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Research On The Improvement Of Court Trial Capacity By Big Data

Posted on:2021-08-27Degree:MasterType:Thesis
Country:ChinaCandidate:S J XuFull Text:PDF
GTID:2516306230495874Subject:legal
Abstract/Summary:PDF Full Text Request
The era of big data has arrived and it has shown strong vitality and influence in various fields.The people’s courts aim at improving the quality of trials,the efficiency of trials,strengthening the administration of trials,promoting the solution of difficult problems in execution and safeguarding judicial justice.courts make full use of advanced information technologies such as big data,cloud computing and artificial intelligence to fully explore the value of judicial big data,and implement the reform of the judicial system.However,just as the Internet technology in the past,while the big date promote the judicial modernization,it also brings a series of problems,such as incomplete information security legislation,incomplete data,declining the autonomy of judges,increasing the cost of court input,algorithm black hole and so forth.Based on the background of the rapid development of big data,and focuses on how big data can improve the judicial capacity of the court and judicial modernization.on the basis of collecting and reading a large number of documents,this paper analyzes the current situation of people’s courts in Guizhou province using big data to improve their judicial capacity,summarize its achievements and advantages,and try to find the problems use of big data to improve the judicial capacity of the court,and give some measures to improve and cope with it.This paper summarizes the research status of big data on the improvement of judicial capacity of courts at home and abroad,by means of literature research,systematic analysis and other research methods.firstly,this paper expounds the application of big data in improving the judicial capacity of the court,then analyzes the integration process of big data and judicial capacity,and finally defines the concepts of big data and judicial capacity,and analyzes that the improvement of bigdata and judicial capacity of the court has inherent unified attributes.In general,big data has been widely used in the court,and has great value for the improvement of the court’s judgment ability.this paper analyzes the possible role of big data in court trial execution and litigant litigation.show that big data can improve the quality and efficiency of trial,scientific management and supervision of trial,solve the problem of execution and construct the convenient judicature.However,as far as the current situation of the court using big data,there are still many difficulties and challenges that restrict the further improvement of the judicial ability of the court.mainlyinclude the problems to lack of data information security legislation and algorithm black box and data segmentation and judicial data are incomplete and the data information needs to be improved and Insufficient data analysis and application and insufficient information literacy of judicial personnel,insufficient understanding of instrumental rationality,and decreased judicial autonomy.Therefore,based on the attempt to summarize and define the definitions of big data and judicial capacity of the court,research the problems and obstacles faced by the court in improving its judicial capacity under the background of big data,and proposes solutions and improvement measures.the first is to strengthen data information security protection and algorithm regulation,promote data disclosure;secondly,the development of big data technology and the improvement of court data infrastructure;the third is to update the concept of big data and understand the essence of justice.Through continuous reform and development,Chinese courts will surely make the big data play an active role of in improving the judicial capacity of courts and promoting the judicial modernization process.
Keywords/Search Tags:Court big data, Judicial capacity, Judgment quality effect, Judicial impartiality, Challenges and countermeasures
PDF Full Text Request
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