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Record W2003028356 · doi:10.1111/1911-3838.12028

Regroupements d'entreprises et IFRS: le cas de GlobeCom Corporation et Synthetics Inc.

2014· article· fr· W2003028356 on OpenAlexaffvenueabout
Yves Bozec, Philémon Rakoto

Bibliographic record

VenueAccounting Perspectives · 2014
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsMergers and acquisitionsAccountingBusinessInternational Financial Reporting StandardsEnforcementCorporationFinancePolitical science

Abstract

fetched live from OpenAlex

This case addresses the accounting for mergers and acquisitions in Canada. Since January 1, 2011, any new transactions from mergers and acquisitions made by a public company must be recorded in accordance with the International Financial Reporting Standards (IFRS). In the case of a partial acquisitions, two theoretical approaches to accounting is allowed under IFRS 3: the approach of a separate entity and the modified approach of the parent entity. For mergers and acquisitions that occurred before this date, firms could either be early adopters to IFRS or firms could apply the Canadian standards that were allowed at the time of reunification. Under Canadian GAAP (CICA, Chap. 1581), partial acquisitions are accounted for using the approach of the parent entity. Canadian public companies that have chosen to recognize their business combinations which occurred before January 1, 2011, according to the approach of the parent entity, may continue to do so even after the enforcement of IFRS. Thus for years to come, we can see in the financial statements of various Canadian public companies business combinations presented in three different ways: according to the separate entity approach, the parent entity approach and, the modified approach of the parent entity. We also include in the case the U.S. GAAP for mergers and acquisitions. In this case, we strongly draw on an acquisition that actually happened, which we adapted to illustrate the three theoretical approaches to account for mergers and acquisitions. In particular, we have changed the name of the company.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.509
Threshold uncertainty score0.989

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0070.004
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0100.002

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 head0.035
GPT teacher head0.325
Teacher spread0.291 · 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
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
Published2014
Admission routes3
Has abstractyes

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