Mapping the Traits Desired in Followers and Leaders onto Fundamental Dimensions of Social Evaluation
Bibliographic record
Abstract
We applied the social evaluation framework to investigate the traits desired in an “ideal” follower, which were compared to the traits desired in an “ideal” leader. Across three studies and five samples, both differences and similarities in role-specific preferences mapped onto the Vertical-Horizontal dimensions of the social evaluation framework in ways that aligned with the demands of each role. Traits higher on the Horizontal-morality facet (e.g., cooperative, dutiful) and lower on the Vertical-assertiveness facet (e.g., confident, ambitious) differentiated ideal follower preferences from ideal leader preferences. Focusing on the traits most strongly desired in relation to each role, traits that supported social coordination and collective goal attainment (i.e., work ethic, cooperativeness) were prioritized in relation to ideal followers, whereas intelligence was prioritized for ideal leaders. Trustworthiness was equally valued across both roles. Moreover, we differentiated between necessary and luxury traits by adjusting the budget individuals could allocate towards the desired traits. Investments in necessary versus luxury traits further supported the social evaluation framework and highlighted the need to account for the facet-level distinctions within the Vertical (assertiveness, ability) and Horizontal (morality, friendliness) dimensions. Further, these findings were found to be robust across manipulations (e.g., the target’s gender and hierarchical level).
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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 | 0.000 | 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) | 0.001 | 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 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".