Bibliographic record
Abstract
Les sites de rencontres ont favorisé l’essor d’un « papillonnage » numérique intensif. Maints inscrits de ces sites inventent à leur corps défendant de nouvelles manières d’aimer, déliées des exigences de la fidélité ou de l’inscription dans la durée. Les cadres normatifs évoluent, alors qu’Internet offre désormais à la rencontre amoureuse de nouveaux terrains de « drague » et des modalités technologiques et relationnelles augmentées. Ce dispositif permet l’émergence de rapports d’un nouveau genre, tout en industrialisant la rencontre amoureuse. Le polygaming est une solution de rechange sentimentalo-sexuelle bousculant la monogamie instituée en favorisant l’essor de relations ludiques, plurielles, transitoires, fondées sur un consensus hédoniste plus que sur un engagement long, et prenant les sites de rencontre comme dispositif stratégique. Cet article propose une théorisation du polygaming . Il s’agit d’en saisir les grands principes, et d’en mettre au jour le système de valeurs, au fil d’un parcours prenant plus largement en compte les bouleversements induits par les TIC dans le paysage de la rencontre amoureuse depuis quelques années.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".