Leaders' and Followers' Social Rank Styles Interact to Predict Group Performance
Bibliographic record
Abstract
In the current study we extended the research of Zuroff, Fournier, Patall, and Leybman (2010) who found that individuals differ in their use of dominant leadership (DL), coalition building (CB), and ruthless self-advancement (RSA) when trying to secure rank among peers. In this study we examined whether the interaction of leaders' and followers' social rank styles, composed of these 3 dimensions, would influence group performance. Groups of 4 undergraduates were asked to write an article under the randomly assigned leadership of 1 group member. Hierarchical regression revealed that under leaders high in RSA, group performance was weaker when followers were high in RSA and stronger when followers were low in CB. However, under leaders high in CB, performance was stronger when followers where either high in CB or high in RSA.
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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 | 0.001 | 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".