Entre belles-lettres et disciplines: les savoirs au <scp>xviii</scp> <sup>e</sup> siècle <i> Entre belles-lettres et disciplines: les savoirs au <scp>xviii</scp> <sup>e</sup> siècle </i> . Sous la direction de F <scp>ranck</scp> S <scp>alaün</scp> et J <scp>ean</scp> -P <scp>ierre</scp> S <scp>chandeler</scp> . Ferney-Voltaire: Centre international d'étude du <scp>xviii</scp> <sup>e</sup> siècle, 2011. 202 pp.
Bibliographic record
Abstract
The present collection of articles deals with the ambiguity surrounding scholarly disciplines in the eighteenth century, and the polymathic nature of intellectual life during the period. Unlike our own world, in which scholarly practice is divided between disciplines with clearly demarcated boundaries, methods, practices, and canonical texts, the Enlightenment functioned without compartmentalizing thinkers into particular fields. The contributors to this volume are particularly interested in understanding the relationship between literature and ‘science’ (defined broadly). In the 1660s the Academy of Sciences in Paris announced that it dealt with ‘toutes sortes de littérature’ (p. 9), and there was nothing contradictory about natural philosophers conceptualizing themselves as literary figures — although, as the contributors point out, modern disciplines did begin to take shape in the latter part of the century, which subsequently created tensions among intellectual circles. However, what defined the ‘gens de lettres’ of the period was commitment to knowledge, practices of sociability, and refined taste, not an allegiance to this or that particular discipline or ‘art’. Robert Mankin's essay on Edward Gibbon shows the extent to which the latter defined ‘littérature’ in broad terms and saw it as compatible with (and useful for) his ‘science of antiquity’ (p. 44). The essay by Marc J. Ratcliff shows that the growing interest in scientific nomenclature and taxonomies in the period reflected not only an interest in systems of classification but also in language, literature, and terminology. Olivier Ferret argues that the term ‘philosophe’ applied equally to literary and scientific thinkers. Catherine Volpilhac-Auger discusses the many hats worn by Montesquieu: natural philosopher, academician, historian, and early political theorist. Jeanne Peiffer shows that the Journal des savants went to great lengths to avoid specificity and instead preferred a universal and dynamic approach to intellectual commerce. The essays in Entre belles-lettres et disciplines are generally concise and well argued — rarely are they off topic — and the editors set them up with an excellent Introduction. Franck Salaün and Jean-Pierre Schandeler have succeeded in bringing together an important volume that offers perhaps the most thorough treatment to date of the polymathic nature of the European Enlightenment, before universities in the nineteenth century sharpened the differences between scholarly fields.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.057 |
| Meta-epidemiology (narrow) | 0.012 | 0.012 |
| Meta-epidemiology (broad) | 0.012 | 0.007 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.021 | 0.015 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.010 | 0.011 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads 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".