Individual Character: Towards Empirical Investigation
Bibliographic record
Abstract
The study of individual character is an essential area for organizational research as it is instrumental in ensuring ethical behavior at individual and organization level. However it is observed in the literature that this area has been largely untapped and especially moral and social dimensions of character have been ignored in contemporary studies. Further, it is observed that character and related terms, i.e. virtues, morality, ethos and values have been widely used interchangeably due to conceptual ambiguity (the ontological basis) and certain instruments used for empirical investigations potentially suffer due to methodological ambiguity (the epistemological basis) of the construct. In this paper, we have formulated a conceptually sound definition which provides a clear direction for future empirical investigations and facilitates to differentiate individual character from other related terms. Finally, we propose certain missing and new dimensions of individual character and recommend promising research directions in order to further expand content validity of the construct.
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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 | 0.041 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.011 | 0.023 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".