Bibliographic record
Abstract
ABSTRACT Normativity has long been a central concept in ethics, medicine, and the social sciences. It has not been fully explored as an element in historiography or historical thought. This article contends that normativity, when taken as a metaconcept that underpins notions of the “normal,” “norms,” and “normality,” can help us understand changing attitudes to the possibility, actuality, and moral exemplarity of historical phenomena, but only if we disaggregate three different modes or registers of normativity: moral, metaphysical, and phenomenal. After exploring the place of moral normativity in historical thought and writing from antiquity to the early modern era, I discuss metaphysical and phenomenal normativity as filters that, from the Middle Ages through the seventeenth century, were applied to reported or recorded experience prior to any decision to derive from it any moral conclusions. I then argue that Baconian empiricism, Humean skepticism, classical probability theory, and mathematical statistics collectively gave rise to a modern sense of what constituted “normality” for past and present events. Finally, I conclude that the late Enlightenment bequeathed to modernity and postmodernity a normalized sense of fundamental rupture (exemplified by the French Revolution and characterized as the “historical sublime”) that we still experience and struggle through as we routinely reconstruct history as both a linear tradition and a discontinuous series of “new normals.” We also contend with this sense of fundamental rupture as we “renormalize” catastrophes that could reasonably be regarded as beyond normalization while simultaneously fetishizing the experience of disruption, which we have defined as a clinamenic swerve from one normality into another. This paradoxical process is accompanied by a deadened capacity to judge that which is, and is not, normal.
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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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.076 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| 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".