On There Being Wide Reflective Equilibria: Why it is Important to Put it in the Plural
Bibliographic record
Abstract
Wide reflective equilibrium [WRE] is a distinctive coherentist method of justification or explanation or both, depending on the domain or purpose for which it is deployed. I deploy it principally as a method of justification for accounts of morality and normative political and social theory. But it is also used in many domains from the philosophy of mathematics and science to ethics and aesthetics. When deployed in domains as I deploy it for here, WRE starts with a cluster of societies’ specific considered judgments and uncontroversial empirical beliefs and theories and seeks to forge them into a coherent whole along with other considered judgments at all levels of generality. I use it here principally for a justification of political liberalism where it can and should be used for an internal justification, as John Rawls uses it, and as an external justification as Richard Rorty uses it. I use it for both. While these two modes of justification are distinct, they are compatible and importantly so. And for a more complete justification, both are required.
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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 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.057 |
| Scholarly communication | 0.017 | 0.050 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".