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Record W1554775715 · doi:10.7202/800629ar

Un cadre analytique pour étudier l’impact économique des autoroutes interurbaines : une application à la région de Montréal

2009· article· en· W1554775715 on OpenAlexaffvenueabout
Mario Polèse, Jean-Claude Thibodeau

Bibliographic record

VenueL Actualité économique · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economic and Spatial Analysis
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsDiversification (marketing strategy)Tertiary sector of the economyUrban structureService (business)GeographyEconomic geographyWelfare economicsRegional scienceEconomyBusinessEconomicsCivil engineeringEngineeringUrban planningMarketing

Abstract

fetched live from OpenAlex

In this paper, the authors propose a framework which enables them to analyse the economic impact of new highway links between Montreal and eleven surrounding cities, specifically the impact on the economic structure of those cities. The authors observe a relationship between changes in accessibility (to Montreal) and economic structure. Greater accessibility resulting from new highway construction seems generally to favour industrial growth and diversification, although a very rapid and radical change in accessibility can also have negative consequences on the short run. The service sector appears particularly sensitive to changes in accessibility. The authors observe a cut off point of one hour's travel time: as soon as city falls within this travel-time zone its service sector (especially more the sophisticated services) systematically declines. Finally, the authors conclude that the precise nature of the impact of increased accessibility to Montreal is largely a function of the original economic structure of the city concerned: certain structures are more sensitive to changes in accessibility than others.

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)0.001
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score0.741

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.026
GPT teacher head0.229
Teacher spread0.204 · 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
Published2009
Admission routes3
Has abstractyes

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