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Record W4390197238 · doi:10.59670/ml.v20is12.5841

The Link between Economic Growth and Ecological Footprint: What Future Prospects for the G7 Countries: PMG-ARDL

2023· article· en· W4390197238 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

VenueMIGRATION LETTERS · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsKuznets curveEcological footprintEconomicsEnvironmental qualityNatural resource economicsRenewable energyInvestment (military)Energy consumptionDebtEnvironmental pollutionConsumption (sociology)Position (finance)MacroeconomicsSustainabilityEconomic growthGeographyEcologyEnvironmental protectionPolitical science

Abstract

fetched live from OpenAlex

Given the need to achieve economic development while preserving environmental quality, our main objective in this article is to study the impact of economic growth on the ecological footprint in the G7 countries (Italy, France, Canada, the United States, United Kingdom, Japan, Germany) over the period 1961-2018. By studying the environmental Kuznets curve (EKC) using the dynamic ARDL panel, we found that the relationship between EFP (ecological footprint) and GDP is N-shaped. In the renewable Kuznets curve (RKC), we found a U-shaped relationship. The international investment position and debt then contribute to pollution, and the consumption of renewable energy reduces CO2 emissions. However, additional efforts are needed to promote renewable energy in the countries analyzed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.201
Teacher spread0.184 · 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