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Record W2921078438 · doi:10.31957/plj.v1i2.593

International Community and Indonesia’s Policy Towards Climate Change Post-2012

2018· article· en· W2921078438 on OpenAlexaboutno aff
Arie Afriansyah

Bibliographic record

VenuePapua Law Journal · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Policies and Emissions
Canadian institutionsnot available
Fundersnot available
KeywordsObligationNegotiationPolitical scienceClimate changeNormativeInternational communityState (computer science)Political economy of climate changeEconomic shortageEuropean unionFace (sociological concept)Political economyInternational tradeBusinessLawEconomicsSociologyPoliticsGovernment (linguistics)

Abstract

fetched live from OpenAlex

Throughout the international climate change regime’s development up until 2012, the emergence of new and helpful mechanisms and negotiation processes were often accompanied by setbacks such as withdrawals and unmet State obligation. The object of this study focused on international community and indonesia’s policy towards climate change. The Method of this study is normative legal research. The result of this thesis is to situate the internal/domestic climate of several States (the U.S., Canada, Brazil, Norway, and Indonesia) and one regional organization (the EU); and connect it to the outward international policies each have chosen to put forward on the negotiation table and/or submit themselves to. Given the global nature of and concern about climate change, it feels as if there is no shortage of lessons to pick – from outright refusal to be legally bound to the regime at all (the U.S.), an unprecedented and recent move of formal and official withdrawal from the regime’s key instrument (Canada), the struggles with implementation that a regional organization might face (the European Union), to the recent moves and measures in environmental protection pioneered and led by States characterized by their increasingly strong economies (Brazil, Norway, and Indonesia).

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.284
Teacher spread0.258 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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