749 resultados para Charity trust


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As an important component in collaborative natural resource management and nonprofit governance, social capital is expected to be related to variations in the performance of land trusts. Land trusts are charitable organizations that work to conserve private land locally, regionally, or nationally. The purpose of this paper is to identify the level of structural and cognitive social capital among local land trusts, and how these two types of social capital relate to the perceived success of land trusts. The analysis integrates data for land trusts operating in the U.S. south-central Appalachian region, which includes western North Carolina, southwest Virginia, and east Tennessee. We use factor analysis to elicit different dimensions of cognitive social capital, including cooperation among board members, shared values, common norms, and communication effectiveness. Measures of structural social capital include the size and diversity of organizational networks of both land trusts and their board members. Finally, a hierarchical linear regression model is employed to estimate how cognitive and structural social capital measures, along with other organizational and individual-level attributes, relate to perceptions of land trust success, defined here as achievement of the land trusts’ mission, conservation, and financial goals. Results show that the diversity of organizational partnerships, cooperation, and shared values among land trust board members are associated with higher levels of perceived success. Organizational capacity, land trust accreditation, volunteerism, and financial support are also important factors influencing perceptions of success among local, nonprofit land trusts.

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Audit report on the Office of Treasurer of State, Iowa ABLE (Achieving a Better Life Experience) Saving Plan Trust for the year ended June 30, 2016

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The challenging effects of globalization upon the nation-state have been a recurrent theme in the social science discourse since the 1990’s. Nationally organized education is also seen as challenged by new demands originating from globalization. In this article it is argued that ‘nation-state’ and ‘national identity’ are highly relevant concepts when discussing a citizenship education that seeks to develop a civic ethos with, potentially, a global reach. It is further argued that the understanding of such an ethos would benefit significantly from incorporating the role of political trust since trust has been identified as a main feature of the social capital that makes democracy work. Three themes are brought together: national identity and identification, the importance for democracy of political trust and the challenges citizenship education face when carried out in a national context but intended to manage issues that go far beyond the reach of the nation-state. The importance of citizenship education is discussed using recent research on the Swedish citizenship education classroom.

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Audit report on the Office of Treasurer of State, Iowa Educational Savings Plan Trust (Trust) for the year ended June 30, 2016

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We propose three research problems to explore the relations between trust and security in the setting of distributed computation. In the first problem, we study trust-based adversary detection in distributed consensus computation. The adversaries we consider behave arbitrarily disobeying the consensus protocol. We propose a trust-based consensus algorithm with local and global trust evaluations. The algorithm can be abstracted using a two-layer structure with the top layer running a trust-based consensus algorithm and the bottom layer as a subroutine executing a global trust update scheme. We utilize a set of pre-trusted nodes, headers, to propagate local trust opinions throughout the network. This two-layer framework is flexible in that it can be easily extensible to contain more complicated decision rules, and global trust schemes. The first problem assumes that normal nodes are homogeneous, i.e. it is guaranteed that a normal node always behaves as it is programmed. In the second and third problems however, we assume that nodes are heterogeneous, i.e, given a task, the probability that a node generates a correct answer varies from node to node. The adversaries considered in these two problems are workers from the open crowd who are either investing little efforts in the tasks assigned to them or intentionally give wrong answers to questions. In the second part of the thesis, we consider a typical crowdsourcing task that aggregates input from multiple workers as a problem in information fusion. To cope with the issue of noisy and sometimes malicious input from workers, trust is used to model workers' expertise. In a multi-domain knowledge learning task, however, using scalar-valued trust to model a worker's performance is not sufficient to reflect the worker's trustworthiness in each of the domains. To address this issue, we propose a probabilistic model to jointly infer multi-dimensional trust of workers, multi-domain properties of questions, and true labels of questions. Our model is very flexible and extensible to incorporate metadata associated with questions. To show that, we further propose two extended models, one of which handles input tasks with real-valued features and the other handles tasks with text features by incorporating topic models. Our models can effectively recover trust vectors of workers, which can be very useful in task assignment adaptive to workers' trust in the future. These results can be applied for fusion of information from multiple data sources like sensors, human input, machine learning results, or a hybrid of them. In the second subproblem, we address crowdsourcing with adversaries under logical constraints. We observe that questions are often not independent in real life applications. Instead, there are logical relations between them. Similarly, workers that provide answers are not independent of each other either. Answers given by workers with similar attributes tend to be correlated. Therefore, we propose a novel unified graphical model consisting of two layers. The top layer encodes domain knowledge which allows users to express logical relations using first-order logic rules and the bottom layer encodes a traditional crowdsourcing graphical model. Our model can be seen as a generalized probabilistic soft logic framework that encodes both logical relations and probabilistic dependencies. To solve the collective inference problem efficiently, we have devised a scalable joint inference algorithm based on the alternating direction method of multipliers. The third part of the thesis considers the problem of optimal assignment under budget constraints when workers are unreliable and sometimes malicious. In a real crowdsourcing market, each answer obtained from a worker incurs cost. The cost is associated with both the level of trustworthiness of workers and the difficulty of tasks. Typically, access to expert-level (more trustworthy) workers is more expensive than to average crowd and completion of a challenging task is more costly than a click-away question. In this problem, we address the problem of optimal assignment of heterogeneous tasks to workers of varying trust levels with budget constraints. Specifically, we design a trust-aware task allocation algorithm that takes as inputs the estimated trust of workers and pre-set budget, and outputs the optimal assignment of tasks to workers. We derive the bound of total error probability that relates to budget, trustworthiness of crowds, and costs of obtaining labels from crowds naturally. Higher budget, more trustworthy crowds, and less costly jobs result in a lower theoretical bound. Our allocation scheme does not depend on the specific design of the trust evaluation component. Therefore, it can be combined with generic trust evaluation algorithms.

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This thesis presents an in-depth case study of a superdiverse neighbourhood in Glasgow where long-term white and ethnic minority communities reside alongside Roma migrants, asylum seekers and refugees, young professionals and other recent arrivals in traditional tenement housing. It focuses on the nature and extent of social contact and trust and on the role of context in shaping social relations. Employing the concepts of social milieu and intersectionality to identify social differences the research examines the relationships between five broad groupings of residents in the neighbourhood: Nostalgic Working Class, Scottish Asian, Liberal Homeowners, Kinship-sited Roma and Global Migrants. Ethnographic fieldwork was carried out in contexts within the neighbourhood, theorised as being potential sites for intergroup contact. Three types of interactions were examined: Group-based Interactions, Neighbour Interactions and Street Interactions. The data comprised documentary evidence, participant and direct observations, in-depth qualitative and walk-along interviews with residents and local organisations. Findings show that rather than individualising and isolating residents, superdiversity can stimulate community activism, yet there remains a preference for interaction within one’s own social milieu. The research has found that the concentration of poverty and material conditions has a more profound effect on social relations than historical diversity and the extent to which diversity is normalised within local discourses. Trust judgements in a superdiverse context may rely more on shared interests, moral outlook and assessments of the context rather than the extent of social contact. The quasi-private spaces of shared residential spaces and community activities can facilitate encounters with the potential to build trust, yet for this to occur cooperation through shared activities may not be sufficient. Interactions may need to move beyond co-presence and conviviality to increased understanding and empathy through dialogue. At an aggregate level, the extent to which superdiversity contributes to social contact and trust within the neighbourhood is strongly influenced by contextual factors and wider economic processes influencing housing tenure mix, private renting, property maintenance, residential churn and environmental conditions. Through examining different types of social contacts, the dynamics of trust as well as contextual influences, this thesis offers insights into the causal processes and factors that influence social relations at a local level.

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An organization trusted by consumers enjoys a number of benefits. Unfortunately, instances of trust-damaging events involving organizations happen often. Damaged consumer trust in an organization has numerous negative consequences for the organization and for consumers. Currently, there is a paucity of theory about consumer trust recovery. So, understanding why and how consumer trust recovery occurs is timely, and theoretically and practically relevant. However, the findings from this study suggest that we need to distinguish between two kinds of consumer trust recovery. The first (I call it unconscious consumer trust recovery) refers to trust recovery that occurs without the consumer being fully conscious of it. In other words, a consumer is aware of their damaged trust during the scandal, but is not aware that their trust in the organization has improved. The consumer does not think about his or her recovered trust, just as they did not think about their level of trust before the scandal. The consumer trust is habitual. The second (I call it conscious consumer trust recovery) refers to an improvement in damaged trust where the consumer is fully conscious of their trust recovery. In other words, in conscious trust recovery the consumer is aware that the scandal damaged their trust in the organization. Also, after the scandal, in contrast to unconscious trust recovery, in conscious trust recovery the consumer is also fully aware that he trusts the organization as much or more than during the scandal. My aim is to inductively develop a theory explaining each type of consumer trust recovery. To do so, I use Charmazian grounded theory methodology, because this methodology is developed for theory-building from data and is aligned with the philosophical underpinnings of this study. The empirical context for this study is the meat adulteration scandal (“the horse meat scandal”) in 2013 in the UK. I collect and analyse empirical data about both types of trust recovery in an organization from 31 consumers that experienced both types. My analysis shows that when consumers perceive the scandal as less important, they experience unconscious trust recovery. This happens because the reduced importance of the scandal leads to a shift in consumers’ attention, which in turn leads to their inattentiveness to the scandal. Consumer inattentiveness is an immediate antecedent of unconscious trust recovery. Conscious consumer trust recovery occurs because consumers see cues indicating to them that the food retailer has improved product control systems, which in turn leads to consumer perceptions of the organization’s renewed ability. Consumer perception of renewed ability is an immediate antecedent of their conscious trust recovery. My findings lead me to make three main theoretical contributions to the theory of trust recovery in general and to consumer trust recovery in particular. The first contribution lies in showing that there are two types of consumer trust recovery in an organization, not one, as previously conceptualised, and that the same consumers can experience both types. The second contribution is a theory of unconscious consumer trust recovery in an organization that involves three concepts: consumers’ perceived importance of the scandal, consumers’ shift of attention, and consumer inattentiveness. The third contribution is the finding that conscious recovery of consumer trust occurs even when existing theory of trust recovery would predict that it would not. This study can help managers aiming to repair consumer trust in an organization by identifying a set of antecedents and underlying mechanisms that can guide such trust repair.

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In this article, we advocate for the use of a social-technical model of trust to support interaction designers in further reflecting on trust-enabling interaction design values that foster participation. Our rationale is built upon the believe that technological-mediated social participation needs trust, and it is with trust-enabling interactions that we foster the will for collaborate and share—the two key elements of participation. This article starts by briefly presenting a social-technical model of trust and then moves on with establishing authors rational that interconnects trust with technological-mediated social participation. It continues by linking the trust value to the context of design critique and critical design, and ends by illustrating how to incorporate the trust value into design. This is achieved by proposing an analytical tool that can serve to inform interaction designers to better understand the potential design options and reasons for choosing them.

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"Prepared by G. Joachim [i.e. Joachim G.] Elterich and Linda Graham"--Prelim. p.

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Social network sites (SNS), such as Facebook, Google+ and Twitter, have attracted hundreds of millions of users daily since their appearance. Within SNS, users connect to each other, express their identity, disseminate information and form cooperation by interacting with their connected peers. The increasing popularity and ubiquity of SNS usage and the invaluable user behaviors and connections give birth to many applications and business models. We look into several important problems within the social network ecosystem. The first one is the SNS advertisement allocation problem. The other two are related to trust mechanisms design in social network setting, including local trust inference and global trust evaluation. In SNS advertising, we study the problem of advertisement allocation from the ad platform's angle, and discuss its differences with the advertising model in the search engine setting. By leveraging the connection between social networks and hyperbolic geometry, we propose to solve the problem via approximation using hyperbolic embedding and convex optimization. A hyperbolic embedding method, \hcm, is designed for the SNS ad allocation problem, and several components are introduced to realize the optimization formulation. We show the advantages of our new approach in solving the problem compared to the baseline integer programming (IP) formulation. In studying the problem of trust mechanisms in social networks, we consider the existence of distrust (i.e. negative trust) relationships, and differentiate between the concept of local trust and global trust in social network setting. In the problem of local trust inference, we propose a 2-D trust model. Based on the model, we develop a semiring-based trust inference framework. In global trust evaluation, we consider a general setting with conflicting opinions, and propose a consensus-based approach to solve the complex problem in signed trust networks.

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Aim: Lighthouse Trust in Lilongwe, Malawi serves approximately 25,000 patients with HIV antiretroviral therapy (ART) regimens standardized according to national treatment guidelines. However, as a referral centre for complex cases, Lighthouse Trust occasionally treats patients with non-standard ART regimens (NS-ART) that deviate from the treatment guidelines. We evaluated factors contributing to the use of NS-ART and whether patients could transition to standard regimens. Methods: This was a cross-sectional study of all adult patients at Lighthouse Trust being treated with NS-ART as of February 2012. Patients were identified using the electronic data system. Medical charts were reviewed and descriptive statistics were obtained. Results: One hundred six patients were initially found being treated with NS-ART, and 92 adult patients were confirmed to be on NS-ART after review. Mean patient age was 42.4 ± 10.3 years, and 52 (57%) were female. Mean duration of treatment with the NS-ART being used at the time of data collection was 2.1 ± 1.5 years. Eight patients (9%) were on modified first-line NS-ART and 84 (91%) were on modified second-line NS-ART, with 90 patients (98%) having multiple factors contributing to NS-ART use. Severe toxicity from one medication contributed in 28 cases (30%) and toxicity from multiple medications contributed in 46 cases (50%), while 22 patients (24%) were transitioned to NS-ART following a stockout of their original medication. Following clinical review, 84 patients (91%) were transitioned to standard regimens, and eight (9%) were maintained on NS-ART because of incompatibility of their clinical features with the latest national guidelines. Conclusions: Primary factors contributing to NS-ART use were medication toxicities and medication stockouts. Most patients were transitioned to standard regimens, although the need for NS-ART remains.

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Part 10: Sustainability and Trust