Critical Discourse Analysis and Rhetorical Tropes in Donald Trump’s First Speech to the UN

Language and politics go hand in hand and learning and comprehending political genre is to learn a language created for codifying, extending and transmitting political discourse in any text/talk. Drawing upon the theoretical framework of Fairclough’s CDA and Rhetoric, the current study aims at investigating Donald Trump’s First Speech, from the point of frequency and functions of some rhetorical strategies (Parallelism, Anaphora and the Power of Three, Antithesis and Expletive, etc.), Nominalization, Passivization, We-groups and Modality as well as Lexical and Textual Analysis, presented to the UN delivered on Sep. 19, 2017. Specifically, the study seeks to determine: (1) how President Trump succeeded in conveying his notions and assumptions to his intended audience, and in convincing and negotiating, (2) how he attempted to explicitly and implicitly pass his attitudes on his targets, and (3) how those orientations, intended notions and assumptions were seamlessly presented to his addressees in discoursal and lexico-grammatical levels; (4) and finally in this underlying trend how he achieved his own ends. The results of the study hope to enhance reading comprehension and writing in academic registers for EFL/ESL students.

Islamification vs. Islamophobia: A Message to the Youth in the Occident: Critical & Rhetorical Inquiries

Drawing upon the recent theoretical framework of Burkean concept of identification (ID), the current study aims at probing the interaction of content and form in two letters penned by Iran’s Supreme Leader and addressed to the Youth on Jan. and Nov. 2015. To this end, the study seeks (i) to determine a role ID takes in the conveyance of intended assumptions to the targeted readers; and (ii) to observe if the writer’s objectives, i.e. to identify himself with the readers and to realize his politically-religiously-infused creeds, result in success or failure; moreover, (iii) it seeks to determine how he achieved his end to attenuate the impacts of blazing inferno of Islamophobia and anti-Islam sentiments in his addressees. The whole corpus (about 3000 words), in light of van Dijk’s Socio-cognitive approach, is critically perused to seek out contextually-coded expressions. The study tries to set out a manner in which political text/talk could be analyzed rhetorically employing ID concept. It was found that ID as a two-way process is a key component for both parties to identify with. It makes the readers align themselves with the writer and helps the writer to associate with the readers and accomplish his goals.

What predicts Swedish teachers' disposition for text talk: A survey study

The significance of reading comprehension can hardly be overestimated. Nevertheless, teachers vary in their disposition or willingness to teach reading comprehension. A wealth of field experimental studies have confirmed the importance of text talk, in class or in teacher-guided small groups, for students' reading comprehension. However, researchers have not yet fully explored what makes teachers practice text talk in the classroom. This study aimed to describe and predict teachers' disposition to practice text talk. The study posited two hypotheses based on professional development theory and social capital theory. The data came from a survey study of 320 Swedish teachers (of grades 1 to 12). The study used (a) item response estimation for measurement and (b) linear regression for analysis. It was found that attitudes towards professional development varied with disposition for text talk, on average, after adjusting for other predictors. It was furthermore found that social capital varied with disposition for text talk, on average, after adjusting for other predictors. The conclusion is that the data offer support for both teacher development theory and social capital theory.

Imran Khan’s Speech at UNGA: A Reflection on Us vs. Them Divide Using Fairclough’s 3D Model in CDA

Critical Discourse Analysis views language in use as a kind of social practice, it is often applied to political language (discourse— text, talk, and/or visual), including public speeches. This paper critically analyzes the speech by the Prime Minister of Pakistan, delivered at the United Nations General Assembly (UNGA) on September 28, 2019. The study uses Fairclough's Three-Dimensional Model, to reflect upon "Us" and "Them" in the context of four major themes of the speech: climate change, money laundering, Islamophobia, and Kashmir. The study uses a mixed-method approach for a thorough review of the speech and discusses power within the discourse and power behind discourse. The findings reveal how language reflects the ideology of the political leaders, and how discourse can form and be formed by social practices. The Prime Minister used language effectively to present the ideological dichotomies between "Us" and "Them" in the context of developing countries-developed countries (powerful politically and economically), Muslims - anti-Muslims, and Pakistan/Kashmir - India. He urged the world-leaders at UNGA's highest political forum, after drawing the line of demarcation, to take steps to resolve the differences to achieve harmony and peace in the world. This research enables the common public of Pakistan to understand their leader in terms of the concept of power by comprehending the profounder meaning that language conveys.

Smartphone Mode Recognition During Stairs Motion

Smartphone mode classification is essential to many applications, such as daily life monitoring, healthcare, and indoor positioning. In the latter, it was shown that knowledge of the smartphone location on pedestrians can improve the positioning accuracy. Most of the research conducted in this field is focused on pedestrian motion in a horizontal plane. In this research, we use supervised machine learning techniques to recognize and classify the smartphone mode (text, talk, pocket and swing) while accounting for the movement up and downstairs. We distinguish between the going up and the down motion, each with four different smartphone modes, making eight states in total. This classification is based on the use of an optimal set of sensors that varies according to battery life and the energy consumption of each sensor. The classifier was trained and tested on a dataset constructed from multiple user measurements (total of 94 min) to achieve robustness. This provided an accuracy of more than 90% in the cross validation method and 91.5% if the texting mode is excluded. When considering only stairs motion, regardless of the direction, the accuracy improves to 97%. These results may assist many algorithms, mainly in pedestrian dead reckoning, in improving a variety of challenges such as speed and step length estimation and cumulative error reduction.