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Record W1974294538 · doi:10.1108/14630010210811741

European versus US corporations: A comparison of property holdings

2001· article· en· W1974294538 on OpenAlexaff
Steven Laposa, Mark Charlton

Bibliographic record

VenueJournal of Corporate Real Estate · 2001
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsPricewaterhouseCoopers (Canada)
Fundersnot available
KeywordsBalance sheetVariety (cybernetics)AccountingBenchmark (surveying)Property (philosophy)BusinessBalance (ability)European marketFinancial economicsEconomicsIndustrial organizationActuarial scienceCommerceStatisticsMathematicsGeography

Abstract

fetched live from OpenAlex

This paper compares the corporate property holdings of European and US corporations. The authors initially calculate standard benchmarks based on accounting and balance‐sheet information as of 1999, and then test for significant differences by two‐digit standard industrial classification levels between European and US firms. They follow the methodology of Johnson and Keasler (1993) and compare property, plant and equipment book values to a variety of non‐property balance sheet and market value figures. However, this paper extends previous research through a comparative analysis of 1,573 US firms to 2,182 European firms. The findings suggest there are significant differences between Europe and the USA, dependent on the specific benchmark and industrial sector. The conclusions postulate a variety of explanations of the corporate property differences and provide ideas for further research.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.129
GPT teacher head0.267
Teacher spread0.138 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations39
Published2001
Admission routes1
Has abstractyes

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