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Record W2262218254

Mergers, Acquisitions, and Controlling Shareholders: Canada and Germany Compared

2006· article· en· W2262218254 on OpenAlexaboutno aff
Aviv Pichhadze

Bibliographic record

VenueSSRN Electronic Journal · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Governance and Law
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceShareholderMergers and acquisitionsPosition (finance)AccountingBusinessMarket for corporate controlControl (management)EconomicsFinanceManagement
DOInot available

Abstract

fetched live from OpenAlex

A growing body of literature on corporate governance compares Canada to the United States and/or the United Kingdom, given their Anglo-Saxon ancestry. However, this paper compares Canada to Germany and considers an often overlooked resemblance between the two: the incidence of controlling shareholders. This is particularly important given that the two countries represent two opposing corporate governance regimes. While Canada is characterized by a market-based governance regime and Germany by a bank-based governance regime, both countries exhibit concentrated ownership structures. The similarity between corporate control mechanisms in Canada and Germany is further discussed when focusing on the narrow field of mergers and acquisitions, using examples of disputes between the holders of restricted shares and holders of superior shares, and proposed transactions for change in control. The importance of recognizing the similarity between these two countries is three-fold: (i) from a policy perspective, an understanding of Canada's corporate sector path-dependence is required for the policymaker to set rules and regulations that best serve the Canadian corporate sector; (ii) from the perspective of corporate governance, the paper serves as an initial step in the examination of Canada's unique mid-way position between the United States and the United Kingdom, on the one hand, and Germany and Japan, on the other; and (iii) from the perspective of mergers and acquisitions practice, the Canadian practitioner may have points of reference other than the United States and the United Kingdom that may be more adequate at times.

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)0.001
metaresearch head score (Gemma)0.004
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: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.596

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0050.004
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.172
Teacher spread0.166 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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Same venueSSRN Electronic JournalSame topicCorporate Governance and LawFrench-language works237,207