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Record W187071721

Putting appraisal rights into perspective

2014· article· en· W187071721 on OpenAlexaboutno aff
Jacqueline Yeats

Bibliographic record

VenueStellenbosch Law Review = Stellenbosch Regstydskrif · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Governance and Law
Canadian institutionsnot available
Fundersnot available
KeywordsEnforcementHuman rightsLaw and economicsArgument (complex analysis)International human rights lawPolitical scienceShareholderLawReservation of rightsBusinessEconomicsRight to propertyCorporate governanceFinanceMedicine
DOInot available

Abstract

fetched live from OpenAlex

Appraisal rights were included in the Companies Act 71 of 2008 in accordance with the Department of Trade and Industry's stated objectives of enhanced protection for minority shareholders and development of the Act in line with international company law trends. However, appraisal rights are traditionally underutilised in other jurisdictions where they have existed for many years, most notably the United States and Canada. The reason for this is that they can be complex, expensive and time-consuming to enforce. Furthermore, as a result of the often uncertain outcome of appraisal rights litigation, there is an argument to be made that the enforcement of these rights is open to abuse and that they may be used to stifle legitimate deal activity. Given the challenges and complexity of appraisal rights enforcement, South African courts (and legal practitioners) will have to look to foreign jurisdictions for guidance as to how to interpret and apply this novel, foreign concept. Fortunately it seems that the Act does allow for this. Recently there has been a spate of appraisal rights litigation amidst renewed levels of merger activity in the United States which poses some interesting questions around the proper use of appraisal rights and the attitude of the courts in this regard. Although South African courts have not yet heard any appraisal rights disputes it seems clear that, because this remedy is so complex and internationally relevant, we should keep abreast of legal developments in foreign jurisdictions which may ultimately impact on the understanding, interpretation and application of appraisal rights in the South African context.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.005

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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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; both teacher heads agree on what is shown here.

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 routes1
Has abstractyes

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