An intersectional analysis of socio-cultural identities and gender and health inequities among children and youth in street situations in western Kenya
Bibliographic record
Abstract
Research has uncovered substantial gender, social, and health disparities among children and youth in street situations (CYSS) in Eldoret, Kenya. From 2013-2014 we engaged CYSS aged 11-24 years in a qualitative study to explore the sexual language and practices used in the street subculture in Eldoret, Kenya. We engaged 65 CYSS in 25 in-depth interviews and 5 focus group discussions. This work uncovered stark gender inequities, which result in girls and young women in street situations experiencing profound levels of sexual and gender-based violence and harmful sexual and reproductive health outcomes. To comprehend the underlying drivers of these inequities and to appropriately and adequately intervene, we sought to comprehend how CYSS’s social identities intersect with systems of oppression and privilege to produce and maintain these inequities. We therefore sought to reanalyze the original data from this study using intersectionality as a theoretical framework to explore how systems of oppression in Kenya have shaped the street subculture, construct CYSS’s street and resistance social identities, and how these social identities and the street subculture intersect with macro-level structural factors to produce health and gender inequities. Our analysis identified three distinct social identities that are given to CYSS in Eldoret: Chokoraa (garbage pickers), Mshefa (hustlers), and Mboga ya jeshi (vegetables for soldiers). Our findings revealed how these identities and the street subculture intersect with the Patriarchy, the political-economic context, and social cultural forces in Kenya, resulting in hegemonic masculinity and detrimental gender roles and norms for young men and women. Our findings show that CYSS are a product of the oppressive systems that construct their circumstances and shape their social identities. This population urgently requires policies and programs that intervene at multiple levels to halt the harmful practices within street subculture and associated with street-involvement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".