Methodological reflections from a research project on the mental health of Black youth
Bibliographic record
Abstract
The aim of this study was to provide an illustrative example of how researchers can effectively engage Black youth using a culturally responsive, participatory action research (PAR) approach. We aimed to examine the mental health needs of Black youth and identify culturally relevant strategies to increase access to and uptake of mental health services. The study took a PAR approach to foster maximum inclusion of youth in the research process. We collected data in two phases: (1) individual interviews with 30 youths; and (2) monthly conversation cafés over a four-month period with 99 youth participants. We recruited youth participants through the Africa Centre Youth Empowerment Group in Alberta, at a soccer tournament hosted by Africa Centre and through affiliated social networks, and established a youth advisory group that met quarterly and assisted with data collection, data analysis and dissemination. We shared our findings at a community engagement session for stakeholders. The study provided space for youth to share their experiences and to imagine solutions to their mental health difficulties; it also allowed us to conduct research that carefully integrated the perspectives of those most affected by the study's policy and practice recommendations. This project is an important case example that demonstrates promising practices and accessible methods across the data collection cycle, as well as the key ingredients and mechanisms that support culturally responsive practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.083 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.044 | 0.023 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".