Bibliographic record
Abstract
The philosophical tradition of liberal political thought has come to see tolerance as a crucial element of a liberal political order. However, while much has been made of the value of toleration, little work has been done on individual-level motivations for tolerant behavior. In this article, we seek to develop an account of the rational motivations for toleration and of where the limits of toleration lie. We first present a very simple model of rational motivations for toleration. Key to this model is an application of David Ricardo’s model of trade to thinking about toleration. This model supports the claim that we always have reasons to be as tolerant as possible. We then explore why we do not always see tolerant attitudes in the actual world, and point to some potential preconditions for toleration that the initial model does not capture. Subsequently, we examine a more detailed model that allows us to investigate more carefully the conditions under which tolerant behavior can be rewarded. We conclude by arguing that a consideration of self-interested motivations for toleration is essential to the success of a robust theory of toleration for a diverse society, but that even this approach has its limitations.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".