FATHERS’ IMPORTANCE IN ADOLESCENTS’ ACADEMIC ACHIEVEMENT
Bibliographic record
Abstract
Many studies have investigated mothers’ impact on students’ achievement, yet little is known about how various father types impact students’ school performance. This study examines 6 mutually exclusive categories of father type: resident biological fathers, resident stepfathers, resident adoptive fathers, nonresident biological fathers, unknown biological fathers, and deceased fathers. Adolescents’ school performance from seventh through twelfth grade is examined using data from 3 waves of the National Longitudinal Study of Adolescent Health (Add Health), a nationally representative United States secondary data source. Findings indicate different types of fathers have distinct and independent positive associations with adolescents’ school achievement, after controlling for mother involvement. Adolescents with resident biological fathers had higher school performance than adolescents with nonresident fathers. Adolescents with stepfathers had higher rates of school failure than their peers living with their biological parents. The lowest achievement and the highest risk of school failure and course failure were experienced by those adolescents who did not have a resident father figure and didn’t know the identity of their fathers. Implications include the need to model for the unique influence of father involvement and father type on academic achievement, and the inclusion of unique family contexts in efforts to increase adolescents’ school involvement and integration.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".