Adolescent leisure reading and its longitudinal association with prosocial behavior and social adjustment
Bibliographic record
Abstract
Reading is a popular leisure activity for children, teenagers, and adults. Several theories agree that reading might improve social cognition, but the empirical evidence remains tentative, with research on adolescents especially lacking. We employed a very large, and nationally representative, longitudinal dataset from the National Educational Panel Study (NEPS) in Germany to examine this hypothesis. Specifically, we tested whether reading prospectively predicted future self-reported prosocial behavior and social adjustment in adolescents, controlling for a number of covariates. Two-way cross-lagged panel analyses probed the longitudinal relationship between leisure reading and these social outcomes from Grade 6 to Grade 9. In addition, we examined the effect of cumulative reading experience across Grades 5-8 on future social outcomes, using structural equation modeling. We also explored the unique contributions of cumulative reading experience in different literary genres (classic literature, popular literature, nonfiction, comic books). Cumulative reading in general did not predict future prosocial behavior and social adjustment. However, cumulative reading of modern classic literature was positively associated with later prosocial behavior and social adjustment. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 08 November 2021. The protocol, as accepted by the journal, can be found at: https://doi.org/10.17605/OSF.IO/KSWY7 .
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".