Bibliographic record
Abstract
There is an unacknowledged disagreement on what kind of dialogue best supports democracy. Many view democracy as analogous to a law court and so view “democratic dialogue” as a contest between competing advocates who have acquired the kind of “steel trap” critical thinking skills that are ideal for winning in the external marketplace of ideas. Others assume that the propensity to seriously reflect on opposing viewpoints within the minds of individuals is ideal for democratic maintenance. It will be argued here that our love affair with “critical thinking” that tends to support an external battle of ideas harms democracy. It will be argued that the complexity of our common humanity, the complexity of our form of governance, the complexity of the approaches needed to face wicked problems, and the complexity of the internal engine of personal development requires that we learn to readily engage in open truth-seeking dialogue with those who hold opposing viewpoints and in so doing, enhance the dimensionality through which we view the world. With regard to the educational implications, this suggests that, since engaging in dialogue across difference is the essence of the pedagogical framework that anchors Philosophy for Children, Philosophy for Children ought to be embraced as an essential component of any educational enterprise that views cultivating democratic citizenship as part of its mandate.
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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.039 |
| Scholarly communication | 0.010 | 0.021 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 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".