MétaCan
Menu
Back to cohort
Record W3138679921 · doi:10.24908/ijesjp.v8i1.14691

Practicar el asombro: Una entrevista con Andrea Ballestero alrededor de su libro “Una Historia Futura del Agua”.

2021· article· es· W3138679921 on OpenAlexvenueno aff
Andrea Ballestero, Nicolás Gaitán-Albarracín, Claudia Grisales Bohórquez

Bibliographic record

VenueInternational Journal of Engineering Social Justice and Peace · 2021
Typearticle
Languagees
FieldEnvironmental Science
TopicEnvironmental and Cultural Studies in Latin America and Beyond
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

Andrea Ballestero es profesora asociada de antropología en la Universidad de Rice en Houston. Su trabajo busca entender las relaciones entre ética y técnica en espacios en los que es imposible separar la realidad en compartimentos delimitados por divisiones disciplinares. Así, se ha enfocado en comprender prácticas en las que se funden aspectos legales, económicos, y tecno-científicos, dando forma a lo que es posible en el mundo, pero también abriendo espacios cotidianos para la expresión de aspiraciones éticas para el futuro. En los últimos años, se ha centrado en estudiar el agua en sus múltiples formas, siguiéndola desde acuíferos hasta espacios burocráticos en los que se decide su futuro. 
 Su primer libro, “Una Historia Futura del Agua” (A Future History of Water) explora la forma en la que se producen constantemente distinciones entre el agua como derecho fundamental y el agua como mercancía. Basado en trabajo de campo con funcionarios estatales, activistas y políticos en Costa Rica y Brasil, el libro gira en torno a cuatro artefactos técnicos: una fórmula, un índice, una lista, y un pacto. Usando el asombro como lente metodológico, el libro explora la forma en la que estos artefactos llevan inscritas ciertas posibilidades de futuro, incluso mientras parecen replicar estructuras del presente.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.709
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.007
GPT teacher head0.263
Teacher spread0.256 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Engineering Social Justice and PeaceSame topicEnvironmental and Cultural Studies in Latin America and BeyondFrench-language works237,207