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The spatial economy of North American trade fairs

2012· article· en· W1907254018 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicConferences and Exhibitions Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExhibitionContext (archaeology)SituatedEconomic geographyReflexivitySpace (punctuation)Field (mathematics)EconomyEconomicsGeographySociologySocial science

Abstract

fetched live from OpenAlex

Through a study of trade fairs, this article illustrates that relational approaches to economic geography are not limited to the sphere of economic and social relationships. These relationships are influenced by and, in turn, shape material realities, such as specific infrastructure and the labour market, in a reflexive manner. Trade fairs are “relational events” that bring together regional, national, and often international producers, users, suppliers, and other agents of a value chain or technology field for the purpose of exchanging knowledge about technological and market developments, building partnerships, and maintaining existing networks through learning by interaction and observation. However, these events are also situated in space and time, grounded in the contexts of particular industries, trade patterns, public and private investments, as well as the economic geographies of places. Focusing on North America, this article presents and analyzes data on the economic geography of trade fairs and their regional economic impact (number of events, exhibitors, attendees, exhibition space). It explores regional trade fair patterns and dynamic changes in major trade fair cities by emphasizing the role of history and industry context.

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 categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.508
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.004
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.210
Teacher spread0.200 · 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