This thesis, submitted for the Doctor of Philosophy in Geography and Environment, presents a case study of the development of the UK's market-based management system for oceanic fisheries. Implemented gradually in the years since 1984, the informal nature of the UK's fisheries management system, which has developed through a number of incremental changes and government-industry "gentlemen’s agreements" rather than clear legislative moves, means that few official policy documents (and perhaps consequently, little academic literature) on the subject currently exist. This thesis traces the material and political processes of market formation, looking at the origin of market-based policies in the theories of bioeconomics and wider economic history. It asks what the implicit assumptions of the economic discipline can – and can't – tell us about the impacts and outcomes of market creation, and using a Foucauldian inspired approach to economic performativity, discusses the role of ostensibly descriptive theories in shaping the world around them. Finally, it calls for a greater geographical engagement with marine issues, and proposes an action-research role for geographers in the politics of the sea.

This paper examines the informal economy’s greenhouse-gas (GHG) emissions and whether it poses a problem to the effectiveness of international frameworks designed to reduce GHG emissions. With the results of a literature review conducted on the relation between the informal economy and regulations and results on 160 nations’ theoretical informal-economy emissions over time, this paper finds that the informal economy does hinder the ability of governments to manage GHG emissions. This paper then discusses how this aspect of the world’s economy limits the efficacy of international frameworks to reduce GHG emissions. Suggestions are made on how to incorporate this sector into the proposed frameworks. The paper concludes with summarizing the main findings and proposals for further research.

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In recent years, Small and Medium Enterprise Credit Guarantee Fund(SMEG) has been actively promoting organization restructuring, boosted its business unceasingly, and impelled each innovation guarantee service actively, in order to display the best benefit. This paper combines C. J. Kuo.¡]2003¡^market-based risk neutral model with actuarial valuation principles, using above observable rate discrepancy¡]i.e. one for that guaranteed by SMEG, and the other for non-guaranteed portion¡^to evaluate the credit risk SMEG assumed from guaranteed schemes, then derives the optimal guaranty fees model. The major research finding shows fixed as follows conclusion: 1.The real prepayment in subrogation is close to the total guaranty fees estimated by proposed model. 2.Applying this model can help that the credit risk degree SMEG takes reacts to the guarantee premium, and that SMEG control risk balance revenue and expenditure. This indicates that the model can reflect market information, and thus is easily applicable and referable by SMEG to establish the structure of guaranty fees as well as to reach an integrated risk management.

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Organizations owning HPC infrastructures are facing difficulties in managing their resources. These difficulties come from the need to provide concurrent resource access to different application types while considering that users might have different performance objectives for their applications. Cloud computing brings more flexibility and better resource control, promising to improve the user's satisfaction in terms of perceived Quality of Service. Nevertheless, current cloud solutions provide limited support for users to express or use various resource management policies and they don't provide any support for application performance objectives.In this thesis, we present an approach that addresses this challenge in an unique way. Our approach provides a fully decentralized resource control by allocating resources through a proportional-share market, while applications run in autonomous virtual environments capable of scaling the application demand according to user performance objectives.The combination of currency distribution and dynamic resource pricing ensures fair resource utilization.We evaluated our approach in simulation and on the Grid'5000 testbed. Our results show that our approach can enable the co-habitation of different resource usage policies on the infrastructure, improving resource utilisation.

Mobile sensor networks have been shown to be a powerful tool for enabling a number of activities that require recording of environmental parameters at various spatial and temporal distributions. These mobile sensor networks could be implemented using a team of robots, usually called robotic sensor networks. This type of sensor network involves the coordinated control of multiple robots to achieve specific measurements separated by varied distances. In most formation measurement applications, initialization involves identifying a number of interesting sites to which mobility platforms, instrumented with a variety of sensors, are tasked. This process of determining which instrumented robot should be tasked to which location can be viewed as solving the task allocation problem. Unfortunately, a centralized approach does not fit in this type of application due to the fault tolerance requirements. Moreover, as the size of the network grows, limitations in bandwidth severely limits the possibility of conveying and using global information. As such, the utilization of decentralized techniques for forming new sensor topologies and configurations is a highly desired quality of robotic sensor networks. In this thesis, several distributed task allocation algorithms will be explained and compared in different scenarios. They are based on a market approach since our interest is not only to obtain a feasible solution, but also an efficient one. Also, an analysis of the efficiency of those algorithms using probabilistic techniques will be explained. Finally, the task allocation algorithms will be implemented on a real system consisted of a team of six robots and integrated in a complete robotic system that considers obstacle avoidance and path planning. The results will be validated in both simulations and real experiments.

Industrial companies are dealing with an increasing data overload problem in all aspects of their business: vast amounts of data are generated in and outside each company. Determining which data is relevant and how to get it to the right users is becoming increasingly difficult. There are a large number of datasets to be considered, and an even higher number of combinations of datasets that each user could be using. Current techniques to address this data overload problem necessitate detailed analysis. These techniques have limited scalability due to their manual effort and their complexity, which makes them unpractical for a large number of datasets. Search, the alternative used by many users, is limited by the user’s knowledge about the available data and does not consider the relevance or costs of providing these datasets. Recommender systems and so-called market approaches have previously been used to solve this type of resource allocation problem, as shown for example in allocation of equipment for production processes in manufacturing or for spare part supplier selection. They can therefore also be seen as a potential application for the problem of data overload. This thesis introduces the so-called RecorDa approach: an architecture using market approaches and recommender systems on their own or by combining them into one system. Its purpose is to identify which data is more relevant for a user’s decision and improve allocation of relevant data to users. Using a combination of case studies and experiments, this thesis develops and tests the approach. It further compares RecorDa to search and other mechanisms. The results indicate that RecorDa can provide significant benefit to users with easier and more flexible access to relevant datasets compared to other techniques, such as search in these databases. It is able to provide a fast increase in precision and recall of relevant datasets while still keeping high novelty and coverage of a large variety of datasets.

abstract: Teacher evaluation policies have recently shifted in the United States. For the first time in history, many states, districts, and administrators are now required to evaluate teachers by methods that are up to 50% based on their "value-added," as demonstrated at the classroom-level by growth on student achievement data over time. Other related instruments and methods, such as classroom observations and rubrics, have also become common practices in teacher evaluation systems. Such methods are consistent with the neoliberal discourse that has dominated the social and political sphere for the past three decades. Employing a discourse analytic approach that called upon a governmentality framework, the author used a complementary approach to understand how contemporary teacher evaluation polices, practices, and instruments work to discursively (re)define teachers and teacher quality in terms of their market value. For the first part of the analysis, the author collected and analyzed documents and field notes related to the teacher evaluation system at one urban middle school. The analysis included official policy documents, official White House speeches and press releases, evaluation system promotional materials, evaluator training materials, and the like. For the second part of the analysis, she interviewed teachers and their evaluators at the local middle school in order to understand how the participants had embodied the market-based discourse to define themselves as teachers and qualify their practice, quality, and worth accordingly. The findings of the study suggest that teacher evaluation policies, practices, and instruments make possible a variety of techniques, such as numericization, hierarchical surveillance, normalizing judgments, and audit, in order to first make teachers objects of knowledge and then act upon that knowledge to manage teachers' conduct. The author also found that teachers and their evaluators have taken up this discourse in order to think about and act upon themselves as responsibilized subjects. Ultimately, the author argues that while much of the attention related to teacher evaluations has focused on the instruments used to measure the construct of teacher quality, that teacher evaluation instruments work in a mutually constitutive ways to discursively shape the construct of teacher quality. / Dissertation/Thesis / Doctoral Dissertation Educational Leadership and Policy Studies 2014

For producers motivated by their new status as self-employed, landowning, capitalist coffee growers, specialty coffee presents an opportunity to proactively change the way they participate in the international market. Now responsible for determining their own path, many producers have jumped at the chance to enhance the value of their product and participate in the new “fair trade” market. But recent trends in the international coffee price have led many producers to wonder why their efforts to produce a certified Fair Trade and organic product are not generating the price advantage they had anticipated. My study incorporates data collected in eighteen months of fieldwork, including more than 45 interviews with coffee producers and fair trade roasters, 90 surveys of coffee growers, and ongoing participant observation to understand how fair trade certification, as both a market system and development program, meets the expectations of the coffee growers. By comparing three coffee cooperatives that have engaged the Fair Trade system to disparate ends, the results of this investigation are three case studies that demonstrate how global processes of certification, commodity trade, market interaction, and development aid effect social and cultural change within communities. This study frames several lessons learned in terms of 1. socioeconomic impacts of fair trade, 2. characteristics associated with positive development encounters, and 3. potential for commodity producers to capture value further along their global value chain. Commodity chain comparisons indicate the Fair Trade certified cooperative receives the highest per-pound price, though these findings are complicated by costs associate with certification and producers’ perceptions of an “unjust” system. Fair trade-supported projects are demonstrated as more “successful” in the eyes of recipients, though their attention to detail can just as easily result in “failure”. Finally, survey results reveal just how limited is the market knowledge of producers in each cooperative, though fair trade does, in fact, provide a rare opportunity for producers to learn about consumer demand for coffee quality. Though bittersweet, the fair trade experiences described here present a learning opportunity for a wide range of audiences, from the certified to the certifiers to the concerned public and conscientious consumer.