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Record W4366987794 · doi:10.29173/psur338

Why Market-Based Approaches to Climate Change Won't Save the Planet

2023· article· en· W4366987794 on OpenAlexaffvenue
Tina Kim

Bibliographic record

VenuePolitical Science Undergraduate Review · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDegrowthHegemonyClimate changeEconomicsPolitical economyPoliticsEconomic systemPlanetary boundariesNeoliberalism (international relations)Green growthMarket economyNeoclassical economicsPolitical scienceEcologyLawSustainabilitySustainable development

Abstract

fetched live from OpenAlex

Market-based approaches to climate change incentivize firms to change their environmentally destructive practices. Examples include the carbon tax and the cap-and- tradeprogram. It is assumed they are the most efficient and effective way to combat climate change. Therefore, market-oriented responses to climate change have already been implemented globally and are celebrated within the western political discourse. However, the effectiveness of market-based solutions has been over-emphasized to fit the interests of corporations, leading to major problems. Therefore, market-based approaches are not just nor effective: they are within the capitalist hegemony which perpetuates the climate crisis. To resist the capitalist hegemony, selective degrowth is necessary: structurally and fundamentally changing our relationship with nature and each other for the better. I argue that implementing degrowth is an approach that truly responds to the climate crisis in a just and decolonial way.

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)0.003
metaresearch head score (Gemma)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.807
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.006

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 head0.387
GPT teacher head0.313
Teacher spread0.074 · 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
GenreCommentary

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

Citations5
Published2023
Admission routes2
Has abstractyes

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