Navigating Institutions: Parents’ Knowledge of the Educational System and Students’ Success in Education
Bibliographic record
Abstract
Abstract This study investigates whether families navigate educational institutions more successfully if they have a higher knowledge of the pathways in the educational system that are available to their children. We also study whether this kind of knowledge mediates secondary effects of social origin, i.e. differences in educational pathways once achievement differences between children are accounted for. The role of parents’ knowledge is consistent with various sociological theories concerning educational inequality. Knowledge can affect families’ ability to make rational choices for education but it can also be understood as a form of cultural capital. We use longitudinal student cohort data from the Netherlands combined with individual-level register data on educational attainment to study the importance of knowledge for short-term outcomes (up- and downward transitions in secondary education as well as track placement) and final educational attainment. Our results show that parents’ knowledge is a significant predictor of educational success net of parents’ education, socio-demographic characteristics, and demonstrated ability. If we apply a stricter test to the measure, however, we can see that knowledge matters for downward transitions and obtaining a tertiary degree but that the effect is negligible for upward transitions and track placement if other mechanisms such as cultural capital and aspirations are considered. Further, we conclude that knowledge matters especially for transitions in the educational system that require a move to a new and unknown school environment such as post-secondary or tertiary education. The study shows that knowledge is one useful avenue to investigate when we are confronted with the question why social disparities in educational decision-making arise.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".