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Record W2792080902 · doi:10.1080/2325548x.2019.1546035

Economic Geography: A Critical Introduction

2019· article· en· W2792080902 on OpenAlex
Jamie Peck, Susan M. Roberts, Chris Muellerleile, Leigh Johnson, Shaina Potts, Trevor J. Barnes, Brett Christophers

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

VenueThe AAG Review of Books · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAgricultural geographyEconomic geographyCritical geographyStrategic geographyHuman geographyGeography of financeUrban geographyDevelopment geographyUrbanizationIndex (typography)Historical geographyGeographyEconomic globalizationCultural geographyGlobalizationEconomyEconomicsEconomic growthUrban planningFinancial crisis

Abstract

fetched live from OpenAlex

Acknowledgments vi List of Figures vii 1 Why Economic Geography Is Good For You 1 Part I Thinking Critically about Economic Geography 23 2 What Is Economic Geography? 25 3 Inventing Economic Geography: Histories of a Discipline 50 4 Economic Geography and its Border Country 76 5 Theory and Theories in Economic Geography 107 6 Method and Methodology in Economic Geography 132 7 Unboxing Economic Geography 156 Part II Doing Critical Economic Geography 185 8 Globalization and Uneven Development 187 9 Money and Finance 211 10 Cities and Urbanization 235 11 Nature and the Environment 261 12 Industrial and Technological Change 282 13 Conclusion 304 Index 314

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.971
Threshold uncertainty score1.000

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)0.0010.002

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 head0.017
GPT teacher head0.237
Teacher spread0.220 · 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