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Record W1523931246 · doi:10.1108/eum0000000006188

Crossing the great divide?

2001· article· en· W1523931246 on OpenAlexaboutno aff
Seow Eng Ong, Joseph T.L. Ooi, Edward Ng

Bibliographic record

VenueJournal of Property Investment and Finance · 2001
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsPublicationPublishingRanking (information retrieval)Real estatePolitical scienceLibrary scienceReading (process)EstateGeographyRegional scienceLaw

Abstract

fetched live from OpenAlex

This study examines the issue of cross‐continental publishing in real estate research to understand the research interaction between the two major English‐speaking countries and to determine if a home bias exists. This study also determines the extent to which authors from other countries publish in US and UK journals, and provide a ranking of non‐US universities and authors. The survey of top US and UK real estate journals from 1993 through 1998 reveals that a home bias exists. The home bias concentration is higher in US journals than in UK journals, while UK journals exhibit more balanced origins, emanating not only from the USA/Canada, but also from Australia, New Zealand and Asia. In addition, the study reveals that the Universities of Reading, Ulster and Glasgow are well placed among European universities, while the National University of Singapore ranks well in Asia. Top US researchers tend to publish exclusively in US journals; likewise the same is observed for UK researchers. However, some notable exceptions are observed. Finally, a possible reason for the home bias could be the different research approaches undertaken by US and UK journals.

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 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 score0.877
Threshold uncertainty score0.268

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 studies0.0000.000
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 head0.048
GPT teacher head0.216
Teacher spread0.168 · 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

Citations13
Published2001
Admission routes1
Has abstractyes

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