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Record W2987637664 · doi:10.3389/fbloc.2019.00020

The Middleman Is Dead, Long Live the Middleman: The “Trust Factor” and the Psycho-Social Implications of Blockchain

2019· article· en· W2987637664 on OpenAlexaff
Andrea Gaggioli, Shayan Eskandari, Pietro Cipresso, Edoardo Lozza

Bibliographic record

VenueFrontiers in Blockchain · 2019
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsConcordia University
Fundersnot available
KeywordsBlockchainDecentralizationInternet privacyTrustworthinessComputational trustThe InternetComputer scienceWeb of trustBusinessComputer securityKnowledge managementWorld Wide WebPolitical scienceLawReputation

Abstract

fetched live from OpenAlex

Blockchain is widely regarded as a breakthrough innovation that may have a profound impact on the economy and society, of a magnitude comparable to the effects of the introduction of the Internet itself. In essence, a blockchain is a decentralized peer-to-peer network with no central authority figure, which adds information to the distributed database by collectively validating the accuracy of data. Since each node of the network participates in the review and confirmation of the new information before being accepted, the need for a trustworthy intermediary is eliminated. However, as trust plays an essential role in affecting decisions when transacting with one another, it is important to understand which implications the decentralized nature of blockchain may have on individuals' sense of trust. In this contribution, we argue that the adoption of blockchain is not only a technological, but foremostly a psychological challenge, which crucially depends on the possibility of creating a trust management approach that matches the underlying distributed communication system. We first describe the decentralization technologies and possibilities they hold for the near future. Next, we discuss the psycho-social implications of the introduction of decentralized processes of trust, examining some potential scenarios, and outline a research agenda.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.301
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
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 head0.009
GPT teacher head0.230
Teacher spread0.220 · 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 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

Citations21
Published2019
Admission routes1
Has abstractyes

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