Tackling exclusion: A pilot mixed method quasi-experimental identity capital intervention for young people exiting homelessness
Bibliographic record
Abstract
BACKGROUND: Longitudinal studies examining the life trajectories of young people after they have exited homelessness have identified concerns with persistent social and economic exclusion, struggles to shake off identities of homelessness, and housing instability. This pilot study sought to explore the feasibility of improving socioeconomic inclusion outcomes by bolstering identity capital (sense of purpose and control, self-efficacy and self-esteem) among young people who had experienced homelessness. METHODS: Nineteen individuals (aged 18-26) who had transitioned out of homelessness within the past three years participated in a six-week, six-session program focused on building identity capital. The study employed a mixed method prospective cohort hybrid design with an intervention group (Group One) and a delayed intervention comparison group (Group Two). Participants were interviewed every three months until nine months post-intervention. RESULTS: None of the youth who began the intervention dropped out of the program, with the exception of one participant who moved across the country and was unable to continue. Immediately after participating in the intervention, Group One had statistically significant improvements (p < .05) and large to very large effect sizes in self-esteem (d = 1.16) and physical community integration (d = 1.79) compared to changes in Group Two over the same period, which had not yet begun the intervention. In the pooled analysis, small to moderate effect sizes in hopelessness, physical community integration, and self-esteem were observed at all post-intervention time points. Notably, at six- and nine-months post-intervention, statistically significant improvements (p < .05) and moderate effect sizes in hopelessness (d = -0.73 and d = -0.60 respectively) and self-esteem (d = 0.71 and d = 0.53 respectively) were observed. Youth shared they appreciated the normalizing (vs. pathologizing) of strategies they needed to learn and spoke of the importance of framing new skills as something one needs "to have a better life" vs. "to get better." CONCLUSIONS: These early findings signal that targeting identity capital is feasible and may be a promising approach to incorporate into a more complex intervention that includes housing, education, and employment supports to help youth transition out of homelessness. Future research could build on these findings through a sufficiently powered randomized controlled trial.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".