The multigenerational effects of adolescent motherhood on school readiness: A population-based retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Children born to adolescent mothers generally perform more poorly on school readiness assessments than their peers born to adult mothers. It is unknown, however, whether this relationship extends to the grandchildren of these adolescent mothers. This paper examines the multi-generational outcomes associated with adolescent motherhood by testing whether the grandchildren of adolescent mothers also have lower school readiness scores than their peers; we further assessed if this relationship was moderated by whether the child's mother was an adolescent mother. METHODS: We used population-based data to conduct the retrospective cohort study of children born in Manitoba, Canada, 2000-2009, whose mothers were born 1979-1997 (n = 11,326). Overall school readiness and readiness on five domains of development were analyzed using logistic regression models. RESULTS: Compared with children whose mothers and grandmothers were both ≥ 20 at the birth of their first child, those born to grandmothers who were < 20 and mothers who were ≥ 20 years old at the birth of their first child had 39% greater odds of being not ready for school (95% CI: 1.22-1.60). Children whose grandmothers were ≥ 20 and mothers were < 20 at the birth of their first child had 25% greater odds of being not ready for school (95% CI: 1.11-1.41), and children born to grandmothers and mothers who were both <20 at the birth of their first child had 35% greater odds of being not ready for school (95% CI: 1.18-1.54). CONCLUSIONS: These findings suggest a multigenerational effect of adolescent motherhood on school readiness.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".