Bibliographic record
Abstract
The Specifics of Use of Trusts in Business Relations This thesis deals with possibilities brought by trusts (in Czech: svěřenský fond) to business relations. It analyses the key features of a trust, thanks to which it has a unique and often irreplaceable position in number of financial transactions. Selected financial transaction are described in detail and the importance of trusts in these transactions is explained. The main objective of this thesis is to show that trusts have benefits far beyond the governance of personal property and its intergenerational transfers. By this I want to prompt interest in further research of the use of trusts in business relations in the Czech legal environment. After the introduction, the first chapter of this thesis briefly introduces the history of the trust. It is outlined which role the trust played in different legal systems and what were the motives for its development. The second part describes trust as an institute of civil law. There is also described the implementation of the trust into the legal system of the Canadian province Québec, because this regulation served as a model for the Czech lawmakers. This chapter of the thesis also describes the subjects of the trust and the basic concepts related to this institute. The third part introduces the trust...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.032 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".