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Record W7162108100 · doi:10.82308/15489

Tort law liability of directors and officers towards third party creditors : a comparative study of common and civil law with special focus on Canada and Germany

2003· dissertation· en· W7162108100 on OpenAlexaboutno aff
Jenny Melanie Schlag

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Insolvency and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsTortCorporationHarmDelictJurisdictionCommon lawCivil law (Civil law)Corporate lawLegal liabilityCreditor

Abstract

fetched live from OpenAlex

Where individuals standing outside of the corporation have been harmed by the acts of one of its directors or officers, the question becomes whether they have only a claim against the corporation or whether they may have also a personal claim against the executive inflicting the harm on them. The issue of how far it should be possible to hold directors and officers personally liable for tort has been a contested one and even courts within one and the same jurisdiction provide different solutions. On the one hand, there is the general basic principle that individuals causing harm to others should be held responsible. On the other hand, the fact that directors and officers act as agents on behalf of the corporation might call for an exception to this basic tort law principle. This thesis will compare the solutions proposed by Common law (with focus on the law of Ontario) and German law as an example of a Civil law jurisdiction. An attempt will be made to see in how far the proposed solutions are consistent with legal principles like the separate legal entity of the corporation and the concept of limited liability as well as with arguments related to economic efficiency.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.778

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.011
Science and technology studies0.0090.011
Scholarly communication0.0070.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.227
Teacher spread0.212 · 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 designTheoretical or conceptual
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
Published2003
Admission routes1
Has abstractyes

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