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Record W2005755305 · doi:10.1890/02-5381

A TEST OF THE ENVIRONMENTAL KUZNETS CURVE USING LONG‐TERM WATERSHED INPUTS

2004· article· en· W2005755305 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

VenueEcological Applications · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsBC Hydro (Canada)University of British Columbia
FundersWisconsin Department of Natural ResourcesDivision of Graduate EducationUniversity of Wisconsin-MadisonNational Science Foundation
KeywordsKuznets curvePollutionEnvironmental qualityWatershedPollutantWater qualityEnvironmental scienceEcologyPer capitaEnvironmental degradationNatural resource economicsBiologyEconomicsEnvironmental health

Abstract

fetched live from OpenAlex

The Environmental Kuznets Curve (EKC) postulates that environmental quality is initially degraded with increasing economic prosperity, until reaching some turning point where environmental quality improves with increases in wealth. Tests using environmental indicators beyond those that affect human health have been less supportive of the EKC idea. We hypothesize that environmental changes impacting human health are more likely to show evidence of an EKC than variables less directly related to human health. Furthermore, the EKC hypothesis assumes that ecological damage is reversible, and we argue that this assumption is not always valid. We test for evidence of an EKC in Dane County, Wisconsin, using non‐point‐source pollution time series data for Lake Mendota throughout the 20th century. We examine metals deposited in lake sediments (cadmium, chromium, copper, and lead), other non‐point‐source pollutants such as sulfur and dissolved reactive phosphorus (DRP), and water clarity (measured by Secchi disk depth). We relate changes in ecological variables to changes in real wealth per capita (RWPC) in Dane County over time. The EKC did not describe the relationship between all ecological and economic indicators tested; however, several variables were related to RWPC. Our strongest results (for Secchi depth, DRP, and copper) show increasing pollution with increasing wealth. Secchi depth and DRP are related to water quality and clarity, which have value to society but less direct, immediate health consequences. P pollution may also be fairly irreversible over short time scales. The best models and plots for cadmium, chromium, and lead suggest improvements in environmental quality with increases in RWPC, although these trends were not statistically significant. Results for sulfur were inconclusive. Overall, wealth did not explain much of the variability in any of the ecological variables examined here, suggesting that consideration of additional factors are necessary to explain their dynamics. Economic prosperity cannot be expected to improve all aspects of the environment, but may be biased toward aspects that are ecologically reversible phenomena or of concern to human health.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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