Conversation Club: A Promising Practice in Youth Mentoring of Migrants and Refugees
Bibliographic record
Abstract
This paper evaluates Conversation Club, a Canadian after-school group mentoring intervention focusing on the expansion of the program across three separate regions of Ontario. The authors use a multiple methods design, including questionnaires (n=101), post-session process data, and qualitative interviews (n=18), to evaluate how Conversation Club impacts members’ feelings of hope, belonging, sense of ethnic identity, and social support. A focus group (n = 7) with program facilitators was also conducted to explore the process of dissemination of the Club across regions. Findings suggest that Conversation Club holds promise for newcomer youth across settings. Quantitative data showed significant change (p <.01) in levels of hope and sense of belonging. Interviews revealed an increased sense of belonging, possibility, and social support, as well as improved confidence in communicating with others. Insights regarding use of the Club manual suggest the importance of integrating Conversation Club values with flexibility in facilitation to incorporate the strengths and opportunities of context across regions. Study limitations, as well as implications for further social work research and dissemination of best practices in services for migrant and refugee youth, 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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".