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Fraying Over Paying: Who Will Bear The Costs Of Greenhouse Policy?

2008· book-chapter· en· W4388434140 on OpenAlexaboutno aff
Tracy Snoddon, Randall Wigle

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsSubsidyGreenhouse gasKyoto ProtocolDemiseGovernment (linguistics)Climate changeEmissions tradingPlan (archaeology)BusinessEconomicsNatural resource economicsPublic economicsPolitical scienceMarket economyGeography

Abstract

fetched live from OpenAlex

Abstract When the Kyoto Protocol came into force in February 2005, there was a rekindling of interest in climate change policy in Canada, culminating in the release of the federal government’s Project Green plan that year. Project Green and its precursor, the Climate Change Plan (CCP), proposed a mix of policy instruments including tradable permits, sectoral exemptions and a heavy reliance on voluntary and targeted measures to achieve the Kyoto target of reducing greenhouse gas emissions to 6 per cent below 1990 levels by 2010.1 Most of the targeted measures take the form of subsidies for the adoption of certain abatement technologies and command and control measures. Both plans have been criticized because they are likely to achieve only limited short-term reductions without helping to achieve future reductions at a more modest cost.2 The recent election of a conservative minority federal government in January 2006 has led to the effective demise of Project Green and an uncertain future for climate change policy in Canada. In this chapter, we investigate two alternatives to Project Green. Specifically, we consider the plan proposed by Jaccard, Rivers, and Horne (2004) with the alternative of a purely emissions-based scheme where all emitters are charged a price equal to the world price of carbon permits (international permit trading). The package proposed in Jaccard, Rivers, and Horne (2004) (hereinafter referred to as ‘JRH’) relies on market-oriented regulation and tradable permits. With these instruments, the JRH plan targets energy adoption decisions, laying the groundwork for larger medium to long-run reductions in greenhouse gas emissions.

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)0.007
metaresearch head score (Gemma)0.026
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 score0.033
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.012
Scholarly communication0.0130.014
Open science0.0020.003
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0170.002

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 head0.087
GPT teacher head0.246
Teacher spread0.158 · 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
Published2008
Admission routes1
Has abstractyes

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