Culturally Competent Health Promotion as a Social Inclusion Mechanism: A Study of Ontario Community-Based AIDS Service Organizations
Bibliographic record
Abstract
Ontario is a culturally diversified society. Its population composition has changed drastically in the past few decades to include large numbers of individuals with cultural norms differing from that of the majority. This poses challenges to public health, such as HIV prevention. Identifying practices that promote social inclusion in these communities is an important step toward the maintenance of cultural diversity and elimination of social exclusion. Culturally competent health promotion is one example of socially inclusive practices. Cultural competence refers to practices that take into consideration the cultural and linguistic nuances of a specific community or group. \nThis thesis will be guided by the research questions: (1) What are the main health promotion practices of Community-based AIDS Service Organizations (CBAOs)? (2) How do the activities of these organizations promote social inclusion? This thesis uses qualitative methodology to study the CBAO as the unit of analysis. Data were collected from operators at three ethno-cultural CBAOs in Ontario: South Asian; Black, African, and Caribbean; and Portuguese. CBAOs are organizations within the community that provide HIV prevention resources, as well as support for persons living with HIV/AIDS in the community. The practices demonstrated at CBAOS in these communities illustrate three related mechanisms present that promote social inclusion: (a) community networking, (b) community knowledge and involvement, and (c) community-specific resources. These mechanisms can be used to inform practices at other community-based organizations in Ontario.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.021 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".