Bridging Secondary Survey Data with In-Depth Case Studies to Advance Understandings of Youth Learning and Mental Health Concerns
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Using an explanatory sequential mixed methods research design, the purpose of this article is to demonstrate an innovative mixing of methods via the use of secondary survey data and detailed qualitative cases. This design is illustrated in the context of exploring influential family factors for youth with learning and mental health concerns. The use of case propositions as a central point of integration is highlighted. The integration of the quantitative and qualitative findings demonstrated the multifaceted psychological and relational issues, including parental monitoring, parent mental health, and youth self-efficacy. These meta-inferences provide surprising insight into the complex family experiences of youth with learning disabilities. Implications for theory and research are explored, concluding with a call for more multilevel mixed methods research using secondary data analysis.
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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 | 0.012 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it