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Record W3124979806

Lost in Translation: Problems of Rendering the Term Sustainable Development into Non-Western Languages As Demonstrated in the Case of South Korea

2015· article· en· W3124979806 on OpenAlexaff
Kwang-Hoon Baek, Nakil Ko

Bibliographic record

VenueSSRN Electronic Journal · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability in Higher Education
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsRendering (computer graphics)Term (time)Sustainable developmentComputer scienceLinguisticsPolitical scienceArtificial intelligencePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

This study seeks to demonstrate the usefulness of a relatively underutilized approach to studying sustainable development as a term and concept. While studies on sustainable development have generally followed a normative approach seeking what the term should ideally mean, this study follows a historical approach such as recommended by the historian of philosopher Quentin Skinner to explore what changes of definition it has been capable of undergoing in the actual use. To illustrate why such changes may be a critical issue, we have deliberately focused on the case of a country – South Korea – where the very translation of the term into the native language, combined with other factors, has resulted in sustainable development being generally understood by the public as meaning something quite different from the more normative understanding of the term. Instead of a balanced development that protects the environment and promotes social welfare as well as promoting economic growth, sustainable development in the standard Korean translation has come to be understood as simply meaning continued economic growth, which is to be sought even at the expense of environmental degradation. For documentation and analysis, we have relied on various methods, while focusing on key sectors and select policy areas, including energy. We conclude with further reflections on why an approach such as ours might be a useful methodological addition in sustainable development research.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.121
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.327
Teacher spread0.305 · 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.

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

Citations2
Published2015
Admission routes1
Has abstractyes

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