The Effects of Socioeconomic Vulnerability, Psychosocial Services, and Social Service Spending on Family Reunification: A Multilevel Longitudinal Analysis
Bibliographic record
Abstract
Socio-environmental factors such as poverty, psychosocial services, and social services spending all could influence the challenges faced by vulnerable families. This paper examines the extent to which socioeconomic vulnerability, psychosocial service consultations, and preventative social services spending impacts the reunification for children placed in out-of-home care. This study uses a multilevel longitudinal research design that draws data from three sources: (1) longitudinal administrative data from Quebec’s child protection agencies; (2) 2006 and 2011 Canadian Census data; and, (3) intra-province health and social services data. The final data set included all children (N = 39,882) placed in out-of-home care for the first time between 1 April 2002 and 31 March 2013, and followed from their initial out-of-home placement. Multilevel hazard results indicate that socioeconomic vulnerability, controlling for psychosocial services and social services spending, contributes to the decreased likelihood of reunification. Specifically, socioeconomic vulnerability, psychosocial services, and social services spending account for 24.0% of the variation in jurisdictional reunification for younger children less than 5 years of age, 12.5% for children age 5 to 11 years and 21.4% for older children age 12 to 17 years. These findings have implications for decision makers, funding agencies, and child protection agencies to improve jurisdictional resources to reduce the socioeconomic vulnerabilities of reunifying families.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".