Qui perd gagne: imaginaire du don et Révolution française Qui perd gagne: imaginaire du don et Révolution française. By G <scp>eneviève</scp> L <scp>afrance</scp> . (Collection Socius). Montréal: Presses de l'Université de Montréal, 2008. 362 pp. Pb CA$34.95; €31.00.
Bibliographic record
Abstract
This is an analysis of beneficence as represented in five novels published between 1795 and 1807 — Gabriel Sénac de Meilhan's L'Émigré, Isabelle de Charrière's Trois femmes, Joseph Fiévée's La Dot de Suzette, Germaine de Staël's Delphine and Corinne — against the background of the Revolution. Lafrance argues that the Revolution is enthusiastic about beneficence, in particular as reparation for inequality, rather than as old regime charity that can reinforce a hierarchy. She refers to historians to show both an increase in individual giving in France in the 1790s, and the inauguration of state aid. This is an interesting combination of texts, over a very particular decade or so when aristocratic refugees, accustomed to being benefactors rather than beneficiaries, are forced to accept help. Lafrance draws comparisons both between these novels (and earlier ones) and between any one novel and the position of the Revolutionary governments. These parallels help the reader to understand the network of elements that make up the code of beneficence in the Enlightenment and Revolutionary periods. At the same time, I would want to suggest some distinctions. For example, Lafrance relates Revolutionary State aid to the poor — as recompense for past injustice — both to Constance's and to Josephine's [sic] beneficence in Trois femmes. She argues that the two women have acquired their means of doing good illegitimately, and act as benefactors to forget past crimes. I would argue that, say, in the case of Josephine, it is the opposite: she is determined to care for Emilie and will do so whether the means for doing so are her (legitimate) savings from her wages or involve some sexual contact with men who help with household tasks. The fact that men who help Josephine always demand some recompense seems to me to make her case importantly different from that of a government that helps the starving masses exploited over preceding centuries. Josephine, as portrayed by Charrière, has a far more pragmatic attitude to her ‘virtue’ than many of the commentators do — they read her behaviour as simply wrong (as feudal exploitation was wrong). Condemnation of sexual activity on the part of an unmarried woman is, it is true, the position adopted by eighteenth-century society; but Charrière is far more nuanced, showing the string of respectable men who will exploit a woman if they can (without negative consequences for themselves), and the far smaller range of possibilities for a female servant who wishes to survive, and even to help her beloved mistress live in a degree of comfort. Lafrance also makes a link to Rousseau's La Nouvelle Héloïse as a text that shows beneficence to the poor as a way of enabling inequality by mitigating it. In the context of Rousseau's other works, with their passionate arguments against inequality, I would argue that it is reasonable to accept his case that, when the macro-context is one of extreme inequality, then it is good at least to mitigate this as much as possible by beneficence, rather than assume that beneficence in this case has inequality as its goal (although this is undoubtedly true in some eighteenth-century theory and practice). As these comments show, the book will provoke plenty of discussion — which is, of course, in its favour.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.060 | 0.008 |
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".