Understanding Prosocial and Antisocial Behaviors: The Roles of Self-Focused and Other-Focused Motivational Orientations
Bibliographic record
Abstract
We examine how individual differences in self-focused and other-focused orientations relate to prosocial (e.g., helping, volunteerism) and antisocial (e.g., theft, violence) behaviours/attitudes. Using four datasets (total N = 176, 216; across 78 countries), we find that other-focused orientations (e.g., socially focused values, intimacy motivation, compassionate/communal traits) generally relate positively to prosocial outcomes and negatively to antisocial outcomes. These effects are highly consistent cross-nationally and across multiple ways of operationalizing constructs. In contrast, self-focused orientations (e.g., personally focused values, power motivation, assertive/agentic traits) tend to relate positively to both antisocial and prosocial outcomes. However, associations to prosocial outcomes vary substantially across nations and construct operationalizations. Overall, the effects of other-focused orientations are consistently larger than those of self-focused orientations. We discuss the implications of these findings for interventions that target self-focused and other-focused motivations to influence prosocial and antisocial outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".