Сulture, Stress and Coping: Socio-Cultural Context Influence on Coping Types among Russians
Bibliographic record
Abstract
The paper presents a new psychometric adaptation of the cross-cultural coping scale for the Russian-speaking sample (Cross-Cultural Coping Scale by B. Kuo et al., 2006, Canada: Kuo, Roysircar, Newby-Clark, 2006) and a research made with its help, answering the questions: Do Russians cope with stress? What are socio-cultural contexts of coping in the time of cultural transition? The tool explores the influence of the socio-cultural context on the respondents’ choice between three types of coping. The influence of cultural context on coping and its intensity has been confirmed in this study. The situational context has the greatest impact on the choice of collective coping among Russian respondents. In general Russians evaluate more acute and important stress in the situations Health/Illness than in Job/Career context. There are obvious relations between the choice of avoidance coping and the respondents’ age in the career scenario. In both contexts people use engagement coping (self activity) more actively and are less inclined to avoid difficulties. The choice of coping type is affected by a group of factors: self-concept traits (independent or interdependent selves), stress level, type of values, life satisfaction.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".