Virtue Trait by Situation Interactions
Bibliographic record
Abstract
This chapter discusses the contextualization of human traits in social roles. It begins by exploring how personality traits relate to social roles, then it extrapolates those findings related to virtues and discusses theory and research on social roles and virtue traits. The discussion of the social role contextualization is based on identity theory, which explains that social roles are repetitive patterns of action that are included in social structures and result in role identity formation in the individual. The chapter reiterates that up-to-date trait conceptualizations do not view them as simplistic behavioral tendencies that manifest in any social role. Instead, traits are currently understood as influenced by social role expectations. Practical wisdom plays a large part in the expression of virtues through social roles. Practical wisdom adds an element to virtue expression and social roles that is absent in personality research because some individuals see more opportunities for virtue trait expression within a role than others. It then clarifies this theoretical discussion with examples of common role and virtue enactments from the parenting, teaching, and healing roles. It concludes by discussing how a virtue perspective adds important elements (agency, aspiration, and practical wisdom) to the contextualization of traits.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 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".