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Record W3124277469 · doi:10.18192/aporia.v13i1.5284

Underlying premises in medical mission trips for Madiha (Kulina) Indigenous people in the Brazilian Amazon

2021· article· en· W3124277469 on OpenAlexvenueno aff
Christian Frenopoulo

Bibliographic record

VenueAporia · 2021
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Health and Education
Canadian institutionsnot available
FundersUniversidad de la República UruguayUniversity of PittsburghTinker Foundation
KeywordsIndigenousTRIPS architectureHealth careAmazon rainforestBusinessGovernment (linguistics)Public relationsEconomic growthPolitical scienceEngineering

Abstract

fetched live from OpenAlex

This article proposes two premises that underlie biomedical health care delivery provided through medical missions to Madiha (Kulina) Indigenous Amazonian people living in forest villages. First, that health care is implemented through a set of detached transferable goods and services. Second, that health is a condition that requires the importation of knowledge and resources. The premises were induced through qualitative research on the Brazilian government’s medical missions that provide biomedical care to Madiha (Kulina) in the southwestern Amazon as part of the national health care system. Despite policy rhetoric, delivery practices disregard embedding health and health care in local infrastructure and cultural conditions. There is little or no collaboration with Indigenous healers, capacity building of the local (Indigenous) health care system, education of resident lay health monitors, or extensive and lasting infrastructural development. The article recommends reorientation of delivery to prioritize local health care infrastructure development.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.114
GPT teacher head0.488
Teacher spread0.374 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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