Bibliographic record
Abstract
Within Canada, the HIV/AIDS community is an extensively researched population where people living with HIV/AIDS (PHA) are minimally included in the research process. Community-based research (CBR) has become a widely recognized framework with which to engage in HIV/AIDS research in a response to the need for research frameworks that promote equitable collaboration between community members and community researchers. Coupled with a CBR approach, the Greater Involvement of People Living with HIV/AIDS (GIPA) principle can be incorporated into the research process so that the research is reflective of and responsive to community needs. Drawing on the experiences of five HIV/AIDS community researchers, this study seeks to better understand the tensions and challenges community researchers experience when facilitating CBR with participants with whom they identify with based on race, gender, sexual orientation, immigration status, and HIV status. Within the findings, several themes were explored by participants. The concept of multiple identities was predominately explored as well as the complexities regarding insider and outsider status. Participants also explored the tensions associated with maintaining confidentiality as well as discussing coping and self care practices. Expectations of community members and the research team were highlighted, and participants provided advice or recommendations based on their reflections of their personal experiences of engaging the CBR process. The themes explored by this particular group of community researchers demonstrate the complexities associated with their unique positioning within the research process. As the CBR approach is increasingly being utilized and recognized as an effective tool within a community research context, it is important as practitioners to be mindful of the challenges and benefits of facilitating CBR.
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 | 0.091 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.044 | 0.029 |
| Scholarly communication | 0.020 | 0.011 |
| Open science | 0.008 | 0.029 |
| Research integrity | 0.008 | 0.012 |
| 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".