The Innovation Imperative in Global Health: Gendered Futurity in the Sayana® Press
Bibliographic record
Abstract
In this Position Piece, we explore the hegemony of innovation and the construction of gendered futures in global health through the Sayana® Press, a device that delivers a version of the contraceptive drug commonly known as Depo-Provera. The device has generated tremendous enthusiasm amongst global family planning advocates for its effectiveness and ease of use, including administration by community level providers and self-injection. Claims about its potential are compelling: advocates hope it will dramatically increase access to contraceptives, and thereby unlock the social and material emancipatory promise of family planning. We offer preliminary observations about Sayana Press as an ethnographic and discursive object and further the scholarly conversation on humanitarian design by considering the gendered dimensions of global health technologies. The advent of Sayana Press reflects several significant trends in global health including the intensification of the innovation imperative and the bypassing of investments in infrastructure—both bolstered by the recent rise of the ‘self-care agenda’. Further, we suggest that global health technologies are also techniques in the Foucauldian sense—scripting new subjectivities and bodily norms towards gendered futurities. Finally, we note the dual role of the state in sexual and reproductive health as both source and object of reproductive governance.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.049 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".