Time and Phonology: Precedence-Based Representations

A major factor hindering the establishment of a successful neuroscience of phonology centers around the biological viability of a given phonological framework. The ultimate aim of this project is to find potential alignments between linguistics and neuroscience. In this vein, the main topic of the thesis rests upon establishing the minimal complexity requirements for a phonological representation that is biologically plausible, cognitively sound, and empirically motivated. Heeding Minimalist proposals (Chomsky, 1995) that encourage efficiency in computation and economy in representation, I embark on an in-depth exploration of the parameters of cognition that are necessary and sufficient in a phonological representation while discounting the processes and parameters that can be said to be “domain-general”. To that end, I take seriously Ernst Po ̈ppel’s (2004) exhortation to consider the role of temporal events like linear order and precedence in the study of cognitive systems like phonology by surveying the literature on time perception. The conclusions support a separation of order from phonological representations, extending the scope of substance-freeness (Hale and Reiss, 2000) by characterizing order as substance. Such an approach can contribute to thoroughly defining the object of study and offer insight that narrows the search space for potential bridges

Identity, Governmentality, Chronicity and Development: A Study of Zambian Teachers Living With and Affected by HIV and ‘Therapeutic Citizenship’

This research examines the nature and processes of the ‘therapeutic citizenship’ status acquired by HIV positive schoolteachers who are on antiretroviral therapy (ART), and further ascertains this status’s implications for Zambia’s national development prospects. Teachers, who are a key group for those prospects, are disproportionately affected by ART. The theoretical frames of identity, chronicity and governmentality are explored and used as lenses through which the therapeutic citizenship of teachers living with HIV and ART can be understood and appropriated. Additionally, the concept of ubuntu, derived from African philosophies, is used to decipher values and virtues of human community. Semi-structured interviews with 41 HIV positive teachers in Zambia aged 25–55 were conducted. Transcripts were processed using NVivo Pro 12, and thematic analysis in different areas of interest of the thesis was employed. The findings show that reported experiences of being on ART are affected by demographic factors such as location, age and gender. About 70% of participants described their health from a physical point of view, thus excluding mental-health issues caused by the ongoing uncertainties of HIV citizenship. Over 50% of participants found living on ART socially disruptive and medically difficult. For instance, the unending treatment practices around HIV were associated with positionings within a supportive biomedical citizen-state contract around ART, in relation to (de)professionalisation, in relation to ‘accepting’ or resisting lifelong medication, and in relation to citizenship within ‘pharmaceutical colonialism’. However, living with ART also increased pride in what the teachers’ students were achieving, making their HIV less relevant and perhaps less stigmatising. I argue in this thesis that being HIV positive and on ART in Zambia can create a specific form of ‘therapeutic citizenship’. This form of citizenship appears to be shaped by the importance of improving relationships between patients and clinic personnel, by community-based health care, by past experiences and present events, and by ongoing uncertainties about the future. Therefore, HIV citizenship can have both positive and negative influences on national development for a low-income country such as Zambia

Automatic discovery of complex causality

This study entails the understanding of and the development of a computational method for automatically extracting complex expressions in language that correspond to event to event sequential relations in the real world. We here develop component procedures of a system that would be capable of taking raw linguistic input (such as those from narrative writings or social network data), and find real-world semantic relations among events. Such an endeavor is applicable to many types of sequential relations, for which we use causality as a case study, both for its importance as a prominent type of sequential relation between events, as well as for its general prevalence in natural language. But we also demonstrate that the idea is also applicable in principle to other major types of event to event relations, such as reciprocity. The study primarily focuses on those types of causalities that contain complex structures and require in-depth linguistic analyses to discover and extract. Designing an automated method for the extraction of structurally complex causal expressions entails methodologies and theories that are beyond conventional methods used in computational semantics. The classes of adjunctive causal structure, and embedded causal structure are types that are hard to access using traditional methods, but more amenable for methods developed in this study. The principal procedures employed for the extraction of these are a heavily mod- ified form of Hidden Markov Model (HMM), which we use to deal with causal structures that have sequentially complex makeup. We also designed a highly modified Genetic Algo- rithm (GA) adapted for embedded context-free structures, used to rank and extract those causal structures that have deep embedding at the syntax-semantics interface. These will be reformulated, augmented, and explored in depth. With these methods using unsupervised and semi-supervised learning, we were able to obtain reasonable results in terms of discrimination of causal pairs ⟨ei,ej⟩ pairs and some longer chains of causation from corpora. From these results, we were also able to perform additional linguistic analysis over their theoretical semantic structure, and observe aspects of each that allows us to sub-classify the relations according to standard ideas in formal logic as well as from behavioral psychology. These methods would be critical to a system for building a graph theoretic representation of a social network, from corpora produced by entities within that network, which would utilize the methods described in this project, and similar approaches can be extended to model and discover other types of complex event- relations. These types of fundamental technologies, would in turn, help us to design and build the types of on-line and mobile services that provide increased machine awareness of user behavior and to be able to target and cater to users individually