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Environmental Economic Geography

2008· article· en· W1970561143 on OpenAlexaff
Roger Hayter

Bibliographic record

VenueGeography Compass · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMandateInstitutionalismSustainabilityReciprocalValue (mathematics)Resource (disambiguation)Political scienceSociologyEconomic systemEconomic geographyEconomicsEcologyPolitics

Abstract

fetched live from OpenAlex

Abstract This article advocates evolutionary institutionalism as a conceptual platform to launch a systematic approach to environmental economic geography. Evolutionary institutionalism interprets industrial transitions through the lens of innovative behaviour that is shaped by reciprocal economic and non‐economic processes and periodically restructures economies in the form of new techno‐economic paradigms (TEP). In this approach, environment–economy relations need not be zero‐sum games, as is often assumed. Rather, as a result of innovation and choice, these relations have been recalibrated historically and can be redefined again towards developing a green TEP in which development and sustainability are co‐imperatives. It is argued that the mandate of environmental economic geography is to assess and prescribe how place makes and should make a difference to a green TEP and the article sketches a research agenda to promote this goal. This research agenda focuses on the themes of regions as institutions, remapping resource use and sustainable value chains.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.006
Scholarly communication0.0060.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.019
GPT teacher head0.266
Teacher spread0.248 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations77
Published2008
Admission routes1
Has abstractyes

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