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Record W2231641843 · doi:10.1057/9781137408341_5

The Human Rights Framing of Maternal Health: a Strategy for Politicization or a Path to Genuine Empowerment?

2014· book-chapter· en· W2231641843 on OpenAlexaff
Candace Johnson, Surma Das

Bibliographic record

VenuePalgrave Macmillan US eBooks · 2014
Typebook-chapter
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHuman rightsEmpowermentMillennium Development GoalsChildbirthPolitical scienceEconomic growthFraming (construction)PoliticsGlobePsychological interventionCommitMedicineDeveloping countryGeographyNursingPregnancyLaw

Abstract

fetched live from OpenAlex

Every year, more than half a million women worldwide die from complications arising from pregnancy and childbirth. Most of these deaths are preventable, examples of what Amartya Sen calls "remediable injustices" (2009, p. vii). The urgency of the issue became evident when, in 2000, governments around the globe decided to commit to "reduce maternal mortality" by three-quarters by the year 2015, making it one of the eight Millennium Development Goals (MDGs). Despite sincere and combined efforts by governments, nongovernmental organizations, and various global agencies, the goal of reducing maternal mortality by three-quarters will not be met by most countries—especially developing ones—by 2015. The struggle to improve maternal health conditions globally has led many scholars and practitioners to assert that maternal health is not simply a public health or development issue. Rather, maternal health and preventable maternal deaths are human rights issues because such deaths result from a range of factors that include but are not limited to gender inequality and discrimination, lack of adequate recognition of women's right to health, and insufficient acknowledgment of women's right to life, as well as various political, economic, social, and cultural barriers that limit women's access to appropriate interventions (Center for Reproductive Rights, 2008; Dasgupta, 2010; Hunt & Bueno De Mesquita, 2010; Yamin, 2010; Yamin & Maine, 1999).KeywordsMaternal HealthMaternal MortalityMaternal DeathPublic Health Care FacilityUniversal Health CoverageThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.801
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.027
GPT teacher head0.309
Teacher spread0.281 · 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.

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

Citations1
Published2014
Admission routes1
Has abstractyes

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