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Financiación al Desarrollo Sostenible a través de Inversiones de Impacto (II): Hacia la Construcción de un Framework Teórico

2017· article· es· W2769068223 on OpenAlexaff
Orlando Enrique Conteras Pacheco, Alejandra Barbosa Calderón

Bibliographic record

VenueCuadernos Latinoamericanos de Administración · 2017
Typearticle
Languagees
FieldSocial Sciences
TopicHigher Education and Sustainability
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesPolitical scienceGeographyArt

Abstract

fetched live from OpenAlex

Una inversión de impacto (II) se define como la colocación de recursos financieros en empresas, queapuntan a resolver problemas sociales y ambientales de manera medible, rentable y escalable. El presente artículo pone de manifiesto la oportunidad de desarrollo académico de la temática concerniente a las II, con el objetivo de preparar el proceso de construcción de un framework teórico fundamentado en la elaboración de un marco conceptual y la mención de casos de estudio como instrumentos explicativos. De esta forma, se muestra como algunos fondos de impacto han comenzado a desplegar su accionar en los sistemas productivos de algunos países latinoamericanos y generan valor de largo plazo a través del apoyo de proyectos y emprendimientos basados en criterios que difieren de los aplicados tradicionalmente por inversionistas convencionales. Las contribuciones obtenidas en el estudiodan cuenta de las condiciones exigidas por estos fondos para depositar confianza en ideas que pretenden ser sostenibles, y de los tipos de negocio que tienen la capacidad de atraer dichos inversores, como es el caso de los emprendimientos sociales, las eco-innovaciones, y los negocios orientados a la base de lapirámide social de las regiones y países.

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0050.005
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.002
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 head0.019
GPT teacher head0.366
Teacher spread0.347 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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