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Record W4407118280 · doi:10.33137/utjph.v6i1.43999

South-North Learning in Mapuche Territory- Report back from the 10th Escuela Abierta de Salud Pública in Temuco, Araucania, Chile

2025· article· en· W4407118280 on OpenAlexaff
Lisa Nussey, Carlos Piñones Rivera

Bibliographic record

VenueUniversity of Toronto Journal of Public Health · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Education, Indigenous Social Dynamics
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsGeographyHumanitiesDemographySociologyArt

Abstract

fetched live from OpenAlex

This article summarizes the proceedings of the 10th Escuela Abierta de Salud Pública (Public Health Open School), held in the Mapuche territory, Temuco, Araucania, Chile in the spring of 2024. The free school brought together more than one hundred Indigenous and community leaders and organizers, students, clinicians, academics, educators, workers, and organizers to build collective analysis and action about health under capitalism. The conference focused on the emancipatory praxis of social determination of health and critical interculturality, which put forward transformative, meta-critical agendas for public and collective health research and practice. The article is submitted as a contribution to the growing and necessary movement for genuine South-North learning and collaboration to build a public and collective health praxis that is up to the challenge of intervening in the deepening crises of the global capitalist order.

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)0.002
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.131
Threshold uncertainty score0.261

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0030.002
Open science0.0010.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.019
GPT teacher head0.282
Teacher spread0.263 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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