Learning to be Moved: The Modes of Democratic Responsiveness
Bibliographic record
Abstract
Being responsive to the experiences, ideas, and stories of others is an essential trait for democratic citizens. Responsiveness promotes the general welfare, it shows respect for others, and allows for what Tony Laden has called the social practice of reasoning. Political theorists have shown how responsiveness is a middle ground between dominance and acquiescence, where citizens show a willingness to be moved by those around them. Responsiveness is tested, though, when citizens interact with those who hold what are thought to be immoral or unjust beliefs. The key question: Is it possible to engage responsively with those who hold morally suspect beliefs, to be legitimately “moved” by those around us, without necessarily acquiescing to the moral problems? We argue that such engagement is both possible and desirable. There are at least five different ways to be moved by others in a productive, civic sense. We describe these modes, explain their moral depth, and give some examples. Civic educators should be aware of these modes and teach students how they can be manifest in democratic life.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.076 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".