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Record W7096924408

Change. Edited by Ronan Paddison and Thomas Hutton, Sage Publications, London, Forthcoming

2010· article· en· W7096924408 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional resilience and development
Canadian institutionsnot available
Fundersnot available
KeywordsSAGEFace (sociological concept)
DOInot available

Abstract

fetched live from OpenAlex

(SSHRC) and the Fonds Québécois de la recherche sur la science et la culture (FQRSC). © Tous droits réservés. RÉSUMÉ La ville résiliente: à la recherche des facteurs de succès des économies urbaines Ce texte jette un regard critique sur les facteurs de succès des économies urbaines, plus précisément, la capacité des économies locales à s’adapter à des chocs extérieurs. La résilience aux chocs prend deux formes: a) la capacité de survivre aux chocs, appelée Résilience-a; b) la capacité de changer face à des chocs, appelée Résilience-b. Des exemples de la première sont la Nouvelle-Orléans (ouragan Katrina), Nagasaki (bombe atomique) et des villes allemandes détruites durant la dernière guerre. Résilience-a est un trait quasi universel; les villes ne meurent pas, même si elles peuvent connaître un déclin. Résilience-b est plus rare. Le changement face à des événements (changements de frontières; changements technologiques…) qui menace la base économique de la ville est plus difficile. Des villes comme Boston et Chicago ont réussi à se transformer, à l’opposé

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.700

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.234
Teacher spread0.203 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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