Responsibility as Responsiveness: Enacting a Dispositional Ethics of Encounter
Bibliographic record
Abstract
With the normative demand to attend to social difference and an absence of universal evaluative terms with which to do so, recent theory has increasingly turned to the study of the affective rather than epistemological conditions of ethical encounter. This I call a “dispositional ethics” that construes responsibility as responsiveness. Recent articulations of such an ethics, notably in the most current work of Judith Butler, James Tully, Jade Larissa Schiff, and Ella Myers, highlight its connection to situated practices of concrete bodies-in-relation, but often stop short of developing an account of what such embodied practices might be. Based on interviews with thirteen experts who take the body as their primary vocational and intellectual field and characterize their practice as an art of listening, I distinguish three dimensions of a dispositional ethics in practice and some of the specific strategies available to cultivate the conditions for responsiveness in political 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 | 0.020 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.077 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".