Emotionally expressive interdependence in Latin America: Triangulating through a comparison of three cultural zones.
Bibliographic record
Abstract
Evidence suggests that Latin Americans display elevated levels of emotional expressivity and positivity. Here, we tested whether Latin Americans possess a unique form of interdependence called expressive interdependence, characterized by the open expression of positive emotions related to social engagement (e.g., feelings of closeness to others). In Study 1, we compared Latin Americans from Chile and Mexico with European Americans in the United States, a group known to be highly independent. Latin Americans expressed positive socially engaging emotions, particularly in response to negative events affecting others, whereas European Americans favored positive socially disengaging emotions, such as pride, especially in response to personally favorable circumstances. Study 2 replicated these findings with another group of Latin Americans from Colombia and European Americans in the United States. Study 2 also included Japanese in Japan, who expressed positive emotions less than Latin and European Americans. However, Japanese displayed a higher tendency to express negative socially engaging emotions, such as guilt and shame, compared to both groups. Our data demonstrate that emotional expression patterns align with overarching ethos of interdependence in Latin America and Japan and independence among European Americans. However, Latin Americans and Japanese exhibited different styles of interdependence. Latin Americans were expressive of positive socially engaging emotions, whereas Japanese were less expressive overall. Moreover, when Japanese expressed emotions, they emphasized negative socially engaging emotions. Implications for theories of culture and emotion are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".