Growth in perceived control across 25 years from the late teens to midlife: The role of personal and parents’ education.
Bibliographic record
Abstract
This study examined trajectories of perceived control and their association with parents' education and personal educational experience (educational attainment and years of full-time postsecondary education) in 971 Canadian high school seniors tracked 7 times across 25 years. Latent growth models showed that, on average, perceived control increased from age 18 to age 25 and decreased by age 32, with a further slower decrease by age 43. Parents' education contributed to a growing gap in perceived control, however, such that among individuals with at least 1 university-educated parent, perceived control increased across 25 years, reaching its highest level at age 43. Personal educational attainment (completion of a university degree or not) was not associated with growth in perceived control, but individuals who were higher on perceived control at age 18 were more likely to complete a university degree. Parallel process modeling found that perceived control at age 19 predicted gains through age 32 in years of postsecondary education. Postsecondary enrollment at age 19 did not predict gains in perceived control over time. Parents' education predicted both higher levels of perceived control and enrollment in full-time postsecondary education at age 19. Family socioeconomic status contributes to perceived control early in the transition to adulthood and may lead to diverging trajectories over the next 25 years, and perceived control contributes to subsequent postsecondary educational experience. Further longitudinal research should explore the development and determinants of perceived control across the full life span.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".