“It's not you, it's me”: transformational leadership and self‐deprecating humor
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
Purpose The purpose of this paper is to investigate leaders’ use of humor as an expression of how they value themselves relative to others. The paper suggests that humor can minimize or exacerbate the status differences between leaders and followers. The paper hypothesizes that leaders’ use of self‐ or in‐group‐deprecating humor would be positively associated with ratings of transformational leadership as they minimize those distinctions, whereas leaders’ use of aggressive humor would be negatively associated with ratings of transformational leadership because it exacerbates status distinctions. Design/methodology/approach A total of 155 undergraduates (58 males, 97 females; M age=20 years, SD =1.31) were assigned randomly to one of four conditions, each depicting a different type of humor in a leader's speech. Findings Leaders using self‐deprecating humor were rated higher on individualized consideration (a factor of transformational leadership) than those that used aggressive humor. Research limitations/implications The authors encourage future field research on the role of humor as an expression of leaders’ self‐ versus other‐orientation. Originality/value Humor and work might seem inconsistent, but this study demonstrates how leadership can use humor to improve leader‐follower relationships. Furthermore, it contributes to our understanding of self‐deprecating humor which has received scant attention relative to other forms of humor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.009 | 0.002 |
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