Do peers contribute to the likelihood of secondary school graduation among disadvantaged boys?
Bibliographic record
Abstract
This 17-year longitudinal study tested whether low peer-perceived acceptance and association with aggressive-disruptive friends during preadolescence predicted students' failure to graduate from secondary school. Participants were 997 Caucasian, French-speaking boys from low-socioeconomic status, urban neighborhoods. The boys were recruited in kindergarten (age 6) and followed through early adulthood (age 23). Low levels of prosocial behaviors and high levels of aggressive-disruptive behaviors in childhood were expected to predict negative preadolescent peer experiences. Adolescent academic achievement and school commitment were expected to mediate the link between preadolescent peer experiences and early adulthood graduation status. Results of structural equation modeling analyses tended to support these hypotheses. Greater childhood aggression-disruptiveness positively predicted friends' preadolescent aggression-disruptiveness. Having aggressive-disruptive friends, in turn, was related to a lower likelihood of graduation. Lower academic achievement and school commitment partially mediated the association between friend characteristics and graduation. Peer acceptance did not contribute to graduation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".