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A Comparative Study on the Management of Digital Assets in Virtue of Fiduciary Relationship

2019· article· en· W4403442751 on OpenAlexaboutno aff
Md. Riaduzzaman, Arif Mahmud, Musfek Nazneen

Bibliographic record

VenueDIU journal of humanities & social science. · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsnot available
Fundersnot available
KeywordsFiduciaryVirtueBusinessAccountingLaw and economicsEconomicsPolitical scienceLawDuty

Abstract

fetched live from OpenAlex

In this era of digital communication, people keep living online even after death. Digital information stored in a personal computer; information stored in cloud backups, online digital accounts and records of digital communications is recognized as digital assets in various countries. As the extent of digital assets is ever-evolving, a perfect balance between the concerning rights and privacy issues should be constructed without any gap. The paper ventures to examine the legal extent of digital assets with illustration and exceptions by comparing American and Canadian legislations. Some recent cases have been analyzed to find out the taxonomy of obstacles faced by the family members while getting access to deceased digital assets even after a court order in fast. The paper examined the existing user end policy of popular digital service providing companies with the intent to find out issues connected proteins with digital assets rights which are not recognized by the existing policies. Society can deny the significant values of digital assets and that's why fiduciaries should get access to virtual assets or accounts holding such assets of a deceased or person with disabilities. The paper has compared thefirnctionaliry of different American state legislations and the American federal and Canadian uniform legislation for the management of digital assets and record of digital communication in virtue of fiduciary relationship. Many states lack similar legislation and Bangladesh is also not an exception. Policymakers needed to be aware of such novus legal developments for safeguarding the rights and interest of the citizens. The paper concluded by providing recommendations for the policymakers

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.066
GPT teacher head0.291
Teacher spread0.225 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2019
Admission routes1
Has abstractyes

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