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Record W4225123950 · doi:10.17157/mat.9.2.5765

The Innovation Imperative in Global Health: Gendered Futurity in the Sayana® Press

2022· article· en· W4225123950 on OpenAlexafffund
Margaret MacDonald, Ellen Foley

Bibliographic record

VenueMedicine Anthropology Theory · 2022
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsYork University
FundersLangley Research CenterYork University
KeywordsSociologyReproductive healthGlobal healthConversationEmpowermentHegemonyHealth careGender studiesPublic relationsPolitical sciencePoliticsLawPopulation

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.045
GPT teacher head0.413
Teacher spread0.369 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2022
Admission routes2
Has abstractyes

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