Immigrant Latino men in rural communities in the Northwest: social environment and HIV/STI risk
Bibliographic record
Abstract
This study explored how migration-related socio-cultural and environmental factors interact to render immigrant Latino men residing in rural Oregon at increased risk for HIV/STI. More specifically, the paper describes the socio-demographic characteristics and sexual risk profile of immigrant Latino men and characterises the physical and socio-cultural contexts in which they reside. In-depth interviews were conducted with 49 men who newly immigrated to the USA and had recently engaged in sexual intercourse with women. Content analysis indicated that job instability and seasonal/industry restrictions resulted in frequent changes in employment and living situations, and one-third of respondents reported having no one to turn to when in need. Over two-fifths had ever had sex with a sex worker, with almost a quarter reporting sex with a sex worker in the past three months. In addition, over half of the men reported that they never, or inconsistently, used condoms. Although respect for wives/girlfriends was valued, loneliness, sexual experimentation and inherent sexual needs were cited as reasons that men have sex outside their primary relationships. Our data support the convergence of risky environments and migration-driven factors in exacerbating STI prevalence and the HIV epidemic among Latino immigrant men residing in the Northwest.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".