Pierre Bayle and Richard Simon: toleration, natural law, and the Old Testament
Bibliographic record
Abstract
Pierre Bayle (1647–1706) developed an expansive theory of toleration in his Commentaire philosophique (1686) by arguing that tolerance is a universal principle of natural law. However, by situating toleration in natural law rather than positive law, Bayle was brought into theoretical conflict with the Old Testament injunction that the state should punish idolatry. To resolve this conflict, Bayle drew upon the work of early modern Hebraists, particularly the Catholic biblical scholar Richard Simon (1638–1712). Bayle adapted Simon’s idea that theocracy uniquely shaped the institutions of ancient Israel to argue that prohibitions against idolatry should be exclusive to the Hebrew republic. Bayle argued that the Mosaic Law did not punish someone for their sincerely held religious beliefs but only prohibited treason, and these circumstantial laws should not be emulated by other states. This allowed Bayle to contend for the moral veracity of the Old Testament and the notion that toleration is an unconditional principle of natural law. Bayle’s use of Simon displayed the revolutionary potential of textual critical scholarship in the early modern period, as he adapted Simon’s critical ideas to his own aims of promoting religious toleration within the ecclesiastical and civic spheres of his own confessional context.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".