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Record W4402599747 · doi:10.3390/su16188141

Impacts of Urbanization on Energy Consumption in the South Asian Association for Regional Cooperation Zone

2024· article· en· W4402599747 on OpenAlexaff
Tithy Dev, Morteza Haghiri, Gabriela Sabau

Bibliographic record

VenueSustainability · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsUrbanizationEnergy consumptionGross domestic productConsumption (sociology)Renewable energyPopulationEconomicsNatural resource economicsEfficient energy useBusinessAgricultural economicsEconomic growthEnvironmental healthEngineering

Abstract

fetched live from OpenAlex

Energy resources play a vital role in the process of urbanization, and the high level of energy consumption has significantly created an alarming situation for environmental degradation. Increased demand for energy consumption in the South Asian Association for Regional Cooperation (SAARC) zone is a core concern for decreasing the existing reserves of energy, especially nonrenewable energy, when the growth of urbanization is increasing also. This study investigates the impacts of urbanization on energy consumption in this region by identifying factors that influence energy use. We employed globally used econometric techniques to examine the relationship between energy use and urbanization. The results of the study indicate that all the independent variables used in the model (except urban population growth) were statistically significant with a 99% level of confidence. In addition, the findings of this study recognized three long-run causalities running from the GDP (gross domestic product) to energy consumption, energy consumption to GDP, and energy consumption to the industry’s share of the countries’ GDP. We recommend (i) taking the initiative to invest in renewable energy, (ii) implementing green energy-efficient technologies in the industrial sector, and (iii) raising public awareness of the negative effects of energy use on the environment through education.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.018
GPT teacher head0.228
Teacher spread0.210 · 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.

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

Citations11
Published2024
Admission routes1
Has abstractyes

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