The Alberta Incidence Study: Predicting ‘Crossover Youth’ and ‘Academic Difficulties’ by Child, Caregiver, and Environmental Factors
Bibliographic record
Abstract
A portion of a Canada wide project, The Alberta Incidence Study investigates various risk factors and prevalence rates of child maltreatment cases in Alberta (MacLaurin et al., 2013). The information collected provides an understanding of children involved in the children’s services population in Alberta. “Crossover Youth” have become a subpopulation of attention in recent years within child maltreatment research. “Crossover Youth” are defined as maltreated youth within children’s services who also engage in delinquency (Herz, et al., 2010). Crossover youth have also been associated to areas of academic difficulties, including learning difficulties and academic performance (Herz et al., 2010). Academic difficulties are defined as children identified with learning disabilities, special needs, or behaviour problems, which are usually identified in the school system. The Alberta Incidence Study Data was utilized to help predict crossover youth or academic difficulties in three categories; Child factors, Caregiver factors and Environmental factors. Results indicate that among maltreated youth, caregivers with any risk factor (5.67 times) and history of foster care (2.37 times) made crossover status more likely. Youth who struggled with alcohol abuse (5.79 times) and intellectual/developmental disabilities (4.83 times) were also more at risk. Youth with indications of poverty were also more likely to crossover (1.93 times). Youth who had caregivers with a history of foster care (5.01 times), or any caregiver risk factor (2.77 times) made academic difficulties more likely. Physical disabilities (55.81 times) and intellectual/developmental disabilities (38 times) increased the chance of academic difficulties. Households who often faced challenges with money for basic necessities increased the likelihood of academic difficulties status (2.29 times). Persons working in this population are recommended to view each risk factor as potentially important for crossover risk and academic difficulties. School psychologists are provided recommendations for diagnosis and risk reduction when working with maltreated children in terms of trauma. Suggestions for future research are discussed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".