The Map and the Territory: An Ethnographic Study of the Low Utilisation of a Global eHealth Network
Bibliographic record
Abstract
Recent years were marked by the implementation of many eHealth projects using information and communication technologies to provide health services in developing countries. While generating great expectations, these projects remain poorly documented and available data suggest high failure rates. This raises a practical question: How are such eHealth networks to be effectively designed and implemented? This paper addresses this question. Specifically, it presents an ethnographic study of the Pan-African e-Network, a project which connects many hospitals all across India and Africa, providing medical teleconsultations and distance learning services. The study investigates the low utilisation of the network, an issue undermining its potential and efficiency. Factors contributing to this situation include communication barriers, the presumed ego of doctors, poor awareness of the project, and a lack of flexibility to work with the specificities of the connected sites. Above all, these factors point towards a dichotomous approach across the project's design and implementation, and taking two distinct yet related forms: (a) an ontological divide between technical and ‘non-technical’ domains; (b) a political sorting out of what is and what is not the project, aimed at neutralising and accounting for heterogeneous processes and practices. In both cases, low utilisation reveals tensions between processes of closure and control, and the openness of a life that will not be contained. Ultimately, this paper intends to destabilise binary modes of thinking as they crystallise oppositions between design and implementation, project and context, technical and social worlds, efficacy and improvisation, mastery and unruliness, map and territory.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".