Data from “Perfectionism, Negative Motives for Drinking, and Alcohol-Related Problems: A 21-day Diary Study”
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Two datasets include self-report data from (a) a 21-day daily diary study (<em>N</em> = 263) and (b) a cross-sectional psychometric study (<em>N</em> = 139) of emerging adult drinkers. Data were collected from two Canadian cities, and represent unique, non-overlapping participants in both datasets. Questionnaires assessed perfectionism, reinforcement sensitivity, big five personality traits, alcohol consumption/problems, binge eating, social support, positive and negative affect, social anxiety, and drinking motives. Daily data were originally analysed using multilevel structural equation modelling and are stored in the Open Science Framework (<a href="https://osf.io/gduy4/" target="_blank">https://osf.io/gduy4/</a>). These data can be used to examine research questions related to personality, emotions, and alcohol consumption, including changes from day-to-day in many variables.
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.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 0.003 |
| 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 it