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Record W6955207232 · doi:10.57912/28607873

INTEREST-BASED EXPLANATIONS OF THE STRINGENCY OF CARBON-PRICING POLICIES: THREE ANALYTICAL APPROACHES

2025· dissertation· en· W6955207232 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typedissertation
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsQualitative comparative analysisArgument (complex analysis)PoliticsIdeologyRealmEnergy policyStakeholderGreenhouse gasProcess (computing)

Abstract

fetched live from OpenAlex

Putting a price on emissions is one of the most efficient ways to fight climate change. However, in spite of the international community’s efforts, most carbon-pricing policies (CPPs) fall short of the stringency needed to reach the commitments of the Paris Agreement. Given that abating emissions imposes costs on specific actors within a national economy, the policy design and implementation of mitigation policies are still in the realm of domestic decision-making. This dissertation investigates the political economy determinants of the stringency of CPPs. It argues that specific constituencies –the emission-intensive trade exposed sectors and the fossil fuel industry– influence the policymaking process to lower CPP stringency because they would pay the cost of commodifying emissions. Chapter 1 uses a non-traditional instrumental variable and finds negative and statistically significant associations between industrial output size and the CPP stringency in 34 countries from 1990 to 2015. Chapter 2 develops an argument that follows from the findings in chapter 1, using process-tracing to assess the “who and how” of stakeholder influence in three Mexican policies, the carbon tax, the Law for Energy Transition and the pilot cap-and-trade. Chapter 3 uses a qualitative comparative analysis to analyze subnational CPPs in North America. It includes 45 cases in which states and provinces in Canada, Mexico, and the United States, have sought to implement these policies. Overall, the chapters find that regardless of the levels of economic development, ideological orientation, institutional design, and other conventional wisdom variables, interest-based considerations influence CPP stringency the most. The dissertation uses three different methods –deductive statistical inferences, process-tracing, and qualitative comparative analysis– to demonstrate how calculations of costs and benefits shape the current landscape of national and subnational CPPs. The work closes with policy recommendations that acknowledge that policymakers must consider political economy forces and engage with powerful stakeholders in the design of these policies.

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)0.011
metaresearch head score (Gemma)0.020
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: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0060.005
Science and technology studies0.0020.015
Scholarly communication0.0080.009
Open science0.0050.006
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0150.001

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 head0.210
GPT teacher head0.366
Teacher spread0.156 · 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
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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