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Record W599059568 · doi:10.4337/9781849806923

Economic Strategies for Mature Industrial Economies

2010· book· en· W599059568 on OpenAlexaboutno aff
Peter Karl Kresl

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2010
Typebook
Languageen
FieldSocial Sciences
TopicLocal Government Finance and Decentralization
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsEconomic geographyBusinessEconomyIndustrial organization

Abstract

fetched live from OpenAlex

Contents: 1. Introduction Peter Karl Kresl 2. Global Competitiveness and the Role of Higher Education/Community Partnerships David J. Maurrasse 3. Montreal's Technological and Cultural Clusters Strategy: The Case of the Multimedia, and Film and Audiovisual Production Diane-Gabrielle Tremblay 4. The Knowledge Base, Research and Development and Regional Economic Policy-the US and UK Experience W.F. Lever 5. Government and Governance: How to Build and Sustain a Consistent Focus: The Case of Three Italian Cities Stefano Mollica, Marco Lucchini and Giovanna Hirsch 6. Economic Structure and Business Organization in the Central Region of Mexico Jaime Sobrino 7. Cooperation and Competition Between Cities: Urban Development Strategies in Hong Kong and Shenzhen Jianfa Shen 8. A City Loses its Major Industry - What Does it Do? The Case of Turin Daniele Ietri 9. Northeastern US Cities and Global Urban Competitiveness Ni Pengfei 10. Industrial Tourism: Opportunities for City and Enterprise Leo van den Berg, Alexander Otgaar, Christian Berger and Rachel Xiang Feng 11. An Aging Population and the Economic Vitality of Pennsylvania's Cities and Towns Peter Karl Kresl 12. The Repositioning of Cities and Urban Regions in a Global Economy Saskia Sassen Index

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.339
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0060.002
Open science0.0010.000
Research integrity0.0020.001
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 head0.030
GPT teacher head0.267
Teacher spread0.237 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2010
Admission routes1
Has abstractyes

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