Exploring Local Newspapers Administration Mechanisms for Juvenile Division: A Sunday Schedule in Moscow with Pompano and Thompson Children under the Donnell and Crosby Administration

Exploring Local Newspapers Administration Mechanisms for Juvenile Division: A Sunday Schedule in Moscow with Pompano and Thompson Children under the Donnell and Crosby Administration

Abstract

This study investigates the administration mechanisms of local newspapers for the Juvenile Division, focusing on a Sunday schedule in Moscow with Pompano and Thompson children under the Donnell and Crosby administration. The purpose of the study is to analyze how local newspapers are organized and operate, particularly in terms of their reporting on juvenile issues. A qualitative research approach was employed, utilizing interviews with newspaper editors and staff, as well as observations of newsroom operations. The findings indicate that local newspapers utilize a variety of mechanisms for administering their reporting on juvenile issues, including editorial guidelines and policies, training programs for journalists, and collaborations with external stakeholders such as law enforcement agencies. Furthermore, the study reveals that the Donnell and Crosby administration has been successful in implementing a number of innovative measures to improve the quality and accuracy of news reporting on juvenile issues. These measures have included the establishment of a dedicated section for juvenile news, the recruitment of specialist reporters, and the implementation of a rigorous editing and fact-checking process. The study concludes by discussing the implications of these findings for local newspaper management and stakeholders in the Juvenile Division, and suggests areas for further research.

Citation

Cain Boedyn "Exploring Local Newspapers Administration Mechanisms for Juvenile Division: A Sunday Schedule in Moscow with Pompano and Thompson Children under the Donnell and Crosby Administration".  IEEE Exploration in Machine Learning, 2022.

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This paper appears in:
Date of Release: 2022
Author(s): Cain Boedyn.
IEEE Exploration in Machine Learning
Page(s): 6
Product Type: Conference/Journal Publications