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
Interest in the topic of wisdom-focused education has so far not resulted in empirically validated programs for teaching wisdom. To start filling this void, we explore the emerging empirical evidence concerning the fundamental elements required for understanding how one can foster wisdom, with a particular focus on wise reasoning. We define wise reasoning through a combination of intellectual humility, recognition of world in flux/change, open-mindedness to diverse viewpoints, and search for compromise/integration of diverse perspectives. In this article, we review evidence concerning how wise reasoning can be facilitated through experiences, teaching materials, environments and cognitive strategies. We also focus on educators, reviewing emerging evidence on how the process of explaining and guiding others impacts one’s wisdom. We conclude by discussing the development of wisdom-focused education, proposing that greater attention to the situational demands and the variability in wisdom-related characteristics across social contexts should play a critical role in its development.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it