Comprehensive evaluation of male health in four communities in rural Honduras
Bibliographic record
Abstract
PODEMOS (Partnership for Ongoing Developmental, Educational and Medical Outreach Solutions) has been a long-standing healthcare provider in 4 communities in northern rural Honduras. In this study, we sought to understand and quantify the health challenges faced by men in the rural communities served by PODEMOS in order to improve the way PODEMOS delivers healthcare. Between June and July of 2015, we conducted 104 structured survey interviews with men 18 years and older in rural Honduras. We found that most men face significant economic limitations in their ability to pay for healthcare and health-determining services and due to low formal education levels face health literacy challenges. Furthermore, we found that a quarter are at risk for health problems due to smoking, and the majority are at risk for musculoskeletal problems due to work in strenuous outdoor labor. However, we found that zero respondents drank alcohol heavily, which is defined as more than 14 drinks in one week. Lastly, we found varying opinions on female contraception use. Our findings indicate that medical brigades to the developing world should understand and quantify the relevant health challenges faced by their target populations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".