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Record W2270286034

Regulating Issuer Bids: The Case of the Dutch Auction

2000· article· en· W2270286034 on OpenAlexaffabout
Anita Anand

Bibliographic record

VenueTSpace (University of Toronto) · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and International Contract Law
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIssuerShareholderBusinessProcurementCommon value auctionLegislatureEconomicsMicroeconomicsFinanceLawMarketingPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Under current securities legislation in Ontario, conventional issuer bids are subject to both "identical consideration" and "pro rata take-up" requirements. A variation of the conventional issuer bid, known as a "Dutch auction" issuer bid, has started to gain prominence in Canada as a mechanism of share acquisition used by issuers to repurchase a portion of their outstanding shares. While Dutch auction issuer bids are distinct in that they allow shareholders to choose a minimum bid price from a range of prices set by the issuer, they are currently subject to the same legislative requirements as conventional issuer bids.
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\nIn this article, the author examines the origin of and policy behind the identical consideration and pro rata takeup requirements. The author argues that the current regulation of Dutch auctions contains a bias in favour of tendering shareholders and that the identical consideration and pro rata take-up requirements should not apply to these kinds of issuer bids. Omitting these requirements for Dutch auction issuer bids would allow equality of opportunity to be achieved. According to the author, this latter notion of equality constitutes the fairest result for both tendering and non-tendering shareholders in a Dutch auction issuer bid.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.983

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.000

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 head0.017
GPT teacher head0.268
Teacher spread0.251 · 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 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

Citations2
Published2000
Admission routes2
Has abstractyes

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