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Record W603377233 · doi:10.25071/2291-3637.37645

The Commodification of the Right to Health

2012· article· en· W603377233 on OpenAlexvenueaboutno aff
Akif Nomani

Bibliographic record

VenueHPS The Journal of History and Political Science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsnot available
Fundersnot available
KeywordsCommodificationRight to healthBusinessPolitical scienceEconomicsLawHealth careMarket economy

Abstract

fetched live from OpenAlex

Within weeks of the first few confirmed deaths caused by the H1N1 flu, it was declared a global pandemic, and just as quickly in the U.S. and Canada, a vaccine was developed and distributed en masse. The global crisis of the H1N1 flu brought to our attention the interesting relationship between globalization and the access to health care globally. Globalization, or the interconnectedness of the world's markets, laws, and cultures, and its affect on health care, provides us a glimpse into the adverse relationship of health in developed and developing countries (Fidler 191). Unfortunately, developing countries, particularly those in Africa, entered the era of globalization with far worse health conditions than those in the developed world. As a result, in 1978 the World Health Organization (WHO) and UNICEF announced the Alma-Ata Declaration, which declared the goal of providing the human right to health for all by the year 2000 (Aginam 619). However, the Alma-Ata Declaration has not been reached, and directly at fault for this failure are the processes of globalization. This paper will argue that the failure of providing health care to those living in the developing world, especially in Africa, is because of the promotion of global governance modalities like the IMF, World Bank, and the WTO, which prevents developing countries from providing health care to its people for the advancement of the global capitalistic market and transnational corporations. This paper will make this argument by examining the current health conditions of developing states. This will be followed by an analysis of the good governance agenda that Western nations believe will help improve health conditions around the world. I will then look at how the good governance agenda places greater importance on civil and political rights as

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.964
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
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 head0.049
GPT teacher head0.330
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

Citations0
Published2012
Admission routes2
Has abstractyes

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