"He is almost a normal child": An Ethnography of Malawi's National Pediatric HIV Treatment Program
Bibliographic record
Abstract
My dissertation is an ethnographic exploration of what it means to raise a child with HIV in one of the poorest countries in the world. Throughout I follow a small number of children and their caregivers as they engage with a new Global Health Initiative (GHI) to provide free universal access to antiretroviral therapy (ART), or anti-AIDS treatment, for infected children at a government run hospital in rural Northern Malawi. To date very little is known about how the roll-out of pediatric ART in decentralized health settings is progressing. The few studies that exist tend to emaphasize access to medicines as the key barrier to treatment, which decontextualizes patients from their social milieu. My project focuses on the clinic-household nexus in order to better understand how historically emdedded social relations impact treatment pathways for young children living with HIV. Specifically, I trace how gendered norms within marriage, disease etiologies, the clinical encounter, land tenancy and migration affect diagnosis and long term treatment adherence. My findings indicate that access to and the long term benefits of ART for children are mediated along socioeconomic fault lines. Although ART is an essential component of any HIV/AIDS care and treatment programme, I argue thoughout that the distribution of medicines alone is ineffective in the absence of loving caregivers, good living conditions, sustainable food sources or a robust public health care system. My research contributes to academic debates about the mechanisms behind embodied inequalities and calls for a broadened scope beyond the individual patient in the development and implementation of HIV care and treatment services for children living with HIV.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".