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Record W1995362889 · doi:10.2118/00-09-tn

Incorporating Environmental Costs Into Energy Planning

2000· article· en· W1995362889 on OpenAlexaff
Peter J. Catania

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2000
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsEnvironmental economicsNatural resourceBusinessProcess (computing)Modernization theoryFormative assessmentValuation (finance)Risk analysis (engineering)Environmental planningEnvironmental resource managementEconomic growthEconomicsPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Abstract The need for valuation of the costs of waste in terms of environmental degradation, not in terms of abatement or avoidance costs, is required. Additionally, the need to enforce these environmental costs into the industrial decision-making process at the formative stages of energy policies will result in a sound environmental policy. It is in the interest of industry to take a pro-active stance rather than oppose such measures. The international agenda must not only recognize the need for balanced, environmentally sound development and end use of all of our energy resources but must also incorporate equal weight with other factors and must be such that no one nation is competitively compromised. Strengthening the level of international cooperation, coordination, and communication among all energy researchers in all areas of energy research and placing education at the forefront will result in a knowledge base wherein policy issues will translate into research issues and the results of research into policy solutions. Environmental factors integrated in the earliest stages of formation of energy policies and research, rather than as an add-on at the end, will facilitate the timely development of energy systems and maintain and protect the quality of our natural environment. One of the complimentary results will be the harnessing of human resources which has been one of the greatest obstacles to modernization and the rational use of energy resources. The emerging nations who are experiencing economic growth rates double that of the developed nations place an urgency on the need to enhance and strengthen the international links among energy researchers and policy makers. Introduction Pollution threatens our natural capital, the productive value of land, air and water, therefore it threatens our very existence. The definition of natural capital by Costenza and Daly(1) is defined as a stock that yields a flow of valuable goods and services into the future. This is viewed as an environmental issue by the public at large but in actual fact it is a market failure, hence, it is an economic problem. This arises from the fact that whenever a commodity is undervalued there is a natural propensity to increase the demand until the price rises and restores equilibrium. Decisions will then be based on this new equilibrium position. On the other hand, if the commodity is continuously undervalued or is free it will result in an inefficient use of the resource. This is the basis to the problem of pollution. Costs borne by society are in general invisible even though society continues to discard the wastes of economic activity into the environment. These externalities or third party effects, either positive or negative, are imposed on parties not directly involved in the production or use of the energy resource. This is one category of social costs and benefits which are usually not taken into consideration in an unregulated market or consumptive decision-making process. If air, land and water had always had a market price, their values would have been recognized in economic terms and pollution would be minimized.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.971
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.005
GPT teacher head0.219
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations1
Published2000
Admission routes1
Has abstractyes

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