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Record W3159737908 · doi:10.22215/cjers.v14i2.2763

Climate Change Politics in Canada and the EU—from Carbon Democracy to a Green Deal?

2021· article· en· W3159737908 on OpenAlexvenueaboutno aff
Markus Lederer

Bibliographic record

VenueThe Canadian Journal of European and Russian Studies · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsDemocracyTransformative learningArgument (complex analysis)Political sciencePolitical economyClimate changeState (computer science)Order (exchange)Economic systemSociologyEconomicsLawEcology

Abstract

fetched live from OpenAlex

The idea of a green deal transforming industrialized societies’ climate policies in a sustainable manner has become highly popular in various countries. The study takes up this notion focusing on climate policy initiatives in Canada and the EU, raising three interrelated issues: (i) on a descriptive level, the study asks where we stand and what has so far been achieved regarding climate policy; (ii) analytically, the study provides a theoretical explanation of why progress has been slow in the EU and hardly visible in Canada, making use of the concept of carbon democracy; (iii) on a prescriptive level, the study explores what will be needed to make a green deal successful, arguing that one has to accept that a green deal is a deeply political project that will create winners and losers and that not all losers can be compensated under the label of a “just transition”. The argument advanced is that the EU and Canada represent a form of carbon democracy in which the extensive use of carbon laid the foundation for establishing democratic institutions and strongly shaped them. The paper shows that the extensive influence of carbon-related activities not only empowers specific non-state agents but is rather deeply enmeshed in the societal and political genome of both regions’ polities. The claim that follows is that climate politics in Canada and the EU will have to be deeply transformative and therefore disruptive in order to be successful.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.096
GPT teacher head0.235
Teacher spread0.139 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations8
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueThe Canadian Journal of European and Russian StudiesSame topicClimate Change Policy and EconomicsFrench-language works237,207