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Record W7110638836

Elementos y herramientas de decisión para la conservación y manejo de paisajes altamente transformados. El caso del Bosque Modelo Risaralda (Risaralda, Colombia)

2025· article· es· W7110638836 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTesis Doctorals en Xarxa (Consorci de Serveis Universitaris de Catalunya) · 2025
Typearticle
Languagees
FieldEnvironmental Science
TopicEnvironmental and sustainability education
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceWork (physics)Latin AmericansEnvironmental governanceQualitative analysisProbabilistic logic
DOInot available

Abstract

fetched live from OpenAlex

ENG- The Model Forests are a platform for action for sustainable landscapes, which was born in Canada and after the Rio de Janeiro Meeting expanded throughout the world. This platform, in Colombia, has existed in a single territory, Risaralda Department, in Colombia, for a period of 16 years and more recently in the Aburra Valley, since 2022. The Model Forests are integrated into a Latin American Network of Model Forests. This is the first time that quantitative and qualitative methods have been applied in the RLABM to address the study of tools and methodologies focused on governance and conservation. The doctoral thesis focused on developing elements and tools for the governance and conservation of the Risaralda Model Forest. The Model Forest is a large territory located between the Central and Western Cordilleras of Colombia and whose borders coincide with the political- administrative delimitation of the Department of Risaralda. The work was approached, with qualitative and quantitative methodologies, in four components that allowed understanding landscape dynamics, understanding the transformation of these landscapes and social dynamics in these landscapes: an analysis of metrics and landscape dynamics, an analysis of networks and interrelations between actors or interested parties and a governance model design based on five criteria and seven indicators that allowed organizing extensive bigrams, performing natural language processing and subsequently using the LDA (Latent Dirichlet Allocation) probabilistic model that directed much of the work of building interrelations and contributed the elements to the governance model. The components analyzed produced some expected findings, as in the case of landscapes, where the conceptual framework of conservation biology was available, and where the most recent analysis of landscape dynamics was produced, finding significant fragmentation and the lack of cores from which the sustainability of the landscape can be guaranteed. In the case of networks, documentary sources of public policy were reviewed and interviews were conducted throughout the territory and with multiple actors or interested parties. It was found that governance, deduced from the documentary, is biased towards the institutional, although in the analyses, based on the interviews, it is the network of relationships between citizens, institutions and organizations, which appears strongly linked to decisions and governance, although not sufficiently recognized in public policy. The purpose, if one can say, was to provide the Risaralda Model Forest with a governance model that recognized what was found from the public and social aspects and that would allow strengthening efforts and decisions aimed at strengthening sustainable landscapes in the case study of the Risaralda Model Forest. It is hoped that this study will offer elements that can be replicated to other Model Forests to review their governance in transformed landscapes

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.283
Teacher spread0.272 · 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