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Record W2557465801 · doi:10.5539/jsd.v9n6p158

Sustainable Development Discourses in China

2016· article· en· W2557465801 on OpenAlexvenueno aff
Berthold Kuhn

Bibliographic record

VenueJournal of Sustainable Development · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Development and Urbanization
Canadian institutionsnot available
Fundersnot available
KeywordsEcological civilizationChinaSustainable developmentPromotion (chess)Political scienceGovernment (linguistics)CivilizationRelevance (law)Economic growthDevelopment planEnvironmental resource managementEcologyPoliticsEconomics

Abstract

fetched live from OpenAlex

The United Nations General Assembly adopted the 2030 Agenda for Sustainable Development in September 2015. The term sustainable development will further shape international cooperation in the next decade and beyond. It is also frequently used in China’s policy documents and connects well to a set of home-grown Chinese discourses, in particular the term of ecological civilisation and the chapter on green development in the 13th Five Year Plan (FYP) approved in March 2016. This paper discusses Chinese discourses related to the promotion of sustainable development on the basis of interviews with experts – academics as well as practitioners. The hybrid character of the concept of sustainable development has been conducive to its growing relevance in China. The Chinese government, however, has also paid attention to balancing the use of the term at the level of policy formulation by promoting home-grown discourses, in particular the concept of ecological civilisation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.338

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.010
Science and technology studies0.0320.026
Scholarly communication0.0100.007
Open science0.0010.010
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.008
GPT teacher head0.254
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations25
Published2016
Admission routes1
Has abstractyes

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