining Health in Recovering Alcoholics
Bibliographic record
Abstract
Public shaming has long been thought to promote positive behavioral change. However, studies suggest that shame may be a detrimental response to problematic behavior because it motivates hiding, escape, and general avoidance of the problem. We tested whether shame about one’s past addictive drinking (measured via nonverbal displays and self-report) predicts future drinking behaviors and changes in health among newly recovering alcoholics (i.e., sober < 6.5 months; N = 105; Wave 2, n = 46), recruited from Alcoholics Anonymous meetings. Results showed that nonverbal behavioral displays of shame expressed while discussing past drinking strongly predicted (a) the tendency to relapse over the next 3 to 11 months, (b) the severity of that relapse, and (c) declines in health. All results held controlling for a range of potential confounders (e.g., alcohol dependence, health, personality). These findings suggest that shame about one’s problematic past may increase, rather than decrease, future occurrences of problem behaviors.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".