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Record W2769923183 · doi:10.1177/0539018417742208

Economie des changements climatiques et structuration du champ de l’économie

2017· article· en· W2769923183 on OpenAlexaff
Pauline Huet

Bibliographic record

VenueSocial Science Information · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsField (mathematics)BureaucracyClimate changeSociologyPoliticsGeographyPolitical scienceRegional scienceHumanitiesEcologyMathematics

Abstract

fetched live from OpenAlex

This article deals with the Economics of Climate Change (ECC). This research area emerged in the mid-1970s and has grown exponentially since the mid-2000s. This paper is based on Richard Whitley’s characterisation of the general economic field as a ‘partitioned bureaucracy’, which makes a distinction between the centre and peripheral areas. We use bibliometric data to highlight the structure of the ECC and measure to what extent Whitley’s category helps to understand this field better. To complete these quantitative data we use qualitative data, collected via survey and interviews, and we analyse scientific publications. With the help of this combination of data, we are able to provide some explanation of the structuration of the ECC, as well as the role of interdisciplinarity and links with the political field in this process. We also provide insights about the rise of climate change and global warming in the social hierarchy of objects in economics.

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)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.008
Science and technology studies0.0020.006
Scholarly communication0.0070.006
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.101
GPT teacher head0.311
Teacher spread0.210 · 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.

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
Published2017
Admission routes1
Has abstractyes

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