Éditorial – Partenariat entre les infirmières et les familles : une santé publique fondée sur les données probantes pour lutter contre la violence envers les enfants
Bibliographic record
Abstract
ÉditorialPartenariat entre les infirmières et les familles : une santé publique fondée sur les données probantes pour lutter contre la violence envers les enfants Lil Tonmyr, Ph.D., rédactrice invitée Diffuser cet article sur TwitterUn trop grand nombre d'enfants canadiens subissent de mauvais traitements, que ce soit de la ne ´gligence, de la violence psychologique, une exposition a `la violence conjugale ou a `la violence physique et sexuelle.Des donne ´es re ´trospectives montrent que 32 % des adultes canadiens ont e ´te ´victimes de violence pendant leur enfance 1 .Certaines donne ´es probantes e ´tablissent un lien entre la violence subie durant l'enfance et un large e ´ventail de conse ´quences ne ´gatives sur la sante ´tout au long de la vie.Ces conse ´quences touchent notamment les sphe `res physique, mentale, sociale et du de ´veloppement et incluent le suicide, la toxicomanie, l'anxie ´te ´, la de ´pression et les proble `mes de sante ´1-4 .
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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 | 0.016 | 0.076 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.026 | 0.020 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".