Bibliographic record
Abstract
This dissertation is concerned with understanding the long-term implications of childhood chronic conditions (e.g., physical, mental/developmental) on health and socioeconomic outcomes in young adulthood. Across three studies, I address issues pertaining to underlying mechanisms, sources of heterogeneity, and comparatively examine the effects of different conditions. I draw on survey and administrative tax data from the US and Canada, which I analyze using a range of statistical tools.The first study examines distributional differences in earnings and mental health scores in young adulthood between individuals who suffered from a chronic condition in childhood, compared to those who did not, using non-parametric distributional methods applied to the Panel Study of Income Dynamics (US). I find that young adults who reported a mental/developmental disorder in childhood cluster in the lower percentiles of both distributions of interest, relative to those who did not. Covariate decompositions suggest educational attainment represents an indirect pathway. The second study investigates long-term implications of childhood chronic conditions in Canada using individual-level linked survey and tax data (National Longitudinal Survey of Children and Youth, T1 Family File). I find that childhood mental/developmental disorders negatively affect all adult outcomes of interest (e.g., income) in baseline and fixed effects specifications, while physical ailments only affect health-related work absences and social assistance take-up. Covariate decompositions point to cognitive skills in adolescence as an indirect pathway. The final study examines the effect of childhood chronic conditions on parental investment behaviours (e.g., affective time, discipline). Using the National Longitudinal Survey of Children and Youth, I find that child mental/developmental disorders and behavioural problems lead parents to reduce investments across investment domains, and that parental socioeconomic characteristics moderate investment responses. I find modest contributions from parental investments in tempering the effects between child health conditions and short-run cognitive skills. Results suggest that childhood chronic conditions affect future outcomes, though processes involved are somewhat complicated. The findings underscore the potential for large returns of investments in childhood health in the form of enhanced long-term outcomes across many domains. Findings encourage further empirical work on mental/developmental health conditions and recommend inter-sectoral policy investments in childhood (e.g., health, education).
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".