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Record W35859060 · doi:10.1038/d41573-022-00126-x

Gobernanza y gobernabilidad ambiental estudio comparado

2010· article· es· W35859060 on OpenAlexaboutno aff
Juan Pablo Galeano Rey

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2010
Typearticle
Languagees
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Production Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSovereigntyConventionAgriculturePolitical scienceFood sovereigntyCorporate governanceLatin AmericansWelfare economicsGeographyEconomyBusinessEconomicsLawFood securityFinancePolitics

Abstract

fetched live from OpenAlex

It compared from a structural scheme the regulatory and politician component about the cases of genetically modified food and biofuels based on agricultural commodities in Colombia, Peru, Venezuela and Cuba during the study period 2002-2008. It determines which cases there is a pattern of governance and governance in  which both environmental and agricultural interests of energy I determine which of the four cases are affirmed to compare the concepts of food sovereignty and/ or energy. On the issue of policies to compare the objectives are the pursuit of variables that explain the similarities and differences of related public policies, regulations on the subject of legal formants are taken of the countries surveyed in the period 2002-2008 with a view to establish legal transplants and receptions associated with those policies. The conclusion in the case studies receiving transplant from an environmental perspective to the provisions of international treaties on the matter from the Rio Biodiversity Convention and 92 of the Cartagena Biosafety Protocol, Montreal. In agriculture associated with the adoption biofuels majority concluded in the cases studied a model of agro-business and approach the energy issue to the topic of energy sovereignty in the case of Venezuela and Cuba.

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 categoriesInsufficient 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 score0.360
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.234
Teacher spread0.222 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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