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Record W7135590231

"Svěřenský fond" - institute of intergenerational wealth preservation and succession

2018· dissertation· cs· W7135590231 on OpenAlexaboutno aff
Michal Skuhrovec

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2018
Typedissertation
Languagecs
FieldArts and Humanities
TopicMedical Research and Islamic Perspectives
Canadian institutionsnot available
Fundersnot available
KeywordsInheritance (genetic algorithm)AncestorInstitutionFiduciaryAppropriationEstateCzechOrder (exchange)
DOInot available

Abstract

fetched live from OpenAlex

"Svěřenský fond" - institute of intergenerational wealth preservation and succession Abstract Thesis named "Svěřenský fond - institute of intergenerational wealth preservation and succession" is dedicated to describe institution of "svěřenský fond" from the perspective of a potential alternative or addition to a more traditional institutions of inheritance law. The aim of the thesis is to describe primarily its use to a purpose of family wealth preservation and succession. In order to fulfill this goal, the first part of the thesis analyses how fiducie/trust of Quebec made its way into Czech legislation. Main matter being the consequences adoption of a patrimony by appropriation caused. Second part follows historical roots of fiduciary institutes. It finds a persistent need for very similar fiduciary, trust-like institutes throughout history. The goal stays the same, a desire of families to preserve their wealth. Historical analysis, using an evolutionist paradigm, finds similarities between trust, modern fiduciary institutes and "svěřenský fond" which simply cannot be unseen. Based on this findings a hypothesis of a common ancestor is construed. Third part describes a newly acquired construction of trust-like institute, which was unseen in Czech law until 2014. It focuses on a result of transplantation of...

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)0.002
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 score0.029
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.281
Teacher spread0.265 · 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
Published2018
Admission routes1
Has abstractyes

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