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Record W3088605958 · doi:10.3926/hdbr.121

Economics and environment: An impossible reconciliation?

2019· article· en· W3088605958 on OpenAlexaff
Alberto Díaz de Junguitu, Iñaki Heras Saizarbitoria, Olivier Boiral

Bibliographic record

VenueHarvard Deusto Business Research · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

It should be noted that the relationship between economics and the environment has never previously featured as one of mankind’s primary or principal concerns. It presently does. The recent worldwide student mobilization for climate action, the Climate Change Congress in Paris (December 2015) or the dieselgate related to the scandals involving companies in the automobile sector not complying with regulatory environmental norms (which started also in 2015), among many other issues, provide evidence that this relationship is presently of central concern to questions regarding the future of mankind. Nevertheless, we should remind ourselves of the fact that, despite being a recurrent theme in the media, the environment continued to be a treated by economists as a subsidiary issue until, in relatively recent times, the effects of the global environmental crisis grew to proportions that meant it became of serious concern to the future of mankind. The aim of this paper is to trace the historical relationship between the environment and economics. In fact, the focus is more modest: we aim to illustrate the principal traces of the presence of the environment in economic science in an attempt to exhibit a path which might lead to the reconciliation of the one (the environment) with the other (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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0170.019

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 head0.029
GPT teacher head0.275
Teacher spread0.247 · 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; both teacher heads agree on what is shown here.

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
Published2019
Admission routes1
Has abstractyes

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