UNCERTAINTY REGULATION, MOTIVATION, AND DAILY LIFE EVENTS ACROSS CULTURES
Bibliographic record
Abstract
The purpose of the present study is to examine in both achievement and social domains how motives predict daily life experiences and how the associations between motives and daily experiences are moderated by uncertainty orientation and country. Participants in China and Canada first participated in a mass-testing session in which their uncertainty orientation, affiliation-related motives, and achievement-related motives were assessed. Then subjects participated in a 2-week daily study session in which they made daily reports of life events. Hierarchical linear modeling was used to predict daily social/achievement events (in level-1) with the individual differences of uncertainty orientation, affiliation/achievement-related motives, and country (in level-2). It was found that affiliation-related motives predicted social events, and achievement-related motives predicted achievement events in given conditions determined by uncertainty orientation, country, or their interaction. The psychological function of fit between individuals’ uncertainty orientation and the culture’s uncertainty-resolving styles is discussed.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".