Bibliographic record
Abstract
Predictability tends to elicit a clear behavioral response and hence, for humans, it is a basic need in both their physical and social environment. However, the liberty inherent in a democratic society makes life essentially unpredictable and, in this sense, may create a sense of unease in its citizens who then may strive for stability in dogma. Dogmatism, however, is antithetical to democratic liberty. Once we take up this Janus focus of democracy, i.e., that it can lead to the best of times and the worst of times, it becomes clear that, to preserve democracy, we must educationally invest in anchoring predictability in the individuals rather than in the environment in which they subsist, and that we can achieve this (i) by explicating clearly to young citizens that the chaos of reasons doing battle is fundamentally different from the chaos of persons doing battle, and (ii) by shoring up what Charles Taylor (1989) calls strong evaluation, i.e., shoring up the ability to confidently and independently judge the worth of any proposed action and how it reflects on one’s ideal self. We will argue, perhaps counterintuitively, that this confidence in the predictability of one’s capacity for independent thought can best be achieved through an education that affords frequent engagement in “truth-seeking” interpersonal inquiries of the sort frequently utilized the practice of Philosophy for Children, but one that is buttressed by reinforcing the belief in Truth and, as well, by exposing participants to “truth-seeking” interpersonal dialogues that are focused on genuine, relevant, and difficult moral quandaries.
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 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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.037 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".