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Record W2155538187 · doi:10.1111/1911-3838.12051

Earnings Quality: Evidence from Canadian Firms' Choice between <scp>IFRS</scp> and U.S. <scp>GAAP</scp>

2015· article· en· W2155538187 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAccounting Perspectives · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessAccountingInternational Financial Reporting StandardsComparabilityShareholderEquity (law)Earnings qualityEarningsQuality (philosophy)Accounting standardFinanceAccounting information systemFinancial accountingCorporate governance

Abstract

fetched live from OpenAlex

Abstract For fiscal years starting on or after January 1, 2011, Canada abandoned Canadian Generally Accepted Accounting Principles ( GAAP ) and adopted International Financial Reporting Standards ( IFRS ), but permitted firms cross‐listed in the United States to adopt U.S. GAAP instead. We document that the number of Canadian firms reporting under U.S. GAAP increased after Canada adopted IFRS . We find that cross‐listed firms are more likely to choose IFRS , if IFRS is the standard most commonly used by the leading global firms in their industry. In addition, we find that firms more likely to choose IFRS are larger, of civil law legal origin, have less U.S. operations, report exploration expense, have fewer U.S. shareholders, and report higher stockholders' equity under Canadian GAAP than under U.S. GAAP . Of these, we find that the convergence benefits of comparability with industry peers are the most significant determinant in firms' choice of standard. Further, we are unable to document changes in earnings quality from cross‐listed firms adopting IFRS or U.S. GAAP or that earnings quality changed for firms adopting IFRS relative to firms adopting U.S. GAAP .

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.

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)0.002
metaresearch head score (Gemma)0.115
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.115
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.005
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.032
GPT teacher head0.265
Teacher spread0.233 · 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