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Record W2166211670 · doi:10.1017/s1355770x0800452x

China's industrial SO<sub>2</sub> emissions and its economic determinants: EKC's reduced vs. structural model and the role of international trade

2008· article· en· W2166211670 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

VenueEnvironment and Development Economics · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsKuznets curveEconomicsPurchasing power parityChinaPer capitaPer capita incomeHeavy industryInternational tradeInternational economicsPopulationEconometricsMacroeconomicsGeography

Abstract

fetched live from OpenAlex

ABSTRACT This paper discusses the validity of the Environmental Kuznets Curve (EKC) hypothesis for the case of China's industrial SO 2 emissions: both its reduced form and structural model are considered. The EKC curve for China's per capita industrial SO 2 emissions predicts the turning point at 10,000 yuan (3,085 US$, Purchasing Power Parity (PPP)). However, given China's fast population expansion, the decreasing trend in per capita emissions may well not be enough to bring about an immediate reduction in terms of total industrial SO 2 emissions and emissions density. Using the structural EKC model makes it possible to reveal how various factors contribute to the industrial SO 2 emissions density – namely, the three commonly known structural determinants and the marginal impact of international trade. International trade proves to have a two-fold impact: a significantly negative direct one and an indirect one that is dependent on the current capital–labour abundance ratio and on the income level of each province.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.177
Teacher spread0.159 · 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