An Examination of the Influence of Implicit Theories, Attribution Styles, and Performance Cues on Questionnaire Measures of Leadership
Bibliographic record
Abstract
We examined the direct and interactive effects of respondents’ implicit leadership theories (ILTs), attribution styles, and performance cues on leadership perceptions. After first assessing respondents’ implicit leadership theories and attribution styles, the participants were randomly assigned to one of nine performance cue conditions ([leader performance: low vs. average vs. high] × [follower performance: low vs. average vs. high]), observed the same leader’s behavior via video, and rated the leader by completing three leadership questionnaires. The results supported the notion that these three components of information have both direct and interactive effects on leadership perceptions as measured by the questionnaires. The three components of information accounted for about 10% of the variance in the three questionnaires. The results contribute to theories of information processing by demonstrating how ILTs, attribution styles, and performance cues interact to predict leadership perceptions. Implications regarding the meaningfulness, construct validity, and utility of leadership scales are discussed.
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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 | 0.003 |
| 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 | 0.002 |
| 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".