Relational Humility: Conceptualizing and Measuring Humility as a Personality Judgment
Bibliographic record
Abstract
The study of humility has progressed slowly due to measurement problems. We describe a model of relational humility that conceptualizes humility as a personality judgment. In this set of 5 studies, we developed the 16-item Relational Humility Scale (RHS) and offered initial evidence for the theoretical model. In Study 1 (N = 300), we developed the RHS and its subscales—Global Humility, Superiority, and Accurate View of Self. In Study 2, we confirmed the factor structure of the scale in an independent sample (N = 196). In Study 3, we provided initial evidence supporting construct validity using an experimental design (N = 200). In Study 4 (N = 150), we provided additional evidence of construct validity by examining the relationships between humility and empathy, forgiveness, and other virtues. In Study 5 (N = 163), we adduced evidence of discriminant and incremental validity of the RHS compared with the Honesty-Humility subscale of the HEXACO–PI (Lee & Ashton, 2004 Lee, K. and Ashton, M. C. 2004. Psychometric properties of the HEXACO personality inventory. Multivariate Behavioral Research, 39: 329–358. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]).
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".