Searle’s theory of Biological Naturalism has been largely ignored in the philosophical literature and Searle’s commentators are confused by his seemingly contradictory views. In this dissertation I attempt to make sense of Biological Naturalism. In chapter 2 I will ascertain which concerns prevent Searle’s readers from understanding his position. The remaining chapters aim to dissolve the tensions and dispel any confusion. Chapter 3 considers Searle’s notion of first-person ontology, finding that it expresses a belief that experiences are essentially subjective and qualitative. In chapter 4 I consider the notions of levels of description, causal reduction and what Searle means by causation and realisation. Chapter 5 turns to the question of how to categorise Searle’s position. Many of his critics charge him with being a property dualist. By highlighting the difference between the meaning of irreducibility intended by the property dualist and Searle I show that there is sufficient difference in their use of the term so as to reject an interpretation of Biological Naturalism as a form of property dualism. Chapter 6 is where I turn to the other end of the physicalism/dualism spectrum and assess whether Searle should be seen as holding a form of identity theory. I first argue for a neutral form of identity that I call real identity, which does not include the inherent reductive privileging of standard identity. I then argue that Searle should be seen as advocating a form of real identity theory; a form of token identity theory which does not privilege the physical over the mental. In chapter 7 I return to the main barriers to making sense of Biological Naturalism which I identified in chapter 2 and lay out my response to each. I conclude with a coherent interpretation of Searle’s position.

Public participation is a collective term for a variety of procedures aimed at involving stakeholders and ordinary people in decisions that may affect them. It is playing an increasingly important role in many democratic societies. Consequently, it has provided the impetus for a number of scientific studies. Most studies of public participation view the subject from a macro-level perspective; they focus on the criteria against which successful public involvement processes should be measured, the institutional arrangements and legal framework needed to achieve such success, etc. By contrast, relatively few studies have adopted a micro-level approach to public participation. Such an approach would entail concentrating on its psychosocial dynamics – in other words, on the behaviour and experience of individual participants, the relationships that form between individuals, the manner in which these shape deliberation and decision-making, etc. The aim of this study was therefore to address the aforementioned imbalance. It took the form of an integrative literature review encompassing publications in the fields of psychology and public participation. Its objectives were (a) to develop a theory of the psychosocial dynamics of public participation; (b) on the basis of this theory, to identify ways in which the effectiveness of public involvement processes might be enhanced; and (c) to propose avenues for future research in the field. Systems theory was chosen as a meta-theoretical framework to guide the process of theory-building. Systems theory may be defined as the study of interrelationships between the properties of whole systems and the properties and organisation of their component elements. Hence, it provided a means of demonstrating how the micro-level aspects of a public participation process (such as the actions, motives and perceptions of individual participants) interact with macro-level variables (such as the cultural and socio-political milieu in which it is embedded) to shape its course and outcomes. On the basis of the study, five complementary models of public participation were constructed. The first three models depict the macro-level characteristics of public participation. These set the stage for the remaining two models, which encompass both its macro- and micro-level dynamics. / Thesis (PhD)--University of Pretoria, 2008. / Psychology / unrestricted

Ce travail concerne principalement la notion de modularité hiérarchique et son utilisation pour expliquer la structure et le comportement dynamique des systèmes complexes au moyen de modèles modulaires hiérarchiques, ainsi qu'un concept de ma proposition, l’antimodularité, relié à la possibilité de la détection algorithmique de la modularité hiérarchique. Plus précisément, je mets en évidence la portée pragmatique de la modularité hiérarchique sur la possibilité de l’explication scientifique des systèmes complexes, c’est-à-dire, systèmes qui, selon une description de base choisie par l’observateur, peuvent être considérés comme composés de parties élémentaires discrètes interdépendantes. Je souligne que la modularité hiérarchique est essentielle même au cours de l’expérimentation visée à découvrir la structure de ces systèmes. Mais la détection algorithmique de la modularité hiérarchique se révèle être une tâche affectée par la démontrée intraitabilité computationnelle de la recherche de la meilleure description modulaire hiérarchique, et par l’excessive cherté computationnelle même des méthodes de détection approximatives de la modularité. L’antimodularité consiste en le manque d’une description modulaire appropriée aux exigences de l’observateur, manque dû ou à l’absence de modularité dans la description basique choisie du système, ou à l’impossibilité de produire algorithmiquement une description hiérarchique valide, en raison des dimensions excessives du système à évaluer en relation à la cherté computationnelle des méthodes algorithmiques. Je souligne, de plus, que la modularité et l’antimodularité dépendent du choix pragmatique d’une spécifique description de base du système, choix fait par l’observateur sur la base de ses objectifs explicatifs. Je montre comment l’antimodularité entrave la possibilité d’appliquer au moins trois types bien connus d’explication: mécanique, déductive-nomologique et computationnelle. Un quatrième type, l’explication topologique, reste par contre indemne. Ensuite j’évalue la présence de modularité dans les systèmes biologiques, avec ses possibles conséquences, et l’éventualité d’encourir dans l’antimodularité en biologie et en autres sciences: éventualité assez probable, au moins dans la biologie des systèmes. Je me permet enfin quelques spéculations métaphysiques et historiques plutôt libres. D’un point de vue métaphysique, l’antimodularité semble suggérer une position possible, selon laquelle les espèces naturelles sont modules qui ont été détectés et, en raison de l’intraitabilité computationnelle de la détection de la meilleure description modulaire hiérarchique, il est improbable qu’ils constituent la meilleure façon possible de décrire le monde, parce que la modularité des espèces naturelles assez probablement ne reflète pas la meilleure modularité possible du monde. D’un point de vue historique, l’utilisation croissante des méthodes computationnels pour la détection de la modularité ou pour la simulation de systèmes complexes, en particulier dans certains domaines de la recherche scientifique, suggère la possibilité d’imaginer une multiplicité de disciplines scientifiques émergentes, guidées par une production croissante et auto-alimentante d’explications potentiellement inintelligibles pour les capacités cognitives humaines. Cela, à mon avis, constituerait un changement historique dans la science, qui, s’il n’a pas déjà eu lieu, pourrait bien être sur le point de se produire. / This work is mainly concerned with the notion of hierarchical modularity and its use in explaining structure and dynamical behavior of complex systems by means of hierarchical modular models, as well as with a concept of my proposal, antimodularity, tied to the possibility of the algorithmic detection of hierarchical modularity. Specifically, I highlight the pragmatic bearing of hierarchical modularity on the possibility of scientific explanation of complex systems, that is, systems which, according to a chosen basic description, can be considered as composed of elementary, discrete, interrelated parts. I stress that hierarchical modularity is also required by the experimentation aimed to discover the structure of such systems. Algorithmic detection of hierarchical modularity turns out to be a task plagued by the demonstrated computational intractability of the search for the best hierarchical modular description, and by the high computational expensiveness of even approximated detection methods. Antimodularity consists in the lack of a modular description fitting the needs of the observer, a lack due either to absence of modularity in the system’s chosen basic description, or to the impossibility, due to the excessive size of the system under assessment in relation to the computational cost of algorithmic methods, to algorithmically produce a valid hierarchical description. I stress that modularity and antimodularity depend on the pragmatic choice of a given basic description of the system, a choice made by the observer based on explanatory goals. I show how antimodularity hinders the possibility of applying at least three well-known types of explanation: mechanistic, deductive-nomological and computational. A fourth type, topological explanation, remains unaffected. I then assess the presence of modularity in biological systems, and evaluate the possible consequences, and the likelihood, of incurring in antimodularity in biology and other sciences, concluding that this eventuality is quite likely, at least in systems biology. I finally indulge in some metaphysical and historical speculations: metaphysically, antimodularity seems to suggest a possible position according to which natural kinds are detected modules, and as such, due to the computational hardness of the detection of the best hierarchical modular description, they are unlikely to be the best possible way to describe the world, because the modularity of natural kinds quite probably does not reflect the best possible modularity of the world. From an historical point of view, the growing use of computational methods for modularity detection or simulation of complex systems, especially in certain areas of scientific research, hints at the envisioning of a multiplicity of emerging scientific disciplines guided by a self- sustained, growing production of possibly human-unintelligible explanations. This, I suggest, would constitute an historical change in science, which, if has not already occurred, could well be on the verge of happening. / Questo lavoro riguarda principalmente il concetto di modularità gerarchica e il suo impiego nello spiegare la struttura e il comportamento dinamico di sistemi complessi mediante modelli modulari gerarchici, nonché un concetto di mia proposta, l’antimodularità, legato alla possibilità del rilevamento algoritmico di modularità gerarchica. Nello specifico, evidenzio la portata pragmatica della modularità gerarchica sulla possibilità di spiegazione scientifica dei sistemi complessi, cioè sistemi che, secondo una descrizione di base scelta dall’osservatore, possono essere considerati come composti da parti elementari discrete interrelate. Sottolineo che la modularità gerarchica è essenziale anche nel corso della sperimentazione volta a scoprire la struttura di tali sistemi. Il rilevamento algoritmico della modularità gerarchica si rivela essere un compito affetto dalla dimostrata intrattabilità computazionale della ricerca della migliore descrizione modulare gerarchica, e affetto dal comunque elevato costo computazionale anche dei metodi di rilevamento approssimati della modularità. L’antimodularità consiste nella mancanza di una descrizione modulare adatta alle esigenze dell’osservatore, mancanza dovuta o all’assenza di modularità nella descrizione di base del sistema scelta dall’osservatore, o all’impossibilità di produrre algoritmicamente una sua descrizione gerarchica valida, per le dimensioni eccessive del sistema da valutare in rapporto al costo computazionale dei metodi algoritmici. Sottolineo che modularità e antimodularità dipendono dalla scelta pragmatica di una certa descrizione di base del sistema, scelta fatta dall’osservatore sulla base di obiettivi esplicativi. Mostro poi come l’antimodularità ostacoli la possibilità di applicare almeno tre tipi noti di spiegazione: meccanicistica, deduttivo- nomologica e computazionale. Un quarto tipo di spiegazione, la spiegazione topologica, rimane sostanzialmente immune dalle conseguenze dell’antimodularità. Valuto quindi la presenza di modularità nei sistemi biologici, e le sue possibili conseguenze, nonché l’eventualità di incorrere nell’antimodularità in biologia e in altre scienze, concludendo che questa eventualità è abbastanza probabile, almeno in biologia dei sistemi. Infine, mi permetto alcune speculazioni metafisiche e storiche piuttosto libere. Dal punto di vista metafisico, l’antimodularità sembra suggerire una posizione possibile secondo cui i generi naturali sono moduli che sono stati rilevati, e in quanto tali, a causa dell’intrattabilità computazionale del rilevamento della migliore descrizione modulare gerarchica, è improbabile che essi siano il miglior modo possibile per descrivere il mondo, perché la modularità dei generi naturali molto probabilmente non rispecchia la migliore modularità possibile del mondo. Da un punto di vista storico, il crescente utilizzo di metodi computazionali per il rilevamento della modularità o per la simulazione di sistemi complessi, in particolare in alcuni settori della ricerca scientifica, suggerisce la possibilità di immaginare una molteplicità di discipline scientifiche emergenti, guidate dalla produzione di spiegazioni potenzialmente inintelligibili dal punto di vista cognitivo umano, produzione che potrebbe iniziare ad autoalimentarsi, portando potenzialmente ad una crescita inarrestabile. Suggerisco che questo scenario cos- tituirebbe un cambiamento epocale nel campo della scienza, che, se non è già avvenuto, potrebbe benissimo essere sul punto di realizzarsi.