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This research project aims to provide a clear and concise guide to latent dirichlet allocation which is a form of topic modelling. The aim is to help researchers who do not have a strong background in mathematics or statistics to feel comfortable with using topic modelling in their work. In order to achieve this, the thesis provides a step-by-step explanation of how topic modelling works. A range of tools that can be used to perform a topic model analysis are also described. The first chapter gives an explanation of how topic modelling, and (more specifically), latent dirichlet allocation works; it offers a very basic explanation and then provides an easy to follow mathematical explanation. The second chapter explains how to perform a topic model analysis; this is done through an explanation of each step used to run a topic model analysis, starting from the type of dataset through to the software packages available to use. The third section provides an example topic model analysis, based on the Philpapers dataset. The final section provides a discussion on the highlights of each chapter and areas for further research.

The aim of this study is to examine nine texts used as teaching material in the reading project A Reading Class in terms of three different text-analytical structures. The texts analysed are non-fiction texts intended for grades 1–3. The analysis focuses on the similarities and differences in the textual, ideational and interpersonal structure of the texts and how the progression in the texts is revealed.   The result of the analysis shows that there are considerably more similarities than differences between the texts as regards the analysed structures. The analysis cannot find any clear progression between the texts in certain respects, although the analysed material is intended for pupils in different grades, while in other respects it is possible to see some notion of progression. The result also shows that the concept of progression is problematic to apply in a text analysis alone, since it is affected by how teachers work in practice with the material in the classroom.

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Communal coping—a process in which romantic partners view a problem or stressor as "ours" rather than "yours" or "mine" and engage in collaborative problem solving to address it —has emerged as an important predictor of health and treatment outcomes. This study investigated communal coping as a theoretically derived and empirically supported intervention target within two couple-focused interventions for health problems: Family Systems Therapy for problematic alcohol use and Family Consultation for health-compromised smoking. With a combined sample of 56 couples (37 alcohol, 21 smoking), this study investigated within-session changes in communal coping—indexed via observable, communal coping behaviors and first-person plural pronoun use (we-talk)—prior to and following therapist implementation of specific solution-focused therapy techniques that aimed to promote communal coping in the couples during a target therapy session. Teams of trained raters observed the target therapy sessions and made independent ratings of couple communal coping behaviors and therapist adherence. Pronoun measures for each partner were obtained via computerized text analysis from transcripts of partners' speech during the target therapy sessions. Both patients and spouses showed increases in communal coping behavior and we-talk from a "baseline" problem-focused therapy block to the "active" solution-focused therapy block. In addition, exploratory analyses revealed that several couple and therapist characteristics, as well as specific solution-focused techniques were associated with within-session changes in communal coping. Findings from this study identify communal coping as a client change process and solution-focused therapy techniques as a therapist change process within the two interventions, and demonstrate successful engagement of communal coping as a therapeutic target.

The patriarchal legal system and the socio-cultural institutions of the Islamic Republic of Iran (IRI) relegate Iranian women to second-class citizens. Yet, Canadian feminist texts such as Margaret Atwood's The Handmaid's Tale (1985) and Carol Shields's Unless (2002) have been translated into Persian, in 2003 and 2005 respectively. Moreover, they circulate freely and are found in Iran’s National Library. This seeming discrepancy needs a systemic and contextually-based explanation. Four questions guide my dissertation: What happens to the texts as they cross the cultural boundaries into the receiving society? Specifically, which features of feminist texts are most vulnerable to censorial interventions and what does that reveal about the interplay of the hegemonic theocratic-patriarchy and translation? Finally, how is the Persian translation of feminist texts even possible, given Iran’s legal, political and socio-cultural antagonism toward women’s autonomy? In other words, what factors mitigate such translations? To answer these questions, I outline the legal representation of women in the legal discourse and the socio-cultural attitudes towards women’s rights in Iran subsequent to the (1906-1911) Constitutional Revolution and the 1979 Revolution, which led to an Islamist government. I examine the impacts of the IRI’s androcentric legislations on women’s rights, and the censorship mechanisms on Persian and imported feminist literature. I explore the types and extent of resistance to censorship, and I study the representation of women in school textbooks, cinema and Persian literature to analyze the impact that the interaction between the legal discourse, censorship and resistance has on cultural products. I conduct a comparative text analysis using theories of feminist linguistics and descriptive translation studies (Toury 1995; Cameron 1985, 1995) to investigate the extent to which patriarchal mechanisms influence the translation of the two novels. The goal is to determine how the legal and socio-cultural discourses of the target society affect the form and meaning of the translation, and to identify translation strategies that undermine the very features that make a novel female-centric. I demonstrate how these translation strategies consistently produce target texts that conform to the state-sponsored patriarchal agenda, and synchronize with the gender values and norms of the IRI.

The application of feedback to enhance motivation is beneficial across various life contexts. While both feedback and motivation have been studied widely in psychological science, most of this research has used close-ended approaches to study feedback empirically, which limits the scope of investigation. The present study was one of the first applications of text-analysis to assess the impact of feedback on the recipient's motivation. A transformer machine-learning model was used to create a tool that can predict the average motivating influence of a particular feedback statement, as perceived by a recipient within an academic context. Feedback was defined and evaluated from the perspective of Feedback Intervention Theory (FIT). Both research hypotheses were supported, given that the model's motivation predictions were positively associated with the actual motivation scores of feedback statements, and the model was closer to estimating the true motivation scores than expected by chance. These findings, paired with additional exploratory analyses, demonstrated the utility and effectiveness of the model in predicting perceived student motivation from feedback statements. Thus, this research provided a reliable tool researchers and practitioners in academia could use to evaluate the motivating influence of feedback for students, and it might inspire future studies in this domain. / Doctor of Philosophy / The use of feedback to enhance motivation is beneficial across various life domains. While both feedback and motivation have been studied widely in psychological science, most of this research has used close-ended (not text-analytic) approaches to study feedback empirically, which limits the scope of investigation. The present study was one of the first applications of text-analysis to assess the impact of feedback on the recipient's motivation. A machine-learning model was used to create a tool that can predict the average motivating influence of a particular feedback statement, as perceived by a recipient within an academic context. Both research hypotheses were supported. The motivation predictions were positively associated with the actual motivation scores of feedback statements, and the model was closer to estimating the true motivation scores than would be expected by chance. These findings, paired with additional exploratory analyses, demonstrated the utility and effectiveness of the model in predicting perceived student motivation from feedback statements. Additionally, based on this study it is recommended that professors include specific behaviors to be modified when delivering feedback. Thus, this research provided a tool that researchers and practitioners in academia could use to evaluate the motivating influence of feedback for students, and it might certainly inspire future studies in this domain.