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Record W2144433527 · doi:10.1561/000.00000012

The Environmental Goods and Services Industry

2008· article· en· W2144433527 on OpenAlex
Bernard Sinclair‐Désgagné

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

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsCenter for Interuniversity Research and Analysis on OrganizationsHEC Montréal
Fundersnot available
KeywordsSubsidyGoods and servicesNegotiationOrder (exchange)LiberalizationBusinessEnvironmental policyEconomicsIndustrial organizationNatural resource economicsEconomyFinanceMarket economy

Abstract

fetched live from OpenAlex

This paper examines the role of pollution abatement goods and services suppliers in the implementation of environmental policies. It first provides a short history of the sector, in order to identify its main segments and understand their specific structure. The impact of particular policy instruments, such as emission taxes, abatement subsidies and technical standards, on key features of industry structure (notably the size and elasticity of demand, and the degree of concentration), is then studied, together with the subsequent consequences on compliance costs. Conclusions are drawn for the appropriate design of environmental policy and for current trade negotiations concerning the liberalization of environmental services.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.618

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 studies0.0000.000
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 head0.065
GPT teacher head0.209
Teacher spread0.143 · 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

Quick stats

Citations64
Published2008
Admission routes1
Has abstractyes

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