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Record W2954968964 · doi:10.31014/aior.1992.02.03.107

The Impact of IFRS Adoption on Earnings Management-Results from Canada

2019· article· en· W2954968964 on OpenAlex
Kousay Said

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Economics and Business · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsFanshawe College
Fundersnot available
KeywordsLeverage (statistics)Earnings managementBusinessAccountingEarningsPanel dataVariablesEconomicsEconometricsStatistics

Abstract

fetched live from OpenAlex

The purpose of this paper is to find out the impact of the adoption of IFRS on the practice of earnings management. It provides empirical results using panel data from 2000 to 2018 of the 19,869 firm-year observations of available data from 791 Canadian firms based on the Modified Jones model. The result of our study supports that there is the existence of earnings management practice. The overall result was negative but not significant suggesting adopting IFRS has no direct influence on earnings management used among publicly listed firms. In addition, this paper examined the influence of firm factors (independent variables) of leverage, return on assets, and enrings growth, the interaction variables of IFRS adoption on earnings management. Obtained results in this paper indicate the interaction variable of IFRS adoption is positively related with earnings management, but not significant, suggesting that adopting IFRS has no direct influence on earnings management used among publicly listed firms.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.183
Teacher spread0.177 · 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