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Record W6981208646

Do differences in national cultures affect cross-country financial statement comparability under IFRS?

2017· dissertation· en· W6981208646 on OpenAlexaboutno aff

Bibliographic record

VenueIowa Research Online (University of Iowa) · 2017
Typedissertation
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsnot available
Fundersnot available
KeywordsComparabilityFinancial statementEnforcementAffect (linguistics)ModerationStatement of changes in financial positionCultural diversityQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

I examine whether cultural differences in trust towards others, materialism, and risk aversion lower financial statement comparability between countries that require International Financial Reporting Standards (“IFRS”). Evidence from various academic disciplines suggest that cultural beliefs and values affect individuals’ estimates and judgments and their consequent decisions, including economic and financial decisions. I posit that certain cultural beliefs and values also affect the estimates and judgments of corporate managers, resulting in inconsistent reporting decisions for given economic events and lower financial statement comparability. I find that two countries have lower comparability when there are greater cultural differences in trust towards others, materialism, and risk aversion. In cross-sectional tests, I find weak evidence that stronger enforcement of IFRS moderates the cultural effects on cross-country financial statement comparability. Stronger enforcement of regulations and law does not moderate the cultural effects. These findings suggest that having a strong IFRS, regulatory, or legal enforcement does not effectively moderate the impact of culture on cross-country financial statement comparability. A possible explanation is that cultural influence on financial reporting is also manifested through enforcement officials; in other words, those in charge of the enforcement are also subject to the same cultural beliefs and values as others involved in the reporting process, making moderation less likely.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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 score0.199
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.109
GPT teacher head0.459
Teacher spread0.350 · 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.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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