La réponse aux besoins affectifs et cognitifs de l’enfant : Application du modèle cumulatif à la population générale
Bibliographic record
Abstract
OBJECTIVES: Several risk factors are associated with neglectful behaviors. Yet their cumulative effect, which refers to the accumulation of risk regardless of the presence or absence of specific factors, remains unknown. This study aims to determine whether risk accumulation predicts caregivers' responses to children's emotional and cognitive needs in the general population and to examine the presence of clinical thresholds. METHOD: A total of 1102 maternal figures of children aged 5 to 9 years old living in Quebec were questioned through a telephone survey. The response to children's emotional and cognitive needs was measured using a validated version of the Parent-Report Multidimensional Neglectful Behavior Scale. Ten individual, family and socioeconomic risk factors were combined to compute a cumulative risk index. RESULTS: Results indicate that the cumulative index predicts the response to children's emotional and cognitive needs in the general population. This effect is observed for families exposed to at least two risk factors and it increases considerably when risk exposure reaches 5 factors. CONCLUSIONS: This study supports the cumulative risk hypothesis, which until now had mainly been examined in vulnerable or clinical samples. It fosters a better statistical understanding of contexts compromising an optimal response to school age children's emotional and cognitive needs in the general population. This breakthrough is particularity important considering the challenges of identifying children at risk of having their needs neglected.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".