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Record W4399046923 · doi:10.1080/14650045.2024.2355208

Territory, Place, Flow, and Scale: Spatial Analysis in the IPE of Trade

2024· article· en· W4399046923 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

VenueGeopolitics · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Zones and Regional Development
Canadian institutionsMcGill University
Fundersnot available
KeywordsScale (ratio)Economic geographyFlow (mathematics)Regional scienceGeographyCartographyMathematicsGeometry

Abstract

fetched live from OpenAlex

We assess the presence and use of the geographical concepts of territory, place, flow, and scale in the International Political Economy (IPE) literature on trade. While IPE scholars have arguably responded somewhat to earlier calls to embrace geography, the uptake remains limited. Relatively few articles incorporate such concepts explicitly and tend to ignore critical scholarship on these ideas. After summarizing the theoretical dimensions of territory, place, flow, and scale in geography, we analyze publications in six leading political science/IPE journals from 2010 to 2022 to identify articles related to trade that draw on one or more of these four concepts. Using a mix of quantitative text analysis and close qualitative readings of selected articles, we find that IPE scholars occasionally use territory, flow, and scale explicitly, but more often their use is implicit. In contrast, place is used rarely, only implicitly, but perhaps offers the greatest opportunity to frame new questions in studies of trade. More generally, we conclude that explicit attention to these four concepts and their use in critical geography scholarship, would help to develop richer, more critical IPE approaches.

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)0.000
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 score0.711
Threshold uncertainty score0.273

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.014
GPT teacher head0.206
Teacher spread0.192 · 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