“Just Looking Out for Us”: Understanding the Role of Ingroup Prototypes in Follower Support of Self-serving Leadership
Bibliographic record
Abstract
Much of the research on negative leader behaviour focuses on the antecedents and consequences of said behaviour; follower reactions to this behaviour are less understood. The present research explores how social categorization motivates followers to support self-serving leaders. Building on social identity theories, I hypothesize that followers perceive self-serving, but prototypical leaders to be more group-serving than non-prototypical self-serving leaders. Additionally, I propose that followers make implicit calculations of how much they expect to benefit (i.e., subjective expected utility) and this, along with the outcome of the leader’s actions (i.e., experienced utility), will also impact follower perceptions of the leader’s effectiveness and their willingness to support that leader. The results of three studies support that leader prototypicality leads to follower assumptions of a leader’s group-serving motivations, which then increases perceptions of leader effectiveness and followers’ support of the leader. This relationship is moderated by subjective expected utility and experienced utility.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".