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Record W2152773361

Approaching social change as a complex problem in a world that treats it as a complicated one: the case of puntos de encuentro, Nicaragua

2008· article· es· W2152773361 on OpenAlexfundno aff
Virginia Lacayo, Rafael Obregón, Arvind Singhal

Bibliographic record

VenueRedalyc (Universidad Autónoma del Estado de México) · 2008
Typearticle
Languagees
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsnot available
FundersYork UniversityRockefeller Foundation
KeywordsHumanitiesPolitical sciencePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

El presente estudio de caso usa principios de la Ciencia de la Complejidad como marco teórico para el análisis de la estrategia de comunicación implementada por Puntos de Encuentro, así como para explorar algunas de las críticas más recientes a las teorías y modelos de evaluación de proyectos para el cambio social. Los resultados de este estudio sugieren que Puntos de Encuentro ha aplicado de manera intuitiva varios principios de la Ciencia de la Complejidad en el diseño, implementación y evaluación de su estrategia de comunicación: la dependencia histórica y contextual del cambio social, su aspecto no lineal y paradójico, la superioridad del todo sobre la suma de las partes, la relevancia de la calidad de las relaciones y las interacciones, los beneficios del control descentralizado para el surgimiento de un nuevo orden y para la auto-organización social, y la importancia de un flujo libre, diverso y participativo de información relevante al sistema para que este pueda cambiar. Como conclusión, el artículo sugiere el uso de la comunicación para el cambio social basadas en los principios de la Ciencia de la Complejidad como estrategia alternativa para promover el cambio.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.005
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.001
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 head0.176
GPT teacher head0.349
Teacher spread0.173 · 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 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

Citations9
Published2008
Admission routes1
Has abstractyes

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