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Record W2883952931 · doi:10.1080/00343404.2018.1490014

The double crisis: in what sense a regional problem?

2018· article· en· W2883952931 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRegional Studies · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional resilience and development
Canadian institutionsQueen's University
FundersBritish AcademyBritish Academy of ManagementCenter for International Business Education and Research, University of Illinois at Urbana-ChampaignNational Aeronautics and Space Administration
KeywordsScope (computer science)Financial crisisEnvironmental crisisEcological crisisScale (ratio)Focus (optics)SociologyEconomicsEconomyPolitical scienceEconomic geographyEnvironmental ethicsMacroeconomicsGeography

Abstract

fetched live from OpenAlex

We are now facing Andrew Sayer’s ‘diabolical double crisis’, which encompasses both a deep financial crisis and an environmental one. The scale, scope and nature of this double crisis is downplayed in the regional studies literature, much of which still focuses on innovative growth models often divorced from broader social and ecological contexts. To help solve both crises we call for regional studies to explore new models that allow a focus to be made on the most important issues of our time. We illustrate this by focusing on the contradictions in the waste produced by contemporary regional economies: waste of abundance, labour and resources.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score0.928

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.135
GPT teacher head0.306
Teacher spread0.171 · 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