Personality Differences in Drinking Contexts, Consequences, and Alcohol Reporting Accuracy: The Role of Extraversion and Neuroticism
Bibliographic record
Abstract
Alcohol use is commonplace on university campuses, with 79.2% of students consuming alcohol each year in Canada.Extraversion, a personality trait consisting of high sociability, is a strong predictor of alcohol use and problems in university students.Neuroticism, a personality trait comprising emotional instability, is associated with alcohol problems but not heavy alcohol use.Study 1 investigated whether students higher in neuroticism consumed more alcohol in response to perceived stress, and whether students higher in extraversion had elevated alcohol consumption regardless of context.Study 1 investigated first-time, first-year undergraduate students who completed 12 daily diary surveys in their first semester.Students reduced their alcohol use in response to substance-related diagnosis in Canada (Statistics Canada, 2013; Tjepkema, 2004).Alcohol use disorder is characterized by a cluster of dysfunctional behaviours caused by dependence on alcohol, such as impaired control, social impairment, and alcohol tolerance and withdrawal (American Psychiatric Association, 2013).Diagnosis typically relies on social dysfunction and not exclusively heavy alcohol use; although many university students engage in heavy drinking, this alone is not sufficient for a clinical diagnosis.However, heavy alcohol use coincides with numerous sub-clinical consequences that can still negatively impact quality of life or increase risk for comorbid mental health issues.
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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 | 0.005 |
| 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".