JOURNAL Uskul 10.1177/0022022103262243 et al. OF / CULTURE, CROSS-CULTURAL CLOSENESS, PSYCHOLOGY AND INTERDEPENDENCE ARTICLE INTERDEPENDENCE AS A MEDIATOR BETWEEN CULTURE AND INTERPERSONAL CLOSENESS FOR EURO-CANADIANS AND TURKS
Bibliographic record
Abstract
The present study examines cross-cultural differences in interpersonal closeness to different people and whether these differences can be explained by independent and interdependent self-construal. Turkish and Euro-Canadian samples of university students were asked to indicate how close they feel and how close they ideally would like to be to family members, romantic partners, friends, and acquaintances. As predicted, Turkish participants scored higher on interdependent self-construal, whereas there was no culture difference on independent self-construal scores. Turkish participants rated their actual and ideal closeness with others higher than Euro-Canadian participants did. Both Turkish and Euro-Canadian participants reported feeling closest and ideally wanting to be closest to their romantic partner, and then to their families and friends, followed by acquaintances. Turkish participants desired more closeness with family members and acquaintances than Euro-Canadian participants did. Interdependent self-construal was found to partially mediate the relationships between culture and actual closeness scores for family, friends, and acquaintances and between culture and ideal scores for family and acquaintances.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.897 | 0.744 |
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".