Le désir d’enfant exploré à travers les pratiques de nomination
Bibliographic record
Abstract
Dans les sociétés occidentales, nommer l’enfant nouveau-né est aujourd’hui une responsabilité dévolue aux parents signataires de la déclaration de naissance, c’est-à-dire à ceux qui ont désiré que cet enfant devienne leur fils ou leur fille. Ce sont eux qui doivent lui transmettre un nom de famille et choisir les prénoms lui conférant une identité propre. À partir de l’analyse de 25 témoignages de parents québécois recueillis en entrevues, cet article explore le lien étroit établi entre désir d’enfant, filiation et nomination. L’analyse des récits sur l’histoire du couple, sur la naissance d’un premier enfant et sur les discussions entourant sa nomination aide à comprendre le sens que les parents donnent à l’enfant et à sa venue, et révèle que ce choix reflue parfois sur le choix du prénom.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".