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Record W1557976777

Stockyards Districts as Industrial Clusters in Two Western Canadian Cities

2004· article· en· W1557976777 on OpenAlexaffabout
Ian MacLachlan, Ivan Townshend

Bibliographic record

VenueOpen ULeth Scholarship (OPUS) (University of Lethbridge) · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsMetropolitan areaEconomies of agglomerationEconomic geographyLivestockResource (disambiguation)Urban agglomerationGeographyEconomyEconomic growthEconomicsForestry
DOInot available

Abstract

fetched live from OpenAlex

The stockyard was the nucleus of the livestock and meat processing agroindustry, one of the key propulsive forces in the rapid growth of western Canada at the turn \nof the century. In metropolitan centres such as Calgary and in smaller cities such as Lethbridge, stockyards functioned as transhipment points for livestock in transit \nand as markets for meat-packing plants. The activities typically drawn together by stockyards created a distinctly western Canadian industrial complex which benefited from agglomeration economies and industrial \ninertia. Nevertheless, public stockyards are now a relict urban land use and have all but disappeared from the urban landscape. The factors contributing to the waning role of stockyards are identified, with implications for the application of the theory of agglomeration economies and industrial clusters to resource-based \nindustries.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0080.003
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.070
GPT teacher head0.249
Teacher spread0.179 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2004
Admission routes2
Has abstractyes

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