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Record W3204720912 · doi:10.53383/100161

International Real Estate Review

2012· article· en· W3204720912 on OpenAlexaff
Robert H. Edelstein, Steve Fortin, Desmond Tsang

Bibliographic record

VenueInternational Real Estate Review · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsMcGill University
Fundersnot available
KeywordsReal estateBusinessInternational Financial Reporting StandardsReal estate investment trustAccountingFair valueSample (material)Capitalization rateFinanceInvestment (military)Asset (computer security)

Abstract

fetched live from OpenAlex

The adoption of the new International Financial Reporting Standards (IFRS), by allowing the option of fair value accounting for real estate investment properties, has dramatically altered the landscape of financial reporting for real estate firms worldwide. In this exploratory study, by examining the financial statements and disclosures of 45 international real estate firms, we demonstrate that the implementation of IFRS has affected financial reporting practices in the real estate industry. We find that under the IFRS, companies place emphasis on market asset valuations, vis-a-vis alternative metrics for current performance. We also find that most real estate firms in our sample choose to report fair values for investment properties in their financial statements rather than the notes to the financial statements. Finally, there is a wide variation in firm disclosures with regards to the determinants of fair market values.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0470.026

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 head0.020
GPT teacher head0.288
Teacher spread0.269 · 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 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

Citations2
Published2012
Admission routes1
Has abstractyes

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