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Record W216671121

High Tech Services Diffusion Points to a New Urban Hierarchy : The Case of Large French Cities/ la Diffusion Des Services De Haute Technologie et Les Changements De la Hierarchie Urbaine

2005· article· fr· W216671121 on OpenAlexvenueno aff
Jacques Fache

Bibliographic record

VenueCanadian Journal of Regional Science · 2005
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsUrban hierarchyHierarchyHumanitiesEconomic geographySociologyPolitical scienceGeographyRegional sciencePopulationArt
DOInot available

Abstract

fetched live from OpenAlex

A diffusion process approach to high technology activities' dynamics represents a good indicator of changes in urban structure and national hierarchy. The case of computing services allows us to see that the development of innovative activities constitutes a crucial factor in a city's ability to change categories and acquire metropolis status or miss the opportunity and be relegated to that of an ordinary city. Une approche basee sur les processus de diffusion des activites de haute technologie represente un bon indicateur des changements de structures urbaines et de hierarchie nationale. Le cas des services informatiques permet de voir que le developpement des activites innovantes est un facteur primordial pour expliquer pourquoi une ville peut changer de categorie et devenir une metropole plus grande, ou, par contre, peut aussi decliner pour devenir une ville ordinaire. ********** Analysing the spatial diffusion of innovative activities is becoming a standard way of treating the question of localisation dynamics. Principles of contact and hierarchical diffusion have been verified in numerous sectors such as agriculture, business, services and high technology activities. Activities linked to innovation follow the standard frameworks of diffusion models, as defined by Hagerstrand (1953-67) and improved or adapted by numerous authors. (2) It is possible to extend these theories to a large number of activities linked to knowledge only as well as high skilled employment (see, as an illustration, Michels (2000, 2001) on services for firms). Conversely, they can also be applied to justify the important role played by poor social and economic conditions in the absence of diffusion (see, as an illustration, Liefooghe (2002) on the role played by legacy in old mining regions in relation to the observed absence of the diffusion of services for firms). Most of these studies are searching for a synthetic model, or are analysing location dynamics on a one-model vision basis. These studies are quite interesting, but their conclusions reach an intersecting point between a standard perspective and a very interesting line of research. Actually, it is possible to use models in another way, as we shall try to demonstrate. The core idea of this paper is that standard diffusion processes do not just constitute a way of describing location dynamics. They also allow us to understand, compare and rank the structures as represented by the various metropolitan areas. Typically, metropolises and towns are ranked in accordance with static statistic criteria (such as population and economic growth). These parameters form the basis of a range of classifications in terms of levels of complexity (see Chevalier 2000; Bonnet 2000; Polese and Tremblay 2005). (3). But if we use the diffusion based hypothesis as a new parameter, the diffusion process may point to different urban structures as well as different stages in the evolution of the city, and most importantly, to different abilities in integrating an innovative system and playing a leading part in the development of its region. The main point concerns the ranking of cities. Can we observe large differences between the standard urban hierarchy and positions as defined by diffusion processes? According to the principles of diffusion theory, we should observe important differences between the top of the urban hierarchy and the lower levels in relation to factors such as the importance of diffusion, the timing of the when the process began and elements regarding the spreading across the region. The most advanced city would be the main metropolis, and thus constitute the diffusion pole branching out towards the rest of the system. Then, large cities should have reached an intermediate stage, and so on. If this hypothesis is verified, it would demonstrate the positive feedback between new knowledge activities and the reinforcement of established organizations. …

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)0.003
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 score0.582
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.237
Teacher spread0.220 · 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 designTheoretical or conceptual
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

Citations0
Published2005
Admission routes1
Has abstractyes

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