Reciprocity and Trust in Political Deliberation: An Investigation into the Norms of Discursive Civility
Bibliographic record
Abstract
Much contemporary political discourse in the US and industrialized west is defective. According to a number of scholars, such as Scott Aikin and Robert Talisse, this defectiveness can plausibly be explicated in terms of a breakdown in political civility. In this thesis, I scrutinize possible explanations for why incivilities are widespread in political discourse. My goal is to defend an explanation according to which citizen incivility in political discourse is blameless. To do this, I appeal to a principle of reciprocity. According to the principle of reciprocity, citizens are not required to maintain civility in political discourse if they have reason to believe that their interlocutors will not reciprocate civility. When applied to contemporary politics, this principle implies that ordinary citizens in democratic societies across the US and industrialised west are often justified in being uncivil in political debate. For these citizens often have no reason to believe that their interlocutors will be civil. If the reciprocity principle is right, then policies aimed at restoring civility in political discourse must be concerned to build citizen trust that others will reciprocate civility. Without this trust, citizens may not see themselves as having reason to be civil. The thesis is divided into two chapters. In chapter 1, I defend the justificatory account of incivility against two competing accounts of political incivility—identity and group theories. These accounts pathologize political incivility as a kind of irrationality, but based on the argument from reciprocity, I argue that political incivilities are often rational and so justified. In chapter 2, I analyse the kind of trust that is necessary to build more civility in political discourse. In particular, I develop and defend a conception of deliberative trust, which is defined as the belief that one’s interlocutor will reciprocally adhere to the norms of civility.
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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 | 0.022 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.029 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".