Bibliographic record
Abstract
Though the vulnerabilities and disadvantages of youths not in employment, education or training (NEET) are widely acknowledged, little mental health research has focused on the conditions that precede youths disengaging from school or work; how and to what extent such disengagement intersects with mental illness; and how early functional disengagement impacts overall outcomes. This symposium addresses these knowledge gaps. Sloan describes the post-secondary outcomes of young adults with emotional and behavioral disorders. Using data from an American longitudinal epidemiological study, she illustrates the interplay of sociodemography, diagnoses and outcomes in youths who had psychiatric disorders by age 16. Healy presents an Irish community-based investigation of the effects of childhood psychotic experiences on global functioning. Compared to children who reported no psychotic experiences, those who did had poorer functioning that persisted into early adulthood. Notably, their underlying global vulnerability extended beyond diagnosable disorders. Henderson shows that NEET youths presenting at Canadian clinical and non-clinical services were likelier to have concurrent mental health and substance use concerns, legal troubles and crime/violence problems; be in unstable housing situations; and need welfare aid. Iyer paints a picture of NEET youths at a Canadian early psychosis program having longer prodromes characterised by unrelenting illness and plummeting premorbid adjustment. This, along with longer durations of untreated psychosis, suggests that NEET youths follow a distinct trajectory of clinical and functional decline. Finally, Cannon (discussant) will situate these findings within what is currently known about youth mental illness and functioning, and highlight their services, research and policy implications.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".