Black heterosexual men’s resilience in times of HIV adversity: findings from the “weSpeak” study
Bibliographic record
Abstract
BACKGROUND: In Canada, heterosexual African, Caribbean and Black (ACB) men tend to suffer a disproportionate burden of HIV. Consequently, studies have examined the underlying contributors to this disparity through the nexus of behavioral and structural factors. While findings from these studies have been helpful, their use of deficit and risk models only furthers our knowledge of why ACB men are more vulnerable to HIV infection. Thus far, there is a dearth of knowledge on how heterosexual ACB men mobilize protective assets to promote their resilience against HIV infection. METHODS: As part of a larger Ontario-based project called weSpeak, this study examined how ACB men acquire protective assets to build their resilience to reduce their HIV vulnerability. We analyzed three focus group discussions (n = 17) and 13 in-depth interviews conducted with ACB men using NVivo and a mixed inductive-deductive thematic analyses approach. RESULTS: The findings show that ACB men mostly relied on personal coping strategies, including sexual abstinence, to build resilience against HIV. Interpersonal resources such as family, friends, and religious communities also played an important role in constructing ACB men's resilience. ACB men bemoaned their lack of access to essential institutional resources, such as health services, that are important in managing HIV adversity. CONCLUSION: Based on these findings, there is an urgent need for HIV policy stakeholders, including service providers, to engage the ACB community in the design of intervention programs. Additionally, addressing the socioeconomic disadvantages faced by ACB communities will increase the capacity of ACB men to develop resilience against HIV.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".