Low relational mobility leads to greater motivation to understand enemies but not friends and acquaintances
Bibliographic record
Abstract
Enemyship occurs across societies, but it has not received as much attention as other types of relationships such as friendship in previous research. This research examined the influence of relational mobility on people's motivation to understand their personal enemies by measuring different dependent variables across three studies. First, a cross-cultural comparison study found that Hong Kong Chinese, from a low-relational-mobility society, reported a stronger desire to seek proximity to enemies relative to European Canadians, from a high-relational-mobility society (Study 1). To test causality, two manipulation studies were conducted. Participants were presented with images of co-workers, including enemies, friends, and acquaintances, in a hypothetical company. The results showed that the participants who perceived lower relational mobility paid more attention to their enemies in an eye-tracking task (Study 2) and had a higher accuracy rate for recognizing the faces of the enemies in an incidental memory test (Study 3). In contrast, the influence of relational mobility on motivation to understand friends and acquaintances was minimal. Implications for research on interpersonal relationships and relational mobility are 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".