Toward the Measurement of Perceived Leader Integrity: Introducing a Multidimensional Approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Even though books and articles in the popular business press consider leader integrity an essential quality of effective leaders, business research has yet to establish firmly the nature of leader integrity and its causes and effects. One reason why integrity research may still be in its early stages is the failure of the literature to describe leader integrity fully and to use such descriptions to develop construct valid measures. Drawing on implicit leadership theory, which states that followers categorize leaders based on multiple traits, attributes and past experiences, this article argues for a multidimensional approach to a leader integrity definition and measurement. The article offers two proof-of-concept tests of how followers may make attributions of leader integrity. Results support two hypotheses suggesting that when making attributions of leader integrity followers use complex information that comes from diverse sources and the information may include judgements of both the moral values of leaders and whether the leader espouses and enacts these values consistently.
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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 | 0.007 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 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 it