Enhancing Judicial Impartiality in Ecuador: A Fuzzy Cognitive Map Approach Using Neutrosophic Logic and Fuzzification

Fuzzy Cognitive Map (FCM) approach, with neutrosophic logic and fuzzification applied to assign weights to the relationships between key concepts. Through expert consensus, eight critical factors were identified: Judicial Independence, Transparency, Corruption, Judicial Training, Accountability, Access to Justice, Procedural Guarantees, and Supervision and Control. Centrality analysis revealed that Judicial Independence and Transparency are the most influential, while Judicial Training has the lowest impact. The use of neutrosophic logic and fuzzification allowed for a flexible and accurate representation of causal relationships, accounting for uncertainty within the system. The findings highlight the need for reforms focused on enhancing judicial independence and transparency, as well as addressing corruption and access to justice. Future research should incorporate dynamic simulations and machine learning to further improve predictive capabilities and deepen the understanding of policy impacts on judicial impartiality.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-01
DOI
https://doi.org/10.5281/zenodo.13769269
Primary Topic
Cognitive Science and Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhancing Judicial Impartiality in Ecuador: A Fuzzy Cognitive Map Approach Using Neutrosophic Logic and Fuzzification

Zenodo (CERN European Organization for Nuclear Research)
Cognitive Science and Mapping
article

Enhancing Judicial Impartiality in Ecuador: A Fuzzy Cognitive Map Approach Using Neutrosophic Logic and Fuzzification

article en

Abstract

Fuzzy Cognitive Map (FCM) approach, with neutrosophic logic and fuzzification applied to assign weights to the relationships between key concepts. Through expert consensus, eight critical factors were identified: Judicial Independence, Transparency, Corruption, Judicial Training, Accountability, Access to Justice, Procedural Guarantees, and Supervision and Control. Centrality analysis revealed that Judicial Independence and Transparency are the most influential, while Judicial Training has the lowest impact. The use of neutrosophic logic and fuzzification allowed for a flexible and accurate representation of causal relationships, accounting for uncertainty within the system. The findings highlight the need for reforms focused on enhancing judicial independence and transparency, as well as addressing corruption and access to justice. Future research should incorporate dynamic simulations and machine learning to further improve predictive capabilities and deepen the understanding of policy impacts on judicial impartiality.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 65%
Cognitive Science and Mapping
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