Conséquences comportementales de la violence faite aux enfants
Bibliographic record
Abstract
Resume Objectif Discuter des repercussions de la violence sur le developpement comportemental durant l’enfance, mettre en evidence certains signes comportementaux susceptibles d’alerter les medecins a la presence d’une maltraitance continue d’un enfant et explorer le role precis du medecin de famille dans une telle situation clinique. Sources des donnees Une recension systematique a servi a examiner la recherche pertinente, les articles de revision clinique et les sites web des organismes de protection de la jeunesse. Message principal Le comportement d’un enfant est une manifestation exteriorisee de sa stabilite et de sa securite interieures. C’est une lentille au travers de laquelle le medecin de famille peut observer le developpement de l’enfant pendant toute sa vie. Tous les genres de violence sont dommageables pour les enfants, qu’elle soit physique, affective ou psychologique, et peuvent causer des problemes a long terme dans le developpement du comportement et de la sante mentale. Les medecins de famille doivent connaitre les indices de maltraitance et de negligence envers les enfants et etre aux aguets de ces derniers afin d’entreprendre les interventions appropriees et ameliorer les resultats pour ces enfants. Conclusion La violence faite aux enfants peut causer un developpement psychologique desordonne et des problemes de comportement. Les medecins de famille exercent un role important dans la reconnaissance des signes comportementaux laissant presager une maltraitance, ainsi que pour offrir de l’aide afin de proteger les enfants.
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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".