Staff perspectives on the successful families program model: Combining supportive housing with wraparound services for teen families
Bibliographic record
Abstract
Providing support to address the systemic barriers that teen families face is a logical step toward improving their health and well-being. One area where teen families face multiple obstacles is accessing safe, secure, affordable housing. This paper describes a unique, innovative model of supportive housing developed in combination with wraparound supports, provided to teen parents in Edmonton, Canada. As part of a larger community-based participatory research and evaluation project, we draw on qualitative data to describe the supportive wraparound housing model that was developed. In particular, we conducted individual interviews and focus groups with a total of 27 staff members from the partner agencies, who provided information about the Successful Families program model. Analysis of interview data resulted in five broad categories that have resonated with our community and academic team as a way to conceptualize and share the work of the program. Categories, which are described in terms of associated subcategories, include: Community, Partnership, Program Principles and Values, Successful Families Program Structures, and Skill and Knowledge Development. Through this work, we aim to promote awareness of considerations for service providers seeking to implement similar services, and expand the limited knowledge base regarding methods for supporting the diverse needs of teen families.
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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 | 0.019 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".