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Record W2957220174 · doi:10.1080/14693062.2019.1627178

Mid-Century Strategies: pathways to a low-carbon future?

2019· article· en· W2957220174 on OpenAlexaff
Narayan Gopinathan, Narayan Subramanian, Johannes Urpelainen

Bibliographic record

VenueClimate Policy · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSWORDUnderpinningJurisdictionClimate policyQuality (philosophy)BusinessEconomicsEnergy sectorStylized factIndustrial policyPolitical scienceClimate changeEconomic systemInternational tradeEngineering

Abstract

fetched live from OpenAlex

ABSTRACT Since the Paris Agreement was adopted in 2015, both national and subnational governments have been encouraged to submit Mid-Century Strategies, outlining how they would reach their deep decarbonization goals. However, research on the design and potential of these strategies has been very limited. To address this shortcoming, here we assess 13 such strategies – six national, seven subnational – in a comparative fashion. We find that the energy-economy-climate models underpinning these strategies are generally of high quality, though national jurisdictions generally performed better. However, most strategies are not plausible without significant changes to policy, and the industrial sector in particular presents a major limitation. The strategies are helpful in revealing this gap, but much works remains to be done for plausible mid-century decarbonization trajectories to become a reality. We also find that public input and societal participation in strategy building were a double-edged sword depending on the constellation of domestic preferences. Key policy insights Governmental Mid-Century Strategies for deep decarbonization are underpinned by high-quality energy-economy-climate models Governments’ proposed strategies require significant new policies, as even among jurisdictions that have an MCS, extant policies are insufficient to achieve deep decarbonization No jurisdiction studied has yet put forward a plausible decarbonization policy for the industrial sector. Public input and societal participation can be a double-edged sword: they can increase durability of the strategy but also enable opposing forces to mobilize against ambitious changes.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.823
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.014

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 head0.039
GPT teacher head0.248
Teacher spread0.209 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations3
Published2019
Admission routes1
Has abstractyes

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