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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.<br>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. <br>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 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.836
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.210
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 teacher head, not a consensus.

Study designQualitative
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

Citations0
Published2025
Admission routes1
Has abstractyes

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