Personal and Situational Antecedents of Workers’ Implicit Leadership Theories: A Within-Person, Between-Jobs Design
Bibliographic record
Abstract
Despite a flourishing literature demonstrating the consequences of implicit leadership theories (ILTs) for workplace phenomena, relatively little is known about the antecedents of ILTs, particularly those that are malleable or can be changed to shape ILTs. In two studies of dual-job holders, which allows for the modeling of between- and within-person predictors, I examined the extent to which workers’ ILTs were stable versus dynamic across work contexts. In line with connectionist perspectives, trait identities, a personal factor, promoted stability in ILTs across situations in both studies, whereas there was some limited evidence that organizational culture, a situational factor, only predicted ILTs within a given job context. Furthermore, the relationship between independent identity and ILTs differed when examining workers’ typical versus ideal leadership conceptualizations. Implications for future research on ILTs are also 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".