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Record W3049737205 · doi:10.1590/0103-11042020s108

Connecting the right to health and anti-extractivism globally

2020· article· en· W3049737205 on OpenAlexaffabout
Erika Arteaga-Cruz, Baijayanta Mukhopadhyay, Sarah Shannon, Amulya Nidhi, Todd Jailer

Bibliographic record

VenueSaúde em Debate · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsCentre for Movement DisordersBP (Canada)
Fundersnot available
KeywordsRight to healthEconomic growthLivelihoodHealth careSocial determinants of healthPolitical scienceBusinessDevelopment economicsAgricultureGeographyEconomics

Abstract

fetched live from OpenAlex

ABSTRACT Natural resources are essential to health and are global commons. Recognizing the devastating damage posed by extraction to health and the environment, as well as the erosion of the sovereignty of our governments that have increasingly conceded people’s health in the interest of profit and development, is important in framing our resistance. Our communities experience growing displacement, the loss of social services, of land, water and livelihood, heightened militarization, violence and repression, and increased incidence of communicable diseases and health problems resulting from exposure to toxics. All of these are linked to an extractivist project driven by global financial capital promoting an unsustainable and inequitable development model that threatens people’s health and the health of the planet. Is it compatible with the right to health to finance national health systems with revenues of activities that intrinsically destroy life? The essay portrays the inconsistency of development policies that fund health/right to health with extractivism and depicts examples of resistance to extractive industries tied to the People’s Health Movement (Canada,Turkey, India and Ecuador) in different types of governments. The need to strengthen the link between the right to health struggles and anti-extractive resistance is highlighted.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.069
Scholarly communication0.0100.007
Open science0.0010.009
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0050.000

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 head0.034
GPT teacher head0.314
Teacher spread0.280 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations10
Published2020
Admission routes2
Has abstractyes

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