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Record W3138759622 · doi:10.24908/ijesjp.v8i1.14690

Fluir como el agua en el trabajo con comunidad: Entrevista a Mariela García Vargas

2021· article· es· W3138759622 on OpenAlexvenueno aff
Mariela García Vargas, Nicolás Gaitán-Albarracín, Angie Serna, Maria Elisa Palacios Possu

Bibliographic record

VenueInternational Journal of Engineering Social Justice and Peace · 2021
Typearticle
Languagees
FieldEnvironmental Science
TopicPublic Health and Environmental Issues
Canadian institutionsnot available
Fundersnot available
KeywordsGarciaErasmus+HumanitiesPolitical scienceGeographySociologyArtArt history

Abstract

fetched live from OpenAlex

Mariela García Vargas es socióloga egresada de la Universidad Nacional de Colombia, con Maestría en estudios del Desarrollo, del International Institute of Social Studies (Erasmus University Rotterdam). Actualmente es profesora asociada en la Universidad del Valle, está adscrita al Instituto CINARA de dicha Universidad y conjuntamente con sus colegas del Instituto ha trabajado en proyectos de gestión comunitaria de agua. Durante su trayecto académico y laboral, Mariela se ha destacado por implementar el enfoque de género, la investigación participativa y resaltar la importancia del estudio sociocultural en distintos proyectos de ingeniería en Latinoamérica.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.285
Teacher spread0.277 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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