Transforming followers’ value internalization and role self-efficacy: Dual processes promoting performance and peer norm-enforcement.
Bibliographic record
Abstract
We develop a model in which transformational leadership bolsters followers' internalization of core organizational values, which in turn influences their performance and willingness to report peers' transgressions. The model also specifies a distinct process wherein transformational leadership enhances follower performance by promoting followers' role self-efficacy. We tested the model on 2 large units (i.e., companies) of soldiers undergoing training and socialization. The study bracketed changes in soldiers' internalization of the organizational values and role self-efficacy over a 14-week period. The results support the widely held but empirically unestablished views that transformational leadership promotes change in value internalization and that this partially explains its influence on follower performance. Findings also indicate a distinct intervening process through which transformational leadership promotes performance by enhancing followers' beliefs in their own capabilities (i.e., self-efficacy). This research thus shows that 2 key processes both contribute to the understanding of how transformational leadership transforms followers and influences their behavior.
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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 | 0.006 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".