Standardized mortality ratios between street-connected young people and the general age-equivalent population in an urban setting in Kenya from 2010 to 2015
Bibliographic record
Abstract
There are currently no published estimates of mortality rates among street-connected young people in Kenya. In this short report, we estimate mortality rates among street-connected young people in an urban setting in Kenya and calculate standardized mortality ratios to assess excess mortality among street-connected young people compared to the general population of Kenyan adolescents. We collected data on deaths among street-connected young people aged 0-29 between 2010 and 2015. We calculated sex-stratified standardized mortality ratios for street-connected young people aged 0-19 and 20-29 from 2010 to 2015, using publicly available Kenya population data as reference. We found that between 2010 and 2015, there were 69 deaths among street-connected young people aged 0 to 29 years in 2013 was 1,248: 341 females (27%) and 907 males (73%). The standardized mortality ratios among street-connected females aged 0-19 and 20-29 years were 2.79 (95% CI 1.44-4.88) and 7.55 (95% CI 3.77-13.51), respectively; standardized mortality ratios among street-connected males aged 0-19 and 20-29 years were 0.71 (95% CI 0.32-1.35) and 5.48 (95% CI 3.86-7.55), respectively. In conclusion, we found that mortality among street-connected young people in an urban setting in Kenya is elevated compared to the general population of Kenyan young people. States should act urgently and take responsibility for protecting street-connected young people's human rights by scaling up programs to prevent morbidity and death associated with youth street involvement.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".