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Record W1993775240 · doi:10.2190/hs.40.3.i

Women's Health in Developing Countries: Beyond an Investment?

2010· article· en· W1993775240 on OpenAlexaff
K. S. Mohindra, Béatrice Nikièma

Bibliographic record

VenueInternational Journal of Health Services · 2010
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsInstitute of Population and Public HealthUniversity of Ottawa
FundersWorld Health Organization
KeywordsInstrumentalismMillennium Development GoalsAgency (philosophy)Economic growthInternational developmentPublic healthPolitical scienceHealth policyIdeologyDeveloping countrySociologyDevelopment economicsPublic relationsMedicineEconomicsHealth careSocial sciencePoliticsLaw

Abstract

fetched live from OpenAlex

Most international programs and policies devised to improve women's health in developing countries have been shaped by powerful agencies and development ideologies, including the tendency to view women solely through the lens of instrumentalism (i.e., as a means to an end). In a literature review, the authors followed the trail of instrumentalism by reviewing the different approaches and paradigms that have guided international development initiatives over the past 50 years. The analysis focuses on three key approaches to international development: the economic development, public health, and women-gender approaches. The findings indicate that progressive changes have adopted a more inclusive development perspective that is potentially beneficial to women's health. On the other hand, most paradigms have largely viewed improving women's lives in general, and their health in particular, as an investment or a means to development rather than an end in itself. Public health strategies did not escape the instrumentalism entrenched in the broader development paradigms. Although there was an opportunity for progress in the 1990s with the emergence of the human development and human rights paradigms and critical advances in Cairo and Beijing promoting women's agency, the current Millennium Development Goals project seems to have relapsed into instrumentalism.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.336
Teacher spread0.323 · 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 designObservational
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

Citations21
Published2010
Admission routes1
Has abstractyes

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