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Record W2143294461 · doi:10.1111/1468-2427.00456

Local dimensions of global investment: Israeli property firms in Central Europe

2003· article· en· W2143294461 on OpenAlexaboutno aff
Igal Charney

Bibliographic record

VenueInternational Journal of Urban and Regional Research · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceEconomyHumanitiesCapital (architecture)GeographyWelfare economicsEconomicsArtArchaeology

Abstract

fetched live from OpenAlex

Transnational property investment has increased dramatically during the last few decades. This process has been traced by literature focusing on capital‐rich countries (e.g. the United States, Canada, Japan) and on major world cities. More recently, in tandem with the collapse of the Berlin Wall, the geographical horizons of foreign investors have broadened to include former socialist countries. This article examines the recent surge in Israeli property investment in Central Europe and argues that global flows depend on relationships between place of origin and destination. Mobility of property capital creates networks that connect cities on a transnational basis. Les investissements immobiliers transnationaux ont énormément augmenté au cours des dernières décennies. Cet aspect a été suivi et documenté surtout pour les pays riches en capitaux (Etats‐Unis, Canada, Japon, par exemple) et les grandes villes mondiales. Plus récemment, parallèlement à la chute du Mur de Berlin, les horizons géographiques des investisseurs étrangers se sont élargis aux anciens pays socialistes. L'article examine l'afflux récent d'investissements immobiliers israéliens en Europe centrale, affirmant que les flux planétaires dépendent des relations entre les lieux d'origine et de destination. La mobilité des capitaux immobiliers crée des réseaux qui relient des villes au plan transnational.

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)0.001
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 score0.866
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.096
GPT teacher head0.381
Teacher spread0.285 · 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

Citations9
Published2003
Admission routes1
Has abstractyes

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