Purpose: The purpose of this study is to understand nursing students' experiences during clinical practice at a public health center. Method: This research used narrative inquiry far data collection. From April 2005 to June 2006, data collection was conducted by open-ended interview, questionnaire and close observation. The participants, who were student nurses, were willing to take part in this study. Results: On the basis of these data, the experiences of clinical practice at public health center were: 1) when the student nurses begin clinical practice at public health centers for the first time, most of the students feel fearful, nervous and stressed. They also mentioned having a hard time being polite to clients and the staff. 2) The students had new experiences at the health public center compared with clinical practice. Especially, the student nurses who were determined to be good nurses were doing home visiting care service. Not only did they have the opportunity to confirm their identity as nurses, but also the students change their career course from clinical nursing to public health nursing. 4) They reflected on themselves after home visiting care service. Conclusion: On the basis of these findings, the following recommendations are made. 1) Data collection and analysis are needed, net only through the narrative method, but also through other various qualitative methods. 2) Comparative study is necessary to enhance clinical experiences through the analysis of the interfering factors and the original experiences.
Recently, government agencies are actively adopting the platform model as a means of public policy. However, existing studies on the public platform are minimal and have focused on user experiences or the possibility of public usage of the platform model. Now the research concerning building governance structure and utilizing network effects of the platform after adopting the platform model in the public sector is keenly required. This study intended to ignite academic dialogue on the governance of public platforms in the context of digital transformation. This study focused on a case of the 'Special delivery,' a public delivery app established by Gyeonggi-do. In order to analyze the characteristics of the public platform and its governance structure, data were collected from press releases, policy reports, and news articles. Data was analyzed using the frame of Hagui's platform design factors and Ansell & Gash's collaborative governance model. The results of the public platform analyses showed 1) incompleteness in the value trade-off accounting, which was designed for platform business based on general cost-benefit analysis, and 2) a closed governance structure that limits direct participation of diverse user groups(i.e., service provider, customer) in order to enhance providers' utility by preventing customers' excessive online activities. The results of this study provided theoretical and policy implications regarding designing the strategy for accounting for value trade-offs and functioning governance structure for public platforms.
What is the relationship between city diplomacy and public diplomacy in the United States? Whilst this question is often raised among scholars and practitioners of public diplomacy, a concrete and systematic response to it seems difficult to locate. This paper addresses the question by relying on earlier research based on empirical analysis of data from semi-structured interviews with city officials with international purview in the United States as well as with current and former officials at the U.S. Department of State who have worked on topics related to city diplomacy. The research and analysis that informs this paper and the diagrams it offers are hinged on design principles and adopt an architecture studio style approach to data analysis. Further, multidimensional scaling and correspondence analysis are used to visualize the convergence and divergence between the functions of public diplomacy, as introduced by Nicholas Cull, and the functions of city diplomacy that this paper introduces. This is done to first, provide a framework for understanding the dynamics between city diplomacy and public diplomacy; and second, uncover the policy intervention space that could guide policies for making U.S. city diplomacy and public diplomacy more strategically aligned.
International Journal of Advanced Culture Technology
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v.11
no.4
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pp.358-377
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2023
During the initial period of the COVID-19 pandemic, governments around the world implemented non-pharmaceutical interventions. For these policy interventions to be effective, authorities engaged in the political discourse of legitimising their activity to generate positive public attitudes. To understand effective COVID-19 policy, this study investigates public attitudes in South Korea, the United Kingdom, and the United States and how they reflect different legitimisation of policy intervention. We adopt a big data approach to analyse public attitudes, drawing from public comments posted on Twitter during selected periods. We collect the number of tweets related to COVID-19 policy intervention and conduct a sentiment analysis using a deep learning method. Public attitudes and sentiments in the three countries show different patterns according to how policy interventions were implemented. Overall concern about policy intervention is higher in South Korea than in the other two countries. However, public sentiments in all three countries tend to improve following implementation of policy intervention. The findings suggest that governments can achieve policy effectiveness when consistent and transparent communication take place during the initial period of the pandemic. This study contributes to the existing literature by applying big data analysis to explain which policies engender positive public attitudes.
Journal of the Korean Operations Research and Management Science Society
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v.40
no.1
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pp.75-89
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2015
In recent years, attention to the high debt ratio in public institutions has pushed the government to make efforts in reducing the debt ratio. However, in order to stimulate the economy, the government needs drastically innovative measures that reduce debt by improving efficiency rather than moderate approaches that focus solely on debt reduction. Despite this need, no study has yet systematically analyzed the overall efficiency of domestic public institutions and identified the source of inefficiencies in each public entity. Therefore, largely two research questions are examined. First, this study compares the efficiency levels by types of public institutions. Second, this study identifies the cause of inefficiencies in each public institution and proposes directions for improving efficiency. Based on a 5-year data of 302 public institutions published in public business information systems and organizational websites from 2009 to 2013, Data Envelopment Analysis (DEA) was performed. The input variables include the number of employees and total costs while the output variables include sales and net income. Reflecting the characteristics of public institutions, the input-oriented CCR model and input-oriented BCC model were utilized. Analysis results are as follows. First, market-oriented public institutions showed the highest efficiency while fund management quasi-governmental agencies showed the highest inefficiency. Second, scale efficiency score was measured by applying the CCR model and the BCC model on the organizations with the lowest efficiency level, fund management quasi-governmental agencies. Based on these analysis results, the source of inefficiency and detailed directions for improvement were proposed for Decision Making Units (DMUs) with low CCR and BCC scores.
The Journal of Asian Finance, Economics and Business
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v.7
no.8
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pp.323-332
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2020
This study aims to examine the level of students' satisfaction toward the services (i.e. accommodation facilities, transportation facilities, and recreation and sports facilities) provided by the public universities in Bangladesh. The study also aims to identify the major service factors that influence students' satisfaction in public universities in the country. A cross-sectional survey was conducted at six public universities to obtain primary data. A standardized questionnaire was distributed to a total of 500 randomly selected students to collect the data. Several statistical tools, namely, reliability analysis, descriptive statistics, correlation analysis and multiple regression analysis were employed to analyze the data. The findings revealed that recreation and sports facilities have the strongest impact on students' satisfaction in the public universities in Bangladesh. Transportation facilities also have positive and significant impact on student's satisfaction. However, the study found a negative correlation between accommodation facilities and students' satisfaction indicating that students are not satisfied with the accommodation facilities provided by the public universities. The findings of this study provide an insight about students' satisfaction that might be useful to authorities of the public universities and other higher educational institutions in designing policies for various services and facilities to be provided to their students.
Journal of Korean Society of Archives and Records Management
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v.21
no.4
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pp.1-18
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2021
Today, record management has become more important in management as records generated from administrative work and data production have increased significantly, and the development of information and communication technology, the working environment, and the size and various functions of the government have expanded. It is explained as an example in connection with the concept of public records with the characteristics of big data and big data characteristics. Social, Technological, Economical, Environmental and Political (STEEP) analysis was conducted to examine such areas according to the big data generation environment. The appropriateness and necessity of applying big data technology in the field of public record management were identified, and the top priority applicable framework for public record management work was schematized, and business implications were presented. First, a new organization, additional research, and attempts are needed to apply big data analysis technology to public record management procedures and standards and to record management experts. Second, it is necessary to train record management specialists with "big data analysis qualifications" related to integrated thinking so that unstructured and hidden patterns can be found in a large amount of data. Third, after self-learning by combining big data technology and artificial intelligence in the field of public records, the context should be analyzed, and the social phenomena and environment of public institutions should be analyzed and predicted.
Objectives: The aim of this study was to evaluate the effect of body weight status and sleep duration on the discrete-time hazard of menarche in Korean schoolgirls using multiple-point prospective panel data. Methods: The study included 914 girls in the 2010 Korean Children and Youth Panel Study who were in the elementary first-grader panel from 2010 until 2016. We used a Gompertz regression model to estimate the effects of weight status based on age-specific and sex-specific body mass index (BMI) percentile and sleep duration on an early schoolchild's conditional probability of menarche during a given time interval using general health condition and annual household income as covariates. Results: Gompertz regression of time to menarche data collected from the Korean Children and Youth Panel Study 2010 suggested that being overweight or sleeping less than the recommended duration was related to an increased hazard of menarche compared to being average weight and sleeping 9 hours to 11 hours, by 1.63 times and 1.38 times, respectively, while other covariates were fixed. In contrast, being underweight was associated with a 66% lower discrete-time hazard of menarche. Conclusions: Weight status based on BMI percentiles and sleep duration in the early school years affect the hazard of menarche.
International Journal of Knowledge Content Development & Technology
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v.12
no.4
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pp.41-65
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2022
This study would understand the overall perception of our society about public libraries, analyzing the texts related to public libraries, utilizing the semantic connection network & sentiment analysis. For this purpose, this study collected data from the last five years with keywords, 'Library' and 'Lifelong Learning Center' from January 1, 2016 through November 30, 2020 through the blogs and cafés of major domestic portal sites. With the collected data, text mining, centrality of keywords, network structure, structural equipotentiality, and sensitivity analyses were conducted. As a result of the analysis, First, 'reading' and 'book' were identified as representative keywords that form the social perception of public libraries. Second, it turned out that there were keywords related to the use of the library and the untact service due to the recent spread of COVID-19. Third, in seeking a plan for the development of public libraries through the keywords drawn to have positive meanings, it is necessary to create continuous services that can form a new image of the library, breaking away from the existing fixed role and image of the library and increase the convenience of use. Fourth, facilities and facilities for library services were recognized from a neutral point of view. Fifth, the spread of infectious diseases, social distancing, and temporary closure and closure of libraries are negatively related to public libraries, and awareness of librarians has been identified as negative keywords.
International Journal of Advanced Culture Technology
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v.8
no.3
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pp.133-139
/
2020
The purpose of this study is to contribute to the provision of basic data for psychological quarantine policy and counseling by examining the public perception of the "corona blue" phenomenon through analysis of social media big data. To do this, key words related to the word 'Corona Blue' were derived and analyzed using the big data analysis program 'Textom'. As a result of the analysis, words such as 'Corona 19', 'depression', 'problem' and 'overcome' were derived as key words. For the analysis results,"pride and awarenes as the public perception of Corona 19", "depression and anxiety as a group trauma as the corona blue phenomenon", "spreading a psychological quarantine culture and demanding social healing as the perception of overcoming corona Blue," and "hope for return to daily life and changes in daily life as the perception of post corona" were discussed. In conclusion, we have identified the need for active psychological support from the community By revealing that Corona Blue is a depression as a group trauma. At this time, it is confirmed that it is necessary to prioritize social healing and psychological quarantine for the main risk groups such as youth or the vulnerable, who are the socially weak.
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