Discussion Of Relationship Research Articles

Transitioning to Online Instructions and COVID-19 Response: A View from Mining Emergent College Students Discourse in Online Discussion Forum

AbstractThe COVID-19 pandemic disrupted teaching and learning activities in higher education around the world. As universities shifted to remote instruction in response to the pandemic, it is important to learn how students engaged in learning during this challenging period. In this paper, we examined the changes in learners’ social and cognitive presence in online discussion forums prior and after remote instruction. We also extracted emergent topics during the pandemic as an attempt to explore what students talked about and how they interacted with their peers. We extracted discussion forum posts between 2019 and 2020 from courses that have been offered repeatedly each term at a four-year university in the U.S. Our findings suggest that students exhibited higher social presence through increased social and affective language during remote instructions. We also identified emergent COVID-19 related discourse, which involved sharing personal experience with positive sentiments and expressing opinions on contemporary events. Our qualitative analysis further revealed that students showed rapport and empathy towrads others, and engaged in active sense making of the pandemic through engaging in critical discourse. Our study sheds lights on leveraging discussion forum to facilitate learner experiences and building classroom community in online courses. We further discussed the potential for conducting large-scale computational linguistic modeling on learner discourse and the role of artificial intelligence in deriving insights on learning behavior at scale to support remote teaching and learning.

Responsibility to future generations: A strategy for combatting climate change across political divides.

Individuals and governments often fail to take action to address climate change owing largely to widespread politicization of the issue and related discourse. In response to recent appeals for non-partisan approaches to pro-environmentalism, we propose that highlighting one's responsibility to future generations (RFG) could offer promise across the political spectrum. We argue that RFG may be effective because it is widely endorsed, uncorrelated with demographic indicators and less tied to political ideology compared to other forms of responsibility, such as personal responsibility for climate change mitigation. Across six main and seven supplementary studies (N = 161,633), we provide evidence for these claims. RFG is not only widely endorsed across countries and demographic groups but it also significantly predicts various measures of pro-environmental behaviour, both in correlational and pre-registered experimental contexts. These findings confirm established effects, reconcile inconsistencies and suggest prioritizing intergenerational responsibility may effectively reshape climate change narratives for the most resistant parties.

A Survey of Studies on Discourse Structure and Relation

A Survey of Studies on Discourse Structure and Relation

"I have to listen to them or they might harm me" and other narratives of why women endure obstetric violence in Bihar, India.

Evidence suggests that obstetric violence has been prevalent globally and is finally getting some attention through research. This human rights violation takes several forms and is best understood through the narratives of embodied experiences of disrespect and abuse from women and other people who give birth, which is of utmost importance to make efforts in implementing respectful maternity care for a positive birthing experience. This study focused on the drivers of obstetric violence during labor and birth in Bihar, India. Participatory qualitative visual arts-based method of data collection-body mapping-assisted interviews (adapted as birth mapping)-was conducted to understand women's perception of why they are denied respectful maternity care and what makes them vulnerable to obstetric violence during labor and childbirth. This study is embedded in feminist and critical theories that ensure women's narratives are at the center, which was further ensured by the feminist relational discourse analysis. Eight women participated from urban slums and rural villages in Bihar, for 2-4 interactions each, within a week. The data included transcripts, audio files, body maps, birthing stories, and body key, which were analyzed with the help of NVivo 12. Women's narratives suggested drivers that determine how they will be treated during labor and birth, or any form of sexual, reproductive, and maternal healthcare seeking presented through the four themes: (1) "I am admitted under your care, so, I will have to do what you say"-Influence of power on care during childbirth; (2) "I was blindfolded … because there were men"-Influence of gender on care during childbirth; (3) "The more money we give the more convenience we get"-Influence of structure on care during childbirth; and (4) "How could I ask him, how it will come out?"-Influence of culture on care during childbirth. How women will be treated in the society and in the obstetric environment is determined by their identity at the intersections of age, class, caste, marital status, religion, education, and many other sociodemographic factors. The issues related to each of these are intertwined and cross-cutting, which made it difficult to draw clear categorizations because the four themes influenced and overlapped with each other. Son preference, for example, is a gender-based issue that is part of certain cultures in a patriarchal structure as a result of power-based imbalance, which makes the women vulnerable to disrespect and abuse when their baby is assigned female at birth. Sensitive unique feminist methods are important to explore and understand women's embodied experiences of trauma and are essential to understand their perspectives of what drives obstetric violence during childbirth. Sensitive methods of research are crucial for the health systems to learn from and embed women's wants, to address this structural challenge with urgency, and to ensure a positive experience of care.

Slogans as a policy distractor: a case of ‘washback’ discourse in English language testing reforms in Japan

ABSTRACT This paper examines recent reforms in English-language testing in Japan using a policy distraction framework. We identify the term ‘washback (effect)’ and other related discourses as major distractors and investigate how ‘washback’ discourses have functioned as political slogans or catchphrases in policy deliberation processes and how they have diverted attention and resources from more essential issues. By analyzing advisory panel minutes and other policy documents, we demonstrate how policy distraction operates. Some committee members initially introduced ‘washback’ discourse in a deliberation meeting, citing studies on language testing. However, this discourse quickly became a political slogan, transforming into a dubious rationale for advocating the use of commercial four-skills English tests in university entrance exams. This ‘washback’ discourse led to policy distraction and the overlooking of more significant issues, such as class size reduction and the improvement of teachers’ working conditions. Additionally, our analysis reveals underlying factors triggering this distraction, including Japanese ideological views on English education and budgetary austerity in education. We discuss the political and pedagogical implications of these findings, particularly regarding the identification of political distractions, their potential threat to teacher agency, and strategies for addressing and correcting these distractions to facilitate social change.

Exploring the Dynamics of Pak-US Relations in Post 9/11 Era: Military Aid, Nuclear Proliferation and Regional Politics

Throughout history, Pakistan and the United States have experienced a complex and evolving relationship. This relationship has witnessed periods of cooperation, strain, and scrutiny, particularly concerning formal engagement, financial collaboration, military ties, and regional security matters. This study is critical because it illustrates the evolving geopolitical landscape by revealing how military aid and nuclear concerns have affected South Asian security. By highlighting strategic interactions between global powers and regional entities, this research contributes to the international relations discourse. To assess the state of US-Pakistan relations post-9/11, this study investigates counterterrorism, nonproliferation, and regional geopolitics. It examines how Pakistan's counterterrorism operations and regional security are influenced by US military support, as well as the impact of regional geopolitics on the partnership. Employing mixed methods research, the study reveals diverse perspectives on the impact of aid, including both cooperation and concerns regarding conditional assistance. Regional dynamics, such as Afghanistan's stability and India-Pakistan tensions, emerge as critical factors influencing the partnership's evolution. Challenges stemming from divergent interests and perceptions are also highlighted. Furthermore, the quantitative aspect indicates that gender influences the outcome variable, suggesting potential behavioral or attitudinal differences between men and women regarding the studied environment.

Self-efficacy Activation Factors: Analysis of Saudi English Language Learners' Self- Efficacious Discourse

This qualitative study aims at investigating Saudi English language learners' self-efficacy activation factors. Seventy-eight participants were recruited through random sampling wherein 46 belonged to English department, 20 belonged to Computer Science department, and 12 were enrolled in Business Management Diploma at King Khalid University, Saudi Arabia. Initially, classroom observation was carried out to identify the items for the unstructured questionnaire. Unstructured questionnaire and interviews were employed as the main data generation tools. Content analysis was employed to the participants' self-efficacious discourse derived from the data which revealed three main themes: 1) ideological beliefs activated learners’ self-efficacy; 2) good management of time improved language learning outcomes; and 3) teachers’ active role in engaging the learners in language practicing sessions and in LMS activated their self-efficacy. Bandura's triadic reciprocal determinism framework was incorporated in the analysis and discussion of the participants' discourse in relation to the emerged themes. The twofold analysis revealed learners' ideological beliefs as the main psychological factor; time management as the main personal factor; and learners' engagement in technologically assisted learning (LMS) as the main environmental factor that constituted learners' reciprocal determinism for achieving the language learning outcomes.

Kwestia transformacji relacji UE-Rosja w dyskursie politycznym przywódców państw Grupy Wyszehradzkiej

The main purpose of the article is to analyze the transformation of EU-Russia relations in the political discourse of the Visegrad Group leaders in the context of Russia’s full-scale military aggression against Ukraine. Based on the analysis of selected speeches, the author focuses on explaining the style of political leadership of the prime ministers from V4 countries and on the main elements of the presented assumptions regarding the transformation of the European Union’s foreign policy. Particular attention is paid to the issue of future format of EU-Russia relations, as well as to the issue of EU enlargement. For this purpose, a comparative analysis of the leadership style evolution of the main actors (both institutional and individual) from the European Union and the Visegrad Group countries was carried out in relation to the issue of cooperation with Russia in 2014–2022 and after the full-scale Russian invasion that took place on February 24, 2022.

Semantic Augmentation in Chinese Adversarial Corpus for Discourse Relation Recognition Based on Internal Semantic Elements

This paper proposes incorporating linguistic semantic information into discourse relation recognition and constructing a Semantic Augmented Chinese Discourse Corpus (SACA) comprising 9546 adversative complex sentences. In adversative complex sentences, we suggest a quadruple (P, Q, R, Qβ) representing internal semantic elements, where the semantic opposition between Q and Qβ forms the basis of the adversative relationship. P denotes the premise, and R represents the adversative reason. The overall annotation approach of this corpus follows the Penn Discourse Treebank (PDTB), except for the classification of senses. We combined insights from the Chinese Discourse Treebank (CDTB) and obtained eight sense categories for Chinese adversative complex sentences. Based on this corpus, we explore the relationship between sense classification and internal semantic elements within our newly proposed Chinese Adversative Discourse Relation Recognition (CADRR) task. Leveraging deep learning techniques, we constructed various classification models and the model that utilizes internal semantic element features, demonstrating their effectiveness and the applicability of our SACA corpus. Compared with pre-trained models, our model incorporates internal semantic element information to achieve state-of-the-art performance.

Critiquing the sacred and the profane in higher education

This paper sets the stage for an examination of ‘critiquing the sacred and profane in higher education,’ outlining the motivation for exploring collective contribution to the field of higher education studies. Specifically, this paper states that the taken-for-granted concepts that frame academic praxis serve as conceptual lenses to critically evaluate how the academy’s principles and practices are formed and reconstructed over time and across contexts. Paying attention to what is considered sacred (and by whom) and, conversely, what is considered profane reveals a story of what and who is valued and the histories, discourse, and power relations that inform these differential notions of ‘sacredness’. The articles within this special issue collectively illuminate the inherent ambiguity of academic concepts, showcasing their diverse interpretations and the significant implications these hold for higher education practices across different contexts, inviting readers to engage with the complexities and nuances that shape the field.

Parsing and encoding interactive phrase structure for implicit discourse relation recognition

Parsing and encoding interactive phrase structure for implicit discourse relation recognition

ВЗАЄМОДІЯ АНАЛІЗУ ДИСКУРСУ ТА АНАЛІЗУ НАСТРОЇВ ДЛЯ ІДЕНТИФІКАЦІЇ ЕМОЦІЙНОГО СТАНУ В ТЕКСТОВОМУ СПІЛКУВАННІ

This paper is devoted to the study of two fundamental tasks of neuro-linguistic programming: discourse analysis and sentiment analysis, which are two fundamental tasks of natural language processing. The paper examined some models and algorithms for improving data processing in the process of textual communication between users. The study showed that the use of a joint model of discourse analysis and sentiment analysis is mutually beneficial. The results show that the information obtained from the discourse can help in determining the mood, and sentiment analysis and knowledge of two text fragments can help determine the discourse relations between them.

The Misbegotten Critique of the Model Minority Myth

Abstract: I argue in this article that Asian Americanists' standard critique of the "model minority myth" does more harm than good and should therefore be abandoned. I show that the critique misses the forest for the trees, disavowing structural anti-Blackness and the differentiated positioning of Asian Americans and Black people that it produces, thereby misconceiving the stakes and function of model minority discourse. What I offer here, then, is a critique of the critique of model minority discourse—as well as suggestions for how to re-assess such discourse in relation to anti-Blackness.

BBScore: A Brownian Bridge Based Metric for Assessing Text Coherence

Measuring the coherence of text is a vital aspect of evaluating the quality of written content. Recent advancements in neural coherence modeling have demonstrated their efficacy in capturing entity coreference and discourse relations, thereby enhancing coherence evaluation. However, many existing methods heavily depend on static embeddings or focus narrowly on nearby context, constraining their capacity to measure the overarching coherence of long texts. In this paper, we posit that coherent texts inherently manifest a sequential and cohesive interplay among sentences, effectively conveying the central theme, purpose, or standpoint. To explore this abstract relationship, we introduce the "BB Score," a novel reference-free metric grounded in Brownian bridge theory for assessing text coherence. Our findings showcase that when synergized with a simple additional classification component, this metric attains a performance level comparable to state-of-the-art techniques on standard artificial discrimination tasks. We also establish in downstream tasks that this metric effectively differentiates between human-written documents and text generated by large language models within specific domains. Furthermore, we illustrate the efficacy of this approach in detecting written styles attributed to various large language models, underscoring its potential for generalizability. In summary, we present a novel Brownian bridge coherence metric capable of measuring both local and global text coherence, while circumventing the need for end-to-end model training. This flexibility allows for its application in various downstream tasks.

Governing collaborative networks in mega transport projects development: Integrative findings from 34 cases worldwide

To enhance the development of transport infrastructure, various networks characterised by cross-sector, interorganisational collaborations have been designed, structured and deployed to tackle project complexities and achieve predefined objectives. However, these endeavours have received limited scrutiny in prior studies. To address this gap and gain novel insights, we conduct a multi-case review of 34 mega transport projects (MTPs) across 14 countries and regions from the perspective of network-based collaboration governance. Three communal complexities that trigger the governance demand for collaborative networks are first identified, followed by an evaluation of their relationships with network structures and governance mechanisms. The findings reveal a multi-level structure within collaborative networks encompassing collaborative governance, financial governance and interorganisational governance, each of which involves distinct governance structures, processes and orchestrators. Following the above-mentioned analysis, we propose an integrative framework to underpin the typology for collaborative network governance, which enables MTPs to improve cross-sector, interorganisational collaboration. Furthermore, these findings consolidate the knowledge base for MTP development, providing a cross-disciplinary platform to guide developed, developing and undeveloped topics and the related discourse in this important field of academic endeavour.

Cross-genre argument mining: Can language models automatically fill in missing discourse markers?

Available corpora for Argument Mining differ along several axes, and one of the key differences is the presence (or absence) of discourse markers to signal argumentative content. Exploring effective ways to use discourse markers has received wide attention in various discourse parsing tasks, from which it is well-known that discourse markers are strong indicators of discourse relations. To improve the robustness of Argument Mining systems across different genres, we propose to automatically augment a given text with discourse markers such that all relations are explicitly signaled. Our analysis unveils that popular language models taken out-of-the-box fail on this task; however, when fine-tuned on a new heterogeneous dataset that we construct (including synthetic and real examples), they perform considerably better. We demonstrate the impact of our approach on an Argument Mining downstream task, evaluated on different corpora, showing that language models can be trained to automatically fill in discourse markers across different corpora, improving the performance of a downstream model in some, but not all, cases. Our proposed approach can further be employed as an assistant tool for better discourse understanding.

Sense-aware connective-based indices of cohesion and their relationship to cohesion ratings of English language learners’ written production

Abstract The use of connectives has been considered important for assessing the cohesion of written texts (Crossley et al., 2019). However, existing connective-based indices have not systematically addressed two issues of ambiguity, namely, that between discourse and non-discourse use of polysemous word forms and that in terms of the specific discourse relations marked by polysemous discourse connectives (Pitler & Nenkova, 2009). This study proposes 34 sense-aware connective-based indices of cohesion that account for these issues and assesses their predictive power for cohesion ratings in comparison to 25 existing indices. Results from the analysis of 3,911 argumentative essays from the English Language Learner Insight, Proficiency and Skills Evaluation Corpus show that 23 sense-aware indices but only three existing indices correlated significantly and meaningfully with cohesion ratings. The sense-aware indices also exhibited greater predictive power for cohesion ratings than existing indices. The implications of our findings for future cohesion research are discussed.

Space and place for health and care – Nationalist discourses in Swedish daily press during the first year of COVID-19

Sweden’s strategy during COVID-19 with restrictions but no firm closure of the society surprised the rest of the world and was questioned, not least by neighbouring countries. This article analyses public discourses on space and place for health and care in the Swedish daily press during the first year of the pandemic, 2020. Critical discourse analysis was conducted on daily press newspaper articles to approach issues of space, place, health and care during the COVID-10 pandemic. The findings suggest three main discourses. First, a powerful discourse on unity against the threat is articulated, urging citizens in Sweden to be loyal in the national space. Secondly, an affirming national reconstructing discourse is manifested, related to constructions of borders of national space but also in relation to places of family life and social contacts to ‘flatten the curve’ and stay healthy. Thirdly, later in the period the overarching discourse of the nation and its loyal citizens was torn apart and increasing tensions were articulated due to, as it appeared, the uncertain actions from the government. This study adds to the literature on a theoretical and practical level. Raising awareness on nationalist discourses in relation to place, space, health, and care could prove important in combating inequalities in the local society as well as when cooperating on an international level.

A Comparative Study of Relation Classification Approaches for Japanese Discourse Relation Analysis

This paper presents a comparative analysis of classification approaches in the Japanese discourse relation analysis (DRA) task. In the Japanese DRA task, it is difficult to resolve implicit relations where explicit discourse phrases do not appear. To understand implicit relations further, we compared the four approaches by incorporating a special token to encode the relations of the given discourses. Our four approaches included inserting a special token at the beginning of a sentence, end of a sentence, conjunctive position, and random position to classify the relation between the two discourses into one of the following categories: CAUSE/REASON, CONCESSION, CONDITION, PURPOSE, GROUND, CONTRAST, and NONE. Our experimental results revealed that special tokens are available to encode the relations of given discourses more effectively than pooling-based approaches. In particular, the random insertion of a special token outperforms other approaches, including pooling-based approaches, in the most numerous CAUSE/REASON category in implicit relations and categories with few instances. Moreover, we classified the errors in the relation analysis into three categories: confounded phrases, ambiguous relations, and requiring world knowledge for further improvements.

Connective Comprehension in Adults: The Influence of Lexical Transparency, Frequency, and Individual Differences

ABSTRACT The comprehension of connectives is crucial for understanding the discourse relations that make up a text. We studied connective comprehension in English to investigate whether adult comprehenders acquire the meaning and intended use of connectives to a similar extent and how connective features and individual differences impact connective comprehension. A coherence judgment study indicated that differences in how well people comprehend connectives depend on the lexical transparency but not on the frequency of the connective. Furthermore, individual variation between participants can be explained by their vocabulary size, nonverbal IQ, and cognitive reasoning style. Print exposure was not found to be relevant. These findings provide further insight into the factors that influence discourse processing and highlight the need to consider individual differences in discourse comprehension research as well as the need to examine a wider range of connectives in empirical studies of discourse markers.