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Record W1712068010 · doi:10.1111/ajes.12072

The Effect of Urbanization and Industrialization on Energy Use in Emerging Economies: Implications for Sustainable Development

2014· article· en· W1712068010 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Economics and Sociology · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsYork University
Fundersnot available
KeywordsIndustrialisationUrbanizationEconomicsEnergy consumptionConsumption (sociology)Sustainable developmentNatural resource economicsFossil fuelEconomic growthMarket economy

Abstract

fetched live from OpenAlex

Abstract This article investigates the impact of two important socio‐economic variables—urbanization and industrialization—on energy consumption in a panel of emerging economies. The results indicate that income increases energy consumption in both the long run and the short run. In the long run, urbanization decreases energy consumption, while industrialization increases it. Long‐run dynamics are important as evidenced by the estimated coefficient on the error correction term. These results have implications for sustainable development. Economic growth policies designed to increase income and industrialization will increase energy consumption. Since most energy needs in emerging economies are currently met by the burning of fossil fuels, economic growth and industrialization policies will be at odds with sustainable development.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score0.406

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 studies0.0000.000
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 head0.015
GPT teacher head0.212
Teacher spread0.197 · 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