Bibliographic record
Abstract
Abstract The last thirty years has seen a resurgence of interest in virtue among philosophers, psychologists, and educators. As is often the case with interdisciplinary endeavors, this renewed interest in virtue faces an important challenge—namely, successfully standing up to the requirements imposed by different disciplinary standards. For virtue, this means developing an account that practitioners from multiple disciplines will find sufficiently rigorous, substantive, and useful. Our volume was born in response to this interdisciplinary challenge. Its objective here is twofold. First, drawing on Whole Trait Theory in psychology and Aristotelian virtue ethics, it offers accounts of virtue and character that are both philosophically sound and psychologically realistic—and thus, able to be meaningfully operationalized into empirically measurable variables. Second, it offers a range of strategies for how virtue and character (so conceived) can be systematically measured, relying on the insights from the latest research in personality, social, developmental, and cognitive psychology, and psychological science more broadly. It thereby seeks to contribute to the emerging science of the measurement of virtue and character.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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; both teacher heads agree on what is shown here.
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".