5 resultados para social benefit

em Digital Commons at Florida International University


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Programs require strong support and guidance from those in leadership positions to ensure proper implementation (Fullen, 2001). Consequently, school site principals must rely on the training they have received to support them in making appropriate decisions. It is the school site principal’s leadership that is pivotal in the success of students with disabilities (DiPaola & Walther-Thomas, 2003; Monteith, 2000). In fact, the principal has a moral obligation to provide an environment that supports social justice in schools (Grogan & Andrews, 2002). The inclusion of students with disabilities does just that—it ensures that these students are not segregated to a “separate but equal” education. This study utilized a participant survey to collect data on principals’ beliefs and training in special education. This information was compared to the percentage of time students with disabilities spent with their non-disabled peers in the principals’ respective schools. An analysis was conducted to identify if a linear relationship exists between the selected variables and the inclusion percentages. Open-ended questions were included in the original survey which allowed for a thematic analysis of the responses. These responses were utilized to allow participants to further express their thoughts on the identified variables. Results indicated that there were no statistically significant relationships identified between the beliefs and training of secondary school site principals and the percentage of time that their students in special education spend with their non-disabled peers. Although the original research questions were not supported, further post hoc analysis indicated that the results obtained did support that the principals believed inclusion had a social benefit to students. Additional investigation into the academic benefits of inclusion is still needed. In addition, principals who indicated that they had some type of training in special education indicated a higher percentage that the individual student should be the focal point when making placement decisions. These results support the need for further research in the area of principal preparation programs and their relationships to the daily practice of school site principals.

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Just as all types of business firms are now expected to go beyond their profit-oriented activities in boosting the well-being of the community, so, too, is corporate social responsibility (CSR) expected from foodservice firms. The significance of the obesity epidemic, combined with the foodservice industry's role in the development of this epidemic, suggests that the industry has an ethical responsibility to implement CSR activities that will help reduce obesity, particularly among children. CSR should be seen as an efficient management strategy through which a firm voluntarily integrates social and environmental concerns into its business operations and its interactions with stakeholders. Although costs are associated with CSR initiatives, benefits accrue to the firm. Decisions regarding alternative CSR activities should be based on a cost-benefit analysis and calculation of the present value of the revenue stream that can be identified as resulting from the specific CSR activities. CSR initiatives should be viewed as long-term investments that will enhance the firms’ value. Key areas for foodservice firms' CSR activities include marketing practices, particularly practices impacting advertising to children and marketing that will enhance the firms’ visibility; portion-size modification; new-product development; and consistent nutrition labeling on menus.

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Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

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Globally, small-scale fisheries (SSFs) are driven by climate, governance, and market factors of social-ecological change, presenting both challenges and opportunities. The ability of small-scale fishermen and buyers to adapt to changing conditions allows participants to survive economic or environmental disturbances and to benefit from optimal conditions. This study presented here identifies key large-scale factors that drive SSFs in California to shift focus among targets and that dictate long-term trends in landings. We use Elinor Ostrom’s Social-Ecological System (SES) framework to apply an interdisciplinary approach when identifying potential factors and when understanding the complex dynamics of these fisheries. We analyzed the interactions among Monterey Bay SSFs over the past four decades since the passage of the Magnuson Stevens Fisheries Conservation and Management Act of 1976. In this region, the Pacific sardine (Sardinops sagax), northern anchovy (Engraulis mordax), and market squid (Loligo opalescens) fisheries comprise a tightly linked system where shifting focus among fisheries is a key element to adaptive capacity and reduced social and ecological vulnerability. Using a cluster analysis of landings, we identified four modes from 1974 to 2012 that were dominated by squid, sardine, anchovy, or lacked any dominance, enabling us to identify external drivers attributed to a change in fishery dominance during seven distinct transition points. Overall, we show that market and climate factors drive the transitions among dominance modes. Governance phases most dictated long-term trends in landings and are best viewed as a response to changes in perceived biomass and thus a proxy for biomass. Our findings suggest that globally, small-scale fishery managers should consider enabling shifts in effort among fisheries and retaining existing flexibility, as adaptive capacity is a critical determinant for social and ecological resilience.

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Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.