Submitted by Edileide Reis (leyde-landy@hotmail.com) on 2013-04-17T13:56:29Z No. of bitstreams: 1 Osvaldo Neto.pdf: 21639077 bytes, checksum: 544939bf18e68d64aca26c58a337373c (MD5) / Approved for entry into archive by Rodrigo Meirelles(rodrigomei@ufba.br) on 2013-05-09T17:33:26Z (GMT) No. of bitstreams: 1 Osvaldo Neto.pdf: 21639077 bytes, checksum: 544939bf18e68d64aca26c58a337373c (MD5) / Made available in DSpace on 2013-05-09T17:33:26Z (GMT). No. of bitstreams: 1 Osvaldo Neto.pdf: 21639077 bytes, checksum: 544939bf18e68d64aca26c58a337373c (MD5) Previous issue date: 2011 / A tutela jurídica contra o dano é uma realidade desde os primeiros ordenamentos de que se tem registro. Dentre os elementos necessários à responsabilização figura o nexo de causalidade. O presente trabalho acadêmico, após verificar o transcurso histórico da responsabilidade civil, para melhor compreensão da feição atual de seus institutos, enfrenta o problema da presunção do liame causal, o debate doutrinário sobre o tema, e o acolhimento na maioria das vezes de forma implícita, pela jurisprudência. / Salvador

The concept of causation is essential to ascribing moral and legal responsibility since the only way an agent can make a difference in the world is through her acts causing things to happen. Yet the extent and manner in which the complex features of causation bear on responsibility ascriptions remain unclear. I present an analysis of four aspects of causation which yields new insights into different properties of responsibility and offers increased plausibility to certain moral views. Chapter I examines the realist assumption that causation is an objective and mind-independent relation between space-time located relata – a postulate meant to provide moral assessment with a naturalistic basis and make moral properties continuous with a scientific view of the world. I argue that such a realist stance is problematic, and by extension so are the views seeking to tie responsibility attributions to an objective relation. Chapter II combines the context sensitivity of causal claims with the plausible idea that responsibility ascriptions rest on the assessment of causal sequences relating agents and consequences. I argue that taking context sensitivity seriously compels us to face a choice between moral contrastivism and a mild version of scepticism, viz. responsibility is not impossible, but ultimately difficult to identify with confidence. I show why the latter view is preferable. Chapter III explores the concern that group agents would causally (and morally) overdetermine the effects already caused by their constituent individuals. I argue that non-reductive views of agency and responsibility lack a coherent causal story about how group agents impact the world as relatively independent entities. I explain the practical importance of higher-order entities and suggest a fictionalist stance towards group agency talk. Chapter IV analyses the puzzle of effect selection – if causes have infinitely many effects, but only one or a few are mentioned in causal claims, what determines their selection from the complete set of consequents? I argue that the criteria governing the difference between effects and by-products lack clarity and stability. I use the concerns about appropriate effect selection to formulate an epistemic argument against consequentialism.

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Previous research has shown that causal attributions can be made from patterns of covariation (Cheng, 1997). While the study of how humans learn contingencies goes back decades (e.g., Ward & Jenkins, 1965), cue interaction effects, involving covariations with two or more cues, have taken on particular importance (e.g., Shanks, 1985), due to their rich potential for theoretical insights. One such effect is causal discounting (Goedert & Spellman, 2005): People believe a cue is less contingent if they learned about it in the presence of a more contingent cue. Using a new method for investigating covariation detection, the steamed-trial technique (Allen et al., 2008), Art Markman, Kelly Goedert and I (Laux et al., 2010) have established that differences in bias underlie causal discounting. We argued that this implies discounting is an effect of a process employed to make causal judgments after learning has occurred. Analyses of how different theories account for discounting, especially simulations of associative models, establishes that this is not necessarily correct; several learning models can reproduce our data. However, model and data explorations show that the key feature of those data is that they track relative, not absolute, magnitudes. My dissertation extends this work establishing the plausibility of a comparative judgment process as the locus of causal discounting. I replicate the finding that responding tracks relative magnitudes. By conducting experiments that parametrically manipulate the contingency of the alternative cue (and thereby the relative contingency of the cues), I show that causal discounting is due to responding to contingencies as a linear function of their relative magnitude. I further verify that discounting manifests identically in response to contingencies presented via summary tables. Because summary tables do not afford the series of experiences necessary to build an association, this enhances the credibility of the theory that discounting is due to a shared process employed subsequent to learning—namely, a judgment process. These investigations reveal that discounting is not a cue interaction effect at all, but rather is a manifestation of a fundamental aspect of the systems that subserve covariation detection. / text

This dissertation is a study of Arguments and Clausal Relations of Pima Bajo within the framework of Categorial Unification Grammar. The theoretical framework explored assumes the existence of three major categories--the Argument Categorizing Element, The Propositional Radical, and the Proposition--and studies the structure building mechanisms which account for those categories. The major categories are taken to be feature-value complexes which combine, via unification, with different type of pronominal forms. It is shown that the notion of arguments as feature-values and the application of a categorial unification grammar accounts for the structure of simple as well as for complex constructions. The final part of the dissertation discusses a phonological algebra which accounts for the linear order of elements.

Propensity score methods (PSM) that have been widely used to reduce selection bias in observational studies are restricted to a binary treatment. Imai and van Dyk extended PSM to estimate non-binary treatment effect using stratification with P-Function, and generalized inverse treatment probability weighting (GIPTW). However, propensity score (PS) matching methods on multiple treatments received little attention, and existing generalized PSMs merely focused on estimates of main treatment effects but omitted potential interaction effects that are of essential interest in many studies. In this dissertation, I extend Rubin’s PS matching theory to general treatment regimens under the P-Function framework. From theory to practice, I propose an innovative distance measure that can summarize similarities among subjects in multiple treatment groups. Based on this distance measure I propose four generalized propensity score matching methodologies. The first two methods are extensions of nearest neighbor matching. I implemented Monte Carlo simulation studies to compare them with GIPTW and stratification on P-Function methods. The next two methods are extensions of the nearest neighbor caliper width matching and variable matching. I define the caliper width as the product of a weighted standard deviation of all possible pairwise distances between two treatment groups. I conduct a series of simulation studies to determine an optimal caliper width by searching the lowest mean square error of average causal interaction effect. I further compare the ones with optimal caliper width with other methods using simulations. Finally, I apply these methods to the National Medical Expenditure Survey data to examine the average causal main effect of duration and frequency of smoking as well as their interaction effect on annual medical expenditures. Using proposed methods, researchers can apply regression models with specified interaction terms to the matched data and simultaneously obtain both main and interaction effects estimate with improved statistical properties.

This research survey was carried out to investigate three areas of concern which are commonly associated with the implementation of government development projects: namely: (i) cost overrun causal factors, (ii) effective remedial cost control measures and (iii) apportionment of professional responsibility for either cost overrun causal factors or costs control remedial measures’ implementation. The ultimate aim was to identify major causes of cost overruns, generate and recommend possible solutions to the problem of cost overruns in the Botswana public construction industry. The research strategy adopted, involved the circulation of questionnaires and subsequent statistical data analysis. Initially, an expert group questionnaire test survey was conducted among ten (10) professionals (expert group), in order to solicit professional opinion and contributory input on the research. The purpose of the expert group questionnaire test survey was to refine the research questionnaires, make necessary questionnaire structure amendments, eliminate possible ambiguities, and finally, to make data collection an easy exercise. Through the expert group questionnaire test survey, the research questionnaires were assessed for validity and reliability. Thus, the questionnaire content validity (Saunders et al. 2003) was established by soliciting comments from the expert group, on the representativeness and suitability of the research questionnaires. Lists of causes of cost overruns factors and effective cost control measures were, developed for each of the three major project development cycle phases; namely: the conception/planning/designing, implementation, and completion/commissioning phases. The research questionnaires which were formulated through expert group questionnaire test survey lists of cost overruns causal factors and cost control remedial measures were circulated to a wide range of practicing professionals. In addition, a representative number of case study projects, with specific reference to cost overruns and cost control, were selected for detailed investigation. Three statistical data analytical methods; the respondents ‘s cost overrun factor/cost control measures ranking order, the Kendell’s Correlation Coefficient and the case study analysis, were simultaneously (triangulation analysis), employed in order to draw conclusive results of the research findings. Hence, the result of the survey identified: i) the most frequent cost overrun causal factors; as inadequate project brief, insufficient/inadequate project design, lack of project coordination and contractual claims and ii) the most effective cost control measures; as appointment of competent project personnel, improved project monitoring, awarding contracts to reputable/competent contractors and monitoring teams and providing time and financial management facilities. The third objective, which was to identify and apportion professional personnel responsibility for causal factors and remedial cost control implementation measures; within each of the three-project development cycle phases; yielded the following results: Clients and project managers were found to play a major contributory role in activities that lead to project cost overruns at conception/planning/designing phase. The project implementation phase allocated blame to contractors, architects and quantity surveyors for cost overruns, while quantity surveyors and contractors were found to be responsible for cost overruns at the completion/commissioning phase. On the implementation of effective remedial cost control measures, the professional responsibility scenario was found to be as follows: clients and project managers play a major role at conception/planning/designing phase, whereas quantity surveyors are key players at implementation phase and project managers; at completion /commissioning phase.

This thesis investigates the causal attributions that students make for teacher behaviour towards them, with the focus being on behaviour likely to be considered "negative." The term "causal attributions" refers to the causes that people give for the behaviour of others (and themselves). Causal attributions impact on emotions and behaviour and, as a consequence, can have a powerful influence upon individuals and those with whom they live and work. Attribution theory was prominent within the 1980s, although originated before this time. Despite this, interest in attribution theory has endured and the theory continues to be applied in research from a range of different disciplines. Although earlier studies have investigated causal attributions within schools, these have often focused upon the causal attributions of teachers. Few studies have focused upon the causal attributions of students and a limited number have focused upon the causal attributions that students make for teacher behaviour. Following an extensive literature review, no studies were found which investigated the relevance of Weiner's models (e.g., Weiner 1995; 2006; 2010) to student causal attributions for "negative" teacher behaviour towards them, including the impact upon the students' emotions and the level of responsibility assigned to teachers as a result of the behaviour. Participants comprised over three hundred Year 10 students from three secondary schools within a north-west local authority who completed a questionnaire containing a scenario and both open-ended questions and those which require scaling of responses. Following this, a follow-up study was designed and this was piloted with a further eight Y10 students to gain their experiences and views of completing the questionnaire. The results of the research suggested that, overall, students attributed the "negative" teacher behaviour to external influences (mainly "stress") and that, on the whole, they would feel "anger" as a result of the behaviour. The results do not fully support the tenets of attribution theory in general, nor those of Weiner in particular. However, based on the results of the research presented in this thesis, potential extensions to Weiner's theories and models are proposed and methodological issues relating to exploring attributions are discussed, as are suggestions for future research.

Doctor of Philosophy / Department of Agricultural Economics / Nathan P. Hendricks / This dissertation focuses on the prediction of agricultural land values and the effects of water rights on land values using machine learning algorithms and hedonic pricing methods. I predict agricultural land values with different machine learning algorithms, including ridge regression, least absolute shrinkage and selection operator, random forests, and extreme gradient boosting methods. To analyze the causal effects of water right seniority on agricultural land values, I use the double-selection LASSO technique. The second chapter presents the data used in the dissertation. A unique set of parcel sales from Property Valuation Division of Kansas constitute the backbone of the data used in the estimation. Along with parcel sales data, I collected detailed basis, water, tax, soil, weather, and urban influence data. This chapter provides detailed explanation of various data sources and variable construction processes. The third chapter presents different machine learning models for irrigated agricultural land price predictions in Kansas. Researchers, and policymakers use different models and data sets for price prediction. Recently developed machine learning methods have the power to improve the predictive ability of the models estimated. In this chapter I estimate several machine learning models for predicting the agricultural land values in Kansas. Results indicate that the predictive power of the machine learning methods are stronger compared to standard econometric methods. Median absolute error in extreme gradient boosting estimation is 0.1312 whereas it is 0.6528 in simple OLS model. The fourth chapter examines whether water right seniority is capitalized into irrigated agricultural land values in Kansas. Using a unique data set of irrigated agricultural land sales, I analyze the causal effect of water right seniority on agricultural land values. A possible concern during the estimation of hedonic models is the omitted variable bias so we use double-selection LASSO regression and its variable selection properties to overcome the omitted variable bias. I also estimate generalized additive models to analyze the nonlinearities that may exist. Results show that water rights have a positive impact on irrigated land prices in Kansas. An additional year of water right seniority causes irrigated land value to increase nearly $17 per acre. Further analysis also suggest a nonlinear relationship between seniority and agricultural land prices.

I describe an approach to forming hypotheses about hidden mechanism configurations within devices given external observations and a vocabulary of primitive mechanisms. An implemented causal modelling system called JACK constructs explanations for why a second piece of toast comes out lighter, why the slide in a tire gauge does not slip back inside when the gauge is removed from the tire, and how in a refrigerator a single substance can serve as a heat sink for the interior and a heat source for the exterior. I report the number of hypotheses admitted for each device example, and provide empirical results which isolate the pruning power due to different constraint sources.