The Maltreatment and Adolescent Pathways (MAP) Project: Using Adolescent Child Protective Services Population-Based Research to Identify Research Questions
Bibliographic record
Abstract
This article introduces readers to the Maltreatment and Adolescent Pathways (MAP) study. The MAP is a longitudinal study that follows active case files of mid-adolescents in a large urban child protective services (CPS) system. The MAP is a unique opportunity to collect information from teens about their physical health (e.g., sleep quality), mental health (e.g., posttraumatic stress disorder) and cognitive style (e.g., attention, memory). The MAP study samples the population of CPS teens on questions that are used in provincial teen surveys, allowing for points of comparison to non-CPS teens. The MAP tracks youth development over 2.5 years. Although the MAP currently has a very small number of Aboriginal teens, the responses of these teens may focus practitioner and researcher attention to priority areas for further research. This includes the investigation of how some research issues, such as maltreatment history, personal safety, relationship to primary CPS worker and suicidal ideation, may be cross-informative. It is known that teen risk behaviours cluster together, but it is important to understand the relationships among these variables. An understanding of these relationships can drive knowledge creation, as well as practice and policy change. Finally, the MAPstudy has succeeded given a successful collaborative partnership between hospital, university, and CPS partners who both strive to keep the youths’ best interests in the forefront.
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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 | 0.023 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".