When to Use Your Head and When to Use Your Heart
Bibliographic record
Abstract
Four studies explored whether perspective-taking and empathy would be differentially effective in mixed-motive competitions depending on whether the critical skills for success were more cognitively or emotionally based. Study 1 demonstrated that individual differences in perspective-taking, but not empathy, predicted increased distributive and integrative performance in a multiple-round war game that required a clear understanding of an opponent's strategic intentions. Conversely, both measures and manipulations of empathy proved more advantageous than perspective-taking in a relationship-based coalition game that required identifying the strength of interpersonal connections (Studies 2-3). Study 4 established a key process: perspective-takers were more accurate in cognitive understanding of others, whereas empathy produced stronger accuracy in emotional understanding. Perspective-taking and empathy were each useful but in different types of competitive, mixed-motive situations-their success depended on the task-competency match. These results demonstrate when to use your head versus your heart to achieve the best outcomes for oneself.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".