Bibliographic record
Abstract
This work is the result of a long process that began with my French book De la tolérance à la reconnaissance (Boréal 2008).It was then translated into English by Mary Baker.I thank her for her professionalism and the high quality of her translation.Since then, it has undergone very important modifications.I still argue that political liberalism, as developed by John Rawls, offers a hospitable theoretical framework for a theory of collective rights applied to peoples.However, very deep changes were made to the overall argument.The most important one concerns my interpretation of the fundamental liberal principle according to Rawls.I now think that toleration as respect for the sake of political stability explains the new orientations taken by Rawls in Political Liberalism.Large parts of the work were completely rewritten, taking into consideration the new philosophical orientation that my work was undertaking.Some chapters were removed, others were added.Many changes took place, whether in expanded arguments, modifications, simplifications, or corrections.The result is a completely new book.I thank the anonymous referees for their comments.I also want to thank my assistant, Jérôme Gosselin-Tapp, for his help in preparing the manuscript.Many institutions have backed this project.I
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.348 | 0.235 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".