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Record W4399551228 · doi:10.1080/08865655.2024.2363198

Back to the Future: Winnipeg’s Reinvention from Borderland Trade and Transportation Gateway to Globalized Trade and Transportation Hub

2024· article· en· W4399551228 on OpenAlexaffvenueabout
Randy William Widdis

Bibliographic record

VenueJournal of Borderlands Studies · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsGateway (web page)International tradeGlobalizationBusinessEconomyPolitical scienceEconomic geographyEconomicsComputer scienceLaw

Abstract

fetched live from OpenAlex

Winnipeg’s location at almost the geographical center of the North American continent has historically made it an important transportation focal point with connections that have integrated the city with places and regions beyond its southern Manitoba boundaries. Winnipeg is also both a borderland city, with historically important links to American centers to the south, and a regional gateway and hub, with strong connections to the rest of Canada. This paper explores the history of Winnipeg as a transportation and trading center and focuses on its early borderland associations with the upper Midwest and northern Plains, its emergence and decline as the major metropolis and gateway to the Canadian West, and its recent efforts to draw upon the past in order to reinvent itself as a Great Plains, North American, and global trade and transportation hub. In doing so, the essay adds to the pre-existing literature that exists regarding Winnipeg as a historical trade center by examining how governments and businesses have integrated and managed globalization processes and geographical features in their desire to make the city more competitive. In particular, it focuses on the role that Winnipeg’s inland dry port – CentrePoint Canada – plays in achieving this objective.

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 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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.634

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 communication0.0000.001
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 head0.017
GPT teacher head0.252
Teacher spread0.235 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations1
Published2024
Admission routes3
Has abstractyes

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