Are Mental Health and Neurodevelopmental Conditions in School Years Barriers to Postsecondary Access
Bibliographic record
Abstract
Various factors (e.g., sex, and parental education) have been identified as key determinants of postsecondary education (PSE). Yet, relatively little is known about the role of disability as a barrier to obtain PSE. The purpose of this study was to examine the relationship between mental health (MHC) and neurodevelopmental conditions (NDC) diagnosed in school years and postsecondary enrolment during early adulthood. The study was possible due to the recent linkage between the National Longitudinal Survey of Children and Youth and T1 Family File. Results showed that 77% of youth who had no diagnosed long-term health conditions at all in their school years (comparison group) attended postsecondary by their early 20s. In contrast, 60% of youth with NDC attended postsecondary in the same time frame, while only 48% of youth with MHC attended postsecondary. Youth with both NDC and MHC were even less likely to attend: only 36% went on to postsecondary. Differences in sex, academic performance, and family background explained only about one third of these gaps. Children with NDC and MHC face additional barriers to attending postsecondary that are distinct from those confronting other youth. These findings have important implications for accommodation and transition support for students with disabilities.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".