Forming a medical diagnosis is a complicated reasoning process undertaken by physicians. Although there has been much research focusing on clinical reasoning approaches, there is limited empirical evidence in relation to causal attribution in medical diagnosis. The research on which this thesis is based explored and examined the social process of medical diagnosis and provides an explanation of the clinical reasoning and causal attribution used by physicians. The research was undertaken in an Emergency Department within an acute hospital, the data were collected using mixed method approach including one to one semi-structured interviews with individual physicians; observation of their medical assessments of patients and secondary data analysis of the subsequent recorded medical notes. The study involved 202 patients and 26 physicians. The analysis of the physicians’ semi-structured interviews, shows how physicians describe the diagnostic step process and how they blend their clinical reasoning skills and professional judgment with evidence-based medicine. Physicians apply prior learning of taught biomedical and pathophysiological knowledge to question patients using pattern recognition of common signs and symptoms of disease. These findings are portrayed through taped narratives of the physician/patient interaction during the medical diagnostic process, which shows how physicians control the medical encounter. The analysis/interpretation of documentary evidence (recorded medical notes) provides an insight into the way in which physicians used the information gathered during the diagnostic step process. By using SPSS it was possible to cluster the cases (individual patients) into groups. This stage-ordered classification procedure demonstrated commonality amongst individual cases whilst highlighting the uniqueness of any cases. A pattern emerged of two groups of cases: Group 1 - comprised of patients with the presenting complaints of chest pain, shortness of breath, collapse, abdominal pain, per rectal bleed, nausea, vascular and neurological problems and Group 2 - comprised of patients presenting with trauma, mechanical falls, miscarriage/gynaecological problems, allergies/rashes and dental problems. Findings show that the clinical reasoning approaches used varied according to the complexity of the patient’s presenting complaint. The recorded medical notes for the patients in Group 1, were comprehensive and demonstrated a combined approach of hypothetic-deductive and probabilistic reasoning which enabled the physicians to deal with the degree of uncertainty that is inherent in medicine. The recorded process in the medical notes was shortened for the majority of patients in Group 2, and here the clinical reasoning approach used was found to deterministic. It is acknowledged, that this is not always the case. By using crisp set QCA it was possible to explore causal conditions consistent with Group 1. Further analysis led to examination of the link of causal conditions presented in the medical notes with the individual impression/working diagnosis made by physicians.

The ability to make associations between causal cues and outcomes is an important adaptive trait that allows us to properly prepare for an upcoming event. Encoding context is a type of associative processing; thus, context is also an important aspect of acquiring causal relationships. Context gives us additional information about how two events are related and allows us to be flexible in how we respond to causal cues. Research indicates that older adults exhibit an associative deficit as well as a deficit in contextual processing; therefore, it seems likely that these deficits are responsible for the deficit in older adults’ causal learning. The purpose of the current study was to more directly test how associative deficits related to older adults’ contextual processing affect their causal learning. Based on past research, it was hypothesized that older adults would be less likely than younger adults to acquire and use contextual information in causal learning. A causal learning scenario from Boddez, Baeyens, Hermans, and Beckers (2011) was used to test the hypothesis that older adults show deficits in contextual processing in a causal learning scenario. This task examined contextual processing using blocking and extinction. Participants went through eight blocks of trials in which they were exposed to various cues and outcomes. They provided expectancy ratings that indicated how likely they believed an outcome was to occur, and these ratings were used to assess age differences in use of contextual information in a causal learning scenario. As expected, both younger and older adults demonstrated blocking in that they assigned higher causal value to a previously trained target cue (A+) than to another cue (X) that was only presented in compound with cue A later in the task (i.e., AX+). Additionally, when tested in the context where the association was originally learned following extinction training (i.e., A-), the causal value of cue A decreased for all groups, even if extinction training took place in a different context. However, ratings for cue A decreased even more for younger adults whose extinction training took place in a different context when tested in their extinction context.

This thesis contributes to the research field of causal inference, where the effect of a treatment on an outcome is of interest is concerned. Many such effects cannot be estimated through randomised experiments. For example, the effect of higher education on future income needs to be estimated using observational data. In the estimation, assumptions are made to make individuals that get higher education comparable with those not getting higher education, to make the effect estimable. Another assumption often made in causal inference (both in randomised an nonrandomised studies) is that the treatment received by one individual has no effect on the outcome of others. If this assumption is not met, the meaning of the causal effect of the treatment may be unclear. In the first paper the effect of college choice on income is investigated using Swedish register data, by comparing graduates from old and new Swedish universities. A semiparametric method of estimation is used, thereby relaxing functional assumptions for the data. One assumption often made in causal inference in observational studies is that individuals in different treatment groups are comparable, given that a set of pretreatment variables have been adjusted for in the analysis. This so called unconfoundedness assumption is in principle not possible to test and, therefore, in the second paper we propose a Bayesian sensitivity analysis of the unconfoundedness assumption. This analysis is then performed on the results from the first paper. In the third paper of the thesis, we study profile likelihood as a tool for semiparametric estimation of a causal effect of a treatment. A semiparametric version of the Bayesian sensitivity analysis of the unconfoundedness assumption proposed in Paper II is also performed using profile likelihood. The last paper of the thesis is concerned with the estimation of direct and indirect causal effects of a treatment where interference between units is present, i.e., where the treatment of one individual affects the outcome of other individuals. We give unbiased estimators of these direct and indirect effects for situations where treatment probabilities vary between individuals. We also illustrate in a simulation study how direct and indirect causal effects can be estimated when treatment probabilities need to be estimated using background information on individuals.

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High causally uncertain (CU) individuals experience lingering doubts about their ability to determine the causes of social events (Weary & Edwards, 1994). Furthermore, these people tend to perceive their interactions and conversational partners more negatively (Boucher & Jacobson, 2009). However, the reasons for these negative reactions remain unclear. Therefore, the purpose of the current set of studies was to explore two possible explanations for these reactions. Specifically, in three studies, I examined if insufficient uncertainty reduction or negative interpersonal expectations mediate the relationship between causal uncertainty and liking for a recent acquaintance. In Study 1 (N = 114), participants engaged in a brief unstructured dyadic conversation, whereas in Study 2 (N = 176), they engaged in three conversations with different partners. Finally, in Study 3 (N = 220), I examined the effects of temporarily activating causal uncertainty beliefs during initial interactions. As predicted, causal uncertainty was negatively associated with liking and uncertainty reduction. In Studies 1 and 2, high CU participants reported more uncertainty about themselves and their partner, and less liking than did low CU participants. Although chronic levels of causal uncertainty in Study 3 were not associated with liking or uncertainty reduction, participants who reported more current feelings of uncertainty also reported more uncertainty about themselves and their partner, and less liking. More importantly, uncertainty reduction fully mediated the effect of causal uncertainty on liking in Study 1 and partially mediated the effect of current uncertainty feelings on liking in Study 3. Therefore, high CU people’s negative social perceptions appear to stem, at least in part, from an inability to reduce their social uncertainty during initial interactions. In contrast, the relationship between causal uncertainty and interpersonal expectations remains unclear. Although causal uncertainty (as well as current uncertainty feelings) in Studies 1 and 3 were not associated with negative interpersonal expectations, high CU participants in Study 2 did report more negative expectations for their first conversation relative to low CU participants. Furthermore, although causal uncertainty was positively related to rejection sensitivity, rejection sensitivity was unable to account for the causal uncertainty effects on liking. / Thesis (Ph.D, Psychology) -- Queen's University, 2009-07-24 15:13:51.847

The precautionary principle has emerged as one of the most contentious international norms within international environmental law. Yet, despite the vexing conceptual uncertainties confronting the precautionary principle, it is repeatedly invoked by policy makers and incorporated within international and domestic environmental law and agreements. This thesis explores how the international norm of precaution comes to be translated from the international sphere to domestic public policy. The research utilizes the pathways framework, which suggests that there are three additional pathways in additional to the direct implementation of international rules in national law and policy - international norms and discourse, markets and direct access - through which actors, institutions and interests can influence domestic and firm-level policy change. The findings propose an explanation of why Canada came to adopt a particular version of the precautionary principle, also revealing the complex nature of norm transfer, the significance of multiple causal pathways of influence and the interactions arising along these pathways.

The thesis develops solutions to two main problems for mental realism. Mental realism is the theory that mental properties, events, and objects exist, with their own set of characters and causal powers. The first problem comes from the philosophy of science, where Psillos proposes a notion of scientific realism that contradicts mental realism, and consequently, if one is to be a scientific realist in the way Psillos recommends, one must reject mental realism. I propose adaptations to the conception of scientific realism to make it compatible with mental realism. In the process, the thesis defends computational cognitive science from a compelling argument Searle can be seen to endorse but has not put forth in an organized logical manner. A new conception of scientific realism emerges out of this inquiry, integrating the mental into the rest of nature. The second problem for mental realism arises out of non-reductive physicalism- the view that higher-level properties, and in particular mental properties, are irreducible, physically realized, and that physical properties are sufficient non-overdetermining causes of any effect. Kim’s Problem of Causal Exclusion aims to show that the mental, if unreduced, does no causal work. Consequently, given that we should not believe in the existence of properties that do not participate in causation, we would be forced to drop mental realism. A solution is needed. The thesis examines various positions relevant to the debate. Several doctrines of physicalism are explored, rejected, and one is proposed; the thesis shows the way in which Kim’s reductionist position has been constantly inconsistent throughout the years of debate; the thesis argues that trope theory does not compete with a universalist conception of properties to provide a solution; and shows weakness in the Macdonald’s non-reductive monist position and Pereboom’s constitutional coincidence account of mental causation. The thesis suggests that either the premises of Kim’s argument are consistent, and consequently his reductio is logically invalid, or at least one of the premises is false, and therefore the argument is not sound. Consequently, the Problem of Causal Exclusion that Kim claims emerges out of non-reductive physicalism does not force us to reject mental realism. Mental realism lives on.

Multiple Description Coding (MDC) was fi rst formulated by A. Gersho and H. Witsenhausen as a way to improve the robustness of telephony links to outages. Lots of studies have been done in this area up to now. Another application of MDC is the transmission of an image in diff erent descriptions. If because of the link outage during transmission, any one of the descriptions fails, the image could still be reconstructed with some quality at the decoder side. In video coding, inter prediction is a way to reduce temporal redundancy. From an information theoretical point of view, one can model inter prediction with Causal Video Coding (CVC). If because of link outage, we lose any I-frame, how can we reconstruct the corresponding P- or B-frames at the decoder? In this thesis, we are interested in answering this question and we call this scenario as causal video coding with possible loss of the fi rst encoded frame and we denote it by CVC-PL as PL stands for possible loss. In this thesis for the fi rst time, CVC-PL is investigated. Although, due to lack of time, we mostly study two-frame CVC-PL, we extend the problem to M-frame CVC-PL as well. To provide more insight into two-frame CVC-PL, we derive an outer-bound to the achievable rate-distortion sets to show that CVC-PL is a subset of the region combining CVC and peer-to-peer coding. In addition, we propose and prove a new achievable region to highlight the fact that two-frame CVC-PL could be viewed as MDC followed by CVC. Afterwards, we present the main theorem of this thesis, which is the minimum total rate of CVC-PL with two jointly Gaussian distributed sources, i.e. X1 and X2 with normalized correlation coeffi cient r, for di fferent distortion pro files (D1,D2,D3). Defi ning Dr = r^2(D1 -1) + 1, we show that for small D3, i.e. D3 < Dr +D2 -1, CVC-PL could be treated as CVC with two jointly Gaussian distributed sources; for large D3, i.e. D3 > DrD2/(Dr+D2-DrD2), CVC-PL could be treated as two parallel peer-to-peer networks with distortion constraints D1 and D2; and for the other cases of D3, the minimum total rate is 0.5 log (1+ ??)(D3+??)/ (Dr+?? )(D2+?? ) + 0.5 log Dr/(D1D3) where ??=D3-DrD2+r[(1-D1)(1-D2)(D3-Dr)(D3-D2)]^0.5/[Dr+D2-(D3+1) ] We also determine the optimal coding scheme which achieves the minimum total rate. We conclude the thesis by comparing the scenario of CVC-PL with two frames with a coding scheme, in which both of the sources are available at the encoders, i.e. distributed source coding versus centralized source coding. We show that for small D2 or large D3, the distributed source coding can perform as good as the centralized source coding. Finally, we talk about future work and extend and formulate the problem for M sources.

This thesis details two experimental tests that can be applied to particular quantum states to reveal important information. We begin by discussing the relevant background in quantum information. We introduce qubits and qudits as basic quantum states, and we discuss the evolution and measurement of quantum states. We then discuss quantum state tomography as a means by which to obtain complete information about a state, followed by a discussion of state discrimination as a means by which to determine the state given the promise that it is drawn from some known set. We then discuss relevant experimental techniques in quantum optics, including measurement, generation of entanglement, and generation of single photons from entanglement. The first experiment we discuss deals with the causal structure of a system, which is the description of the origin of correlations between two or more states. The causal structure can be direct-cause, meaning that one state causes the other; common-cause, meaning that both states are caused by another; or hybrid-cause, which is a combination of the two. We perform the first implementation of a new type of tomography to determine the causal structure; this is called causal tomography and functions regardless of whether two qubits are related by a common state, a process, or some combination thereof. We implement a process on two entangled photons so that we can select the exact causal structure that results, which ranges continuously between direct-cause and common-cause structures. Using causal tomography, we recover causal structures that closely match expected results and demonstrate that quantum mechanics provides an advantage in causal inference. The second experiment we discuss deals with the unambiguous discrimination of multiple quantum states. For the first time, we apply the principles of unambiguous state discrimination to high-dimensional systems. Given a state chosen randomly out of d possible states encoded in d dimensions, we implement a procedure for determining which state was chosen; this procedure in theory functions without error. We encode and detect the states in the orbital angular momentum degree of freedom up to dimension d=14. Although no experiment can provide perfectly error-free measurement due to inevitable imperfections, we obtain an error rate below the theoretical error rate of minimum-error state discrimination for dimensions up to d=12. At the time of submission of this thesis, this work has been accepted for publication in Physical Review Letters.

An argument for the compatibility of causal determinism and free will. Draws on recently conducted philosophical experimentation related to intuition and development of the intuition of agent-causal accounts of free will in children. Argues that regardless of the intuition held, the manner in which people arise to these intuitions shows that the working definition of free will is different than people posit. Lays groundwork for why the working definition of free will is compatible with causal determinism.