MétaCan
Menu
Back to cohort
Record W2519701470 · doi:10.17645/pag.v4i3.635

The Paris Agreement: Destined to Succeed or Doomed to Fail?

2016· article· en· W2519701470 on OpenAlexaboutno aff
Oran R. Young

Bibliographic record

VenuePolitics and Governance · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
FundersTsinghua University
KeywordsAgreementLimitingPolitical scienceMontreal ProtocolLaw and economicsPolitical economyEconomicsOzone layerEngineeringGeographyMeteorologyPhilosophyOzone

Abstract

fetched live from OpenAlex

Is the 2015 Paris Agreement on climate change destined to succeed or doomed to fail? If all the pledges embedded in the intended nationally determined contributions (INDCs) are implemented fully, temperatures at the Earth’s surface are predicted to rise by 3–4 °C, far above the agreement’s goal of limiting increases to 1.5 °C. This means that the fate of the agreement will be determined by the success of efforts to strengthen or ratchet up the commitments contained in the national pledges over time. The first substantive section of this essay provides a general account of mechanisms for ratcheting up commitments and conditions determining the use of these mechanisms in international environmental agreements. The second section applies this analysis to the specific case of the Paris Agreement. The conclusion is mixed. There are plenty of reasons to doubt whether the Paris Agreement will succeed in moving from strength to strength in a fashion resembling experience with the Montreal Protocol on ozone depleting substances. Nevertheless, there is more room for hope in this regard than those who see the climate problem as unusually malign, wicked, or even diabolical are willing to acknowledge.

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 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.001

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 head0.062
GPT teacher head0.251
Teacher spread0.189 · 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
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

Citations34
Published2016
Admission routes1
Has abstractyes

Explore more

Same venuePolitics and GovernanceSame topicClimate Change Policy and EconomicsFrench-language works237,207