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Record W4389792120 · doi:10.51594/ijae.v5i9.647

ECOLOGICAL ECONOMICS IN THE AGE OF 4IR: SPOTLIGHT ON SUSTAINABILITY INITIATIVES IN THE GLOBAL SOUTH

2023· article· en· W4389792120 on OpenAlexaff
Prisca Ugomma Uwaoma, Emmanuel Osamuyimen Eboigbe, Simon Kaggwa, Deborah Idowu Akinwolemiwa, Stephen Osawaru Eloghosa

Bibliographic record

VenueInternational Journal of Advanced Economics · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Technological Innovation
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSustainabilitySustainable developmentIndustrial RevolutionEcological economicsPolitical scienceEconomic growthEconomicsBusinessEcology

Abstract

fetched live from OpenAlex

The study presents an overview of ecological Economics in the Age of 4IR with spotlight on Sustainability Initiatives in the Global South. This study delves into the intersection of ecological economics, the Fourth Industrial Revolution (4IR), and sustainable development initiatives in the Global South. It explores the environmental implications of key 4IR technologies, analyzes economic shifts associated with the digital age, and investigates sustainability initiatives in the Global South. The study highlights successful projects in renewable energy, circular economy practices, and biodiversity conservation, showcasing the region's commitment to ecological and economic sustainability. Challenges and opportunities are discussed, emphasizing the role of inclusive innovation and global cooperation in shaping a future that harmonizes technological advancements with environmental well-being. The study concludes by underscoring the importance of the Global South in influencing a sustainable trajectory in the age of the 4IR. Keywords: Ecological; Economics; 4IR; Sustainability; Global South.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.007
Scholarly communication0.0040.007
Open science0.0000.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.040
GPT teacher head0.285
Teacher spread0.245 · 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 designTheoretical or conceptual
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

Citations30
Published2023
Admission routes1
Has abstractyes

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