Une illustration particulière de l’utilisation de la méthodologie de la théorisation enracinée (MTE) dans le but de mieux comprendre le sentiment de filiation chez les parents qui accueillent un enfant en vue de l’adopter
Bibliographic record
Abstract
Devenir parent en accueillant un enfant dans le contexte du programme Banque-mixte est une expérience singulière. Elle exige que le parent s’occupe d’un enfant comme s’il était le sien, même si légalement son statut de parent d’accueil ne lui accorde aucun droit sur l’enfant. De plus, il doit gérer le stress lié à l’incertitude de pouvoir adopter ou non cet enfant. Ainsi, comment les parents se lançant dans cette aventure réussissent-ils à développer le sentiment qu’ils sont LE parent de l’enfant qu’ils accueillent? Cette question a guidé la réalisation de la présente étude. L’article expose la démarche méthodologique utilisée, soit la méthodologie de la théorisation enracinée (MTE), afin de décrire le processus et les principes de la MTE qui ont guidé la réalisation de la recherche.
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 | 0.024 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".