Family Matters: High School Graduation and Sibling Influence
Bibliographic record
Abstract
INTRODUCTION: Educational attainment is known to be related to family size, birth order, and the educational achievement of an older sibling. OBJECTIVE: This study examines younger siblings in large families, exploring the extent to which each older sibling's educational attainment is associated with attainment of the younger sibling. METHODS: Linkable administrative data were used to create a population-based cohort of third children in three child families born in Manitoba, Canada between April 1, 1984 and March 31, 1994, who stayed in the province until at least age 20 (n = 5,771). Logistic regression models were used to examine the relationship between the youngest siblings' educational achievement and that of their older two siblings, adjusting for a series of confounders. RESULTS: Youngest siblings have the greatest odds of graduating from high school if both older siblings graduated. Females also had greater odds of graduating if only one of those older siblings had graduated; this did not increase the odds for males. Associations in educational attainment were stronger when siblings were born close together. For siblings born further apart, these associations were stronger if those siblings were of the same sex as the youngest sibling. CONCLUSIONS: In large families, the educational attainment of each older sibling is associated with the educational attainment of the younger sibling; associations differ depending on the birth order and sex of the older siblings. Families in which older siblings do not graduate from high school may be experiencing numerous challenges. Children with older siblings who fail to graduate may benefit from additional supports to increase their likelihood of graduation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".