This research suggests that to model the complex dynamics of the organisational change in a firm evolving as it implements internet technologies requires capturing diverse independent and interdependent processes across multiple temporal and spatial context both within and external to the firm. This presents both an ontological and epistemological challenge as dominant research methods are either atemporal in nature and attribute action to disembodied variables or are simply storytelling. To provide explanatory legitimacy requires going deeper to capture the action of actors 'acting' within multiple levels of context and to pinpoint deeper 'rock-bottom' causal mechanisms that drive the higher order processes that give rise to the 'organisational life' we observe. To accomplish explanatory legitimacy I develop an analytical method that makes processuality fundamental and allows for the examination and theorising about mechanisms. The first essential element of this method is a framework that guides the researcher in the systematic gathering together of what we already know from the multidisciplinary and eclectic research in e-business, and in the intensive work of gathering empirical evidence. I apply a new methodology I call narrative sequence analysis, that combines process tracing and sequence analyses to make processes intelligible and help illustrate how mechanisms drive these processes. I use this method to develop an explanatory account of the process of e-business development covering three episodes of change within the Commonwealth Bank of Australia from 1995 to 2006. The research finds that the firm evolves over time as it develops new capabilities and identifies and pursues development opportunities by assembling and committing resources to e-business though both technology development and business application. It draws on past experience and gradually learns to develop, integrate and implement technology into existing business operations, discovers new innovative opportunities in which to apply the technology or is drawn into new areas by others who identify opportunities in which to apply the firm's knowledge, resources and technology. The path to development depends on the firms starting position and the timing of the sequence of events encountered along the way. It is a coevolutionary process where the firm interacts, cooperates, adapts and responds to the actions and interactions of other actors, balanced by the uncertainty of e-business and business operation risk.

Causal reconstruction is the task of reading a written causal description of a physical behavior, forming an internal model of the described activity, and demonstrating comprehension through question answering. T his task is difficult because written d escriptions often do not specify exactly how r eferenced events fit together. This article (1) ch aracterizes the causal reconstruction problem, (2) presents a representation called transition space, which portrays events in terms of "transitions,'' or collections of changes expressible in everyday language, and (3) describes a program called PATHFINDER, which uses the transition space representation to perform causal reconstruction on simplified English descriptions of physical activity.

Explanation-based Generalization requires that the learner obtain an explanation of why a precedent exemplifies a concept. It is, therefore, useless if the system fails to find this explanation. However, it is not necessary to give up and resort to purely empirical generalization methods. In fact, the system may already know almost everything it needs to explain the precedent. Learning by Failing to Explain is a method which is able to exploit current knowledge to prune complex precedents, isolating the mysterious parts of the precedent. The idea has two parts: the notion of partially analyzing a precedent to get rid of the parts which are already explainable, and the notion of re-analyzing old rules in terms of new ones, so that more general rules are obtained.

Fault detection, isolation, and recovery are some of the most critical activities in which astronauts and flight controllers participate. Recent systems to perform the FDIR activity lack portability and extensibility, and do not provide any explanation of the system's activity. In this research, we explore the use of an agent-oriented paradigm and Java technology for better performance of FDIR activity. Also, we have explored the use of explanation in agent-oriented systems, and designed a system-activity tracking mecha-nism that helps the user to understand the agents' behavior. We have explored different ways to generalize this mechanism for arbitrary agent systems to use. Furthermore, we studied mechanisms to automatically add the tracking mechanism to an existing agent system. By using AspectJ, an aspect-oriented tool, a plug-and-playable tracking system has been built that can add the capability to track the activity of the system to any JACK agent system easily. Our experience can help further research on using aspect-oriented tools with agent-oriented paradigms together to obtain better performance.

In this paper I will argue that the controversial process of inferring to the best explanation (IBE) can be made more coherent if its formulation recognizes and includes a significant inductive component. To do so, I will examine the relationship between Harman’s, Lipton’s, and Fumerton’s positions on IBE, settling ultimately upon a conception that categorically rejects Harman’s account while appropriating potions of both Lipton’s and Fumerton’s accounts. The resulting formulation will be called inductive-IBE, and I will argue that this formulation more accurately describes the inferential practices employed in scientific inquiry. The upshot of my argument, that IBE contains a significant inductive component, will be that any conclusion born from such types of inductive inference must be, at best, likely, and not a necessity. And, although previous accounts of IBE have accepted the defeasibility of IBE, I will argue that inductive-IBE is more descriptive because it tells us why this fallibility exists. That is, although the Liptonian conception of IBE acknowledges that IBE is fallible, my account specifically addresses this characteristic and, thus, is more descriptive and informative in this regard. I will use inductive-IBE to argue, contra van Fraassen, that IBE can be a legitimate form of inference that leads science to true theories and real entities.

De psykiatriska diagnoserna har ökat i antal det senaste decenniet. Hur påverkas en individ av att få en psykiatrisk diagnos? Bipolär sjukdom tillhör gruppen psykiska sjukdomar och kännetecknas av växlingar mellan förhöjda stämningslägen såsom mani eller hypomani samt perioder av depressioner. Sjukdomen delas in i bipolär I och II, där bipolär I är den allvarligare varianten. Syftet med föreliggande studie är att undersöka vilken betydelse diagnosen haft för individer med bipolär sjukdom. Åtta personer, sex kvinnor och två män mellan 39-65 år (medelålder 51.6) diagnosticerade med bipolär sjukdom I eller II intervjuades. Svaren bearbetades med hjälp av induktiv tematisk analys. Resultatet visar att diagnosen haft en klart övervägande positiv betydelse. De huvudteman som framkom var förklaring, förståelse och acceptans, samt adekvat behandling. De samstämmiga uppfattningarna om att diagnosen haft en stor positiv betydelse förklaras bland annat av att majoriteten av deltagarna levt i många år utan rätt diagnos, vilket i sin tur inneburit många år inom den psykiatriska vården utan att få rätt hjälp. Rätt diagnos har inneburit rätt behandling, i synnerhet medicinskt, men även via psykoedukativa och psykoterapeutiska insatser. Rätt typ av behandling har därmed medfört en balans i livet, där funktionsförmågan förbättrats avsevärt, och livskvalitén ökat. Ett fåtal negativa konsekvenser av diagnosen framkom i två teman; initiala effekter av diagnosen samt diagnosens begränsande effekt.

In this paper I will argue that the controversial process of inferring to the best explanation (IBE) can be made more coherent if its formulation recognizes and includes a significant inductive component. To do so, I will examine the relationship between Harman’s, Lipton’s, and Fumerton’s positions on IBE, settling ultimately upon a conception that categorically rejects Harman’s account while appropriating potions of both Lipton’s and Fumerton’s accounts. The resulting formulation will be called inductive-IBE, and I will argue that this formulation more accurately describes the inferential practices employed in scientific inquiry. The upshot of my argument, that IBE contains a significant inductive component, will be that any conclusion born from such types of inductive inference must be, at best, likely, and not a necessity. And, although previous accounts of IBE have accepted the defeasibility of IBE, I will argue that inductive-IBE is more descriptive because it tells us why this fallibility exists. That is, although the Liptonian conception of IBE acknowledges that IBE is fallible, my account specifically addresses this characteristic and, thus, is more descriptive and informative in this regard. I will use inductive-IBE to argue, contra van Fraassen, that IBE can be a legitimate form of inference that leads science to true theories and real entities.

Fault detection, isolation, and recovery are some of the most critical activities in which astronauts and flight controllers participate. Recent systems to perform the FDIR activity lack portability and extensibility, and do not provide any explanation of the system's activity. In this research, we explore the use of an agent-oriented paradigm and Java technology for better performance of FDIR activity. Also, we have explored the use of explanation in agent-oriented systems, and designed a system-activity tracking mecha-nism that helps the user to understand the agents' behavior. We have explored different ways to generalize this mechanism for arbitrary agent systems to use. Furthermore, we studied mechanisms to automatically add the tracking mechanism to an existing agent system. By using AspectJ, an aspect-oriented tool, a plug-and-playable tracking system has been built that can add the capability to track the activity of the system to any JACK agent system easily. Our experience can help further research on using aspect-oriented tools with agent-oriented paradigms together to obtain better performance.

My dissertation studies three problems that threaten our functional explanatory practices. The first study, The Normativity Problem and Theories of Biological Function, attempts to explain how it is that biological tokens can perform their functions better or worse, and can retain their functions even when not currently performing them. Etiological theories can try to account for the normativity of functions by cumulative selection or by their contributions to fitness. I argue that neither strategy succeeds. Systemic theories hold that functions are the causal contributions of systemic components to the overall capacities of their containing systems. At first glance, systemic theories do not explain the normativity of functions either. I argue that adding a feedback condition to systemic theories can account for the normativity of functions. The second study, The Malfunction Problem and the Functional Individuation of Biological Traits, attempts to dissolve an apparent paradox about how, if biological traits are functionally individuated, it is possible for an organism to possess a biological trait that malfunctions. The malfunction problem articulates the apparent paradox: A ‘malfunctioning’ trait token seems to no longer belong to its functional type and hence cannot malfunction. I show that distinguishing between the functional type that a token instantiates and the current performance of its function dissolves the paradox. The third study, The Necessitation Problem and the Causal Relevance of Functional Properties, attempts to address a vacuity worry about causal explanation that seems to arise when a property referred to by a causal explanation is individuated by its very effects. Since functional properties are individuated by their functions, and functions are effects, it is hard to see how the ascription of functional properties can play an explanatory role. For the relevant explanations seem to be vacuous: the property that purportedly explains the effect is just the property of having that very effect. I argue that causally relevant functional properties are individuated by historical effects, whereas the effects that they causally explain are current. Since the effects individuating causally relevant properties are distinct from the effects that are causally explained, the vacuity worry does not arise. / Philosophy

<p>Cognitive neuroscience is an interdisciplinary enterprise aimed at explaining cognition and behavior. It appears to be succeeding. What accounts for this apparent explanatory success? According to one prominent philosophical thesis, cognitive neuroscience explains by discovering and describing mechanisms. This "mechanist thesis" is open to at least two interpretations: a strong metaphysical thesis that Carl Craver and David Kaplan defend, and a weaker methodological thesis that William Bechtel defends. I argue that the metaphysical thesis is false and that the methodological thesis is too weak to account for the explanatory promise of cognitive neuroscience. My argument draws support from a representative example of research in this field, namely, the neuroscience of decision-making. The example shows that cognitive neuroscience explains in a variety of ways and that the discovery of mechanisms functions primarily as a way of marshaling evidence in support of the models of cognition that are its principle unit of explanatory significance.</p><p> </p><p>The inadequacy of the mechanist program is symptomatic of an implausible but prominent view of scientific understanding. On this view, scientific understanding consists in an accurate and complete description of certain "objective" explanatory relations, that is, relations that hold independently of facts about human psychology. I trace this view to Carl Hempel's logical empiricist reconceptualization of scientific understanding, which then gets extended in Wesley Salmon's causal-mechanistic approach. I argue that the twin objectivist ideals of accuracy and completeness are neither ends we actually value nor ends we ought to value where scientific understanding is concerned. </p><p>The case against objectivism motivates psychologism about understanding, the view that understanding depends on human psychology. I propose and defend a normative psychologistic framework for investigating the nature of understanding in the mind sciences along three empirically-informed dimensions: 1) What are the ends of understanding? 2) What is the nature of the cognitive strategy that we deploy to achieve those ends; and 3) Under what conditions is our deployment of this strategy effective toward achieving those ends? To articulate and defend this view, I build on the work of Elliot Sober to develop a taxonomy of psychologisms about understanding. Epistemological psychologism, a species of naturalism, is the view that justifying claims about understanding requires appealing to what scientists actually do when they seek understanding. Metaphysical psychologism is the view that the truth-makers for claims about understanding include facts about human psychology. I defend both views against objections.</p> / Dissertation