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Record W3133869691 · doi:10.1111/1758-5899.12920

Beyond Carbon Pricing: Tax Reform is Climate Policy

2021· article· en· W3133869691 on OpenAlexaff
Jessica Green

Bibliographic record

VenueGlobal Policy · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCarbon taxIncrementalismEconomicsMarket failurePoliticsSovereigntyExternalityPublic goodState (computer science)Emissions tradingTax reformClimate changePublic economicsMarket economyPolitical scienceMicroeconomics

Abstract

fetched live from OpenAlex

Abstract The incrementalism of carbon pricing, which includes carbon taxes and emissions trading, has led us astray. It has been proffered as a key component of climate policy, yet evidence clearly shows that its effects are marginal. It provides limited emissions reductions and has provoked considerable political controversy in key large‐emitting countries. More importantly, pricing carbon means viewing climate change as a market failure, rather than as a problem of societal transformation. But rapid decarbonization will require more than market corrections; it demands strong state intervention to reorganize the economy. In this maximalist view, the state must create public goods, rather than merely prevent public bads. This article seeks to expand our collective political imagination about climate policy, moving beyond mundane fights about the appropriate design of carbon pricing. Instead, we need to think bigger. Aggressive climate policy begins with a reassertion of state sovereignty. Multinational corporations use ‘offshore’ tax havens to avoid paying taxes. By closing loopholes on corporate tax evasion, states reaffirm one of their fundamental functions: taxation. This reform would repatriate billions of dollars in missing capital, and help create the political conditions for meaningful action on decarbonization. Tax reform, not just carbon pricing, is climate policy too.

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 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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.656
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.045
GPT teacher head0.277
Teacher spread0.232 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations4
Published2021
Admission routes1
Has abstractyes

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