Facilitating the Pygmalion effect: The overlooked role of subordinate perceptions of the leader
Bibliographic record
Abstract
For many years, the Pygmalion effect has served as a colourful, conceptual reminder of the power of supervisory expectations in enhancing subordinate performance. However, regardless of the myriad of studies that have sought to replicate this effect and identify its parameters, little attention has actually been paid to the processes underlying this phenomenon. Rather, the existing model implies that the subordinate is an ‘always‐willing’, yet somewhat ‘passive’ recipient of Pygmalion‐oriented leader efforts. Our theoretical paper unpacks the role of subordinate perceptions of the leader and considers how it can influence receptiveness to the leader's Pygmalion‐oriented efforts. By revisiting and building upon the original Pygmalion model, we attempt to enrich our understanding of this phenomenon, as well as to offer insight into why not all Pygmalion leader efforts are equally successful.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".