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Record W4283577133 · doi:10.1111/ropr.12493

Framing <scp>market‐based</scp> versus regulatory climate policies: A comparative analysis

2022· article· en· W4283577133 on OpenAlex
Kayla Young, Kayla Gurganus, Leigh Raymond

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueReview of Policy Research · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaCenter for Advanced Study in the Behavioral Sciences, Stanford UniversityUniversity of Ottawa
KeywordsFraming (construction)MandatePoliticsEconomicsPublic economicsContent analysisGreenhouse gasRegulatory reformBusinessPublic administrationPolitical scienceMarket economySociologyLaw

Abstract

fetched live from OpenAlex

Abstract An active debate has emerged about the political viability of market‐based versus non‐market‐based policies to address climate change. As carbon pricing policies face significant political challenges, some have argued that regulatory policies are a better option because they do not highlight consumer energy prices and can be linked to other economic and social priorities. Yet, no study has compared communication strategies for regulatory versus price‐based climate policies in practice. This paper fills that gap through a qualitative content analysis of framing strategies for Ontario's 2016 cap‐and‐trade program for greenhouse gas emissions, and Virginia's 2020 clean energy mandate. Results largely confirm the paper's primary hypothesis that similar financial frames will be used as or more frequently for the regulatory policy as for the price‐based policy, complicating any theory that regulatory policies will face an easier political path due to their different messaging options.

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.

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)0.007
metaresearch head score (Gemma)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.832
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.326
GPT teacher head0.439
Teacher spread0.113 · 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