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Laboratorio Ancestral: Diseño participativo y sabidurías Kichwas en la Amazonia de Ecuador

2021· article· es· W4233109397 on OpenAlexaff
Lucía Garcés

Bibliographic record

Venuenot available
Typearticle
Languagees
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsHumanitiesArtAmazon rainforestCartographyGeographyBiology

Abstract

fetched live from OpenAlex

El artículo presentado a la Conferencia PIVOT 2021 es una reflexión en base al tema Tiempo linear Vs. Tiempo circular, enfocada en responder a la pregunta ¿Cómo cambiaría el pensamiento del futuro, si adoptáramos la noción de ancestralidad? Para responder a esta pregunta la primer parte del artículo aborda la revitalización de sabidurías ancestrales en nacionalidades indígenas de Ecuador, considerando como problemática la uniformidad de los programas educativos que a llevado a los pueblos indígenas a la asimilación de la cultura occidental. Desde está perspectiva, se propone una alternativa a la revitalización de estos saberes desde un pensamiento (de) colonial, guiado por la filosofía Andina a través del trabajo del antropólogo ecuatoriano Patricio Guerrero Arias, quien propone la noción del ¨Corazonar¨. La segunda parte de este estudio se complementa con la descripción de la experiencia de campo con jóvenes del Pueblo Kichwa de Rukullakta, en la Amazonia ecuatoriana. Este proceso creativo se enfocó en la revitalización de sabidurías ancestrales, a través de un proceso participativo que consideró conceptos, modelos y prácticas de diseño participativo, co-diseño, educación popular, investigación acción y diseño de juegos. Finalmente se presentan las herramientas co-diseñadas por los grupos de participantes para mantener, usar y difundir los sabidurías locales para las futuras generaciones.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.320
Teacher spread0.302 · 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 designTheoretical or conceptual
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

Citations2
Published2021
Admission routes1
Has abstractyes

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