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Record W4324336897 · doi:10.18280/ijsdp.180203

Environmental Sustainability Index for Colombia: Implications and Considerations for Its Calculation

2023· article· en· W4324336897 on OpenAlexvenueno aff
David Alberto García-Arango, Andrés Felipe Puerta-Molina, Uvenny Quirama-Estrada

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityIndex (typography)Environmental Sustainability IndexEnvironmental scienceEnvironmental resource managementNatural resource economicsEnvironmental protectionEconomicsComputer scienceEcology

Abstract

fetched live from OpenAlex

In recent years, there has been a growing need to consider environmental sustainability as a main component in the development of countries.This is how, within the framework of the Sustainable Development Goals, environmental sustainability is an important component of directing investment projects and is on the agenda of a good part of the developed and emerging countries.In this paper, components are considered for the calculation of an environmental sustainability index, using at a methodological level the behavior of the energy sector, waste management, air quality, pollution levels, optimization in the use of the earth and biodiversity.The final diagnosis for Colombia shows a good behavior of the indicators where 14 of 18 have improved substantially over time, showing a real commitment in environmental terms, while for the rest of the metrics, there are government initiatives that seek to reduce the problem.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.096
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.006
Science and technology studies0.0010.000
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.022
GPT teacher head0.281
Teacher spread0.259 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2023
Admission routes1
Has abstractyes

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