Hopes and Fears of First-Year Freshman College Students during the COVID-19 Pandemic

The COVID-19 pandemic made the experience of being a first-year freshman college student unique. This study aims to analyze the hopes and fears of these students concerning their current life and future goals. Participating students completed the Hopes & Fears questionnaire. Results showed that students’ hopes and fears were mainly connected with domains of education and the global/collective dimension, followed by personal and family members’ health. Two new categories emerged, self-fulfillment and solidarity, reflecting the importance of the contextual dimension that these students were navigating. The findings of the current study contribute to the research of college students’ hopes and fears towards their future and accounts for the analyses of this topic as we progress to a post-pandemic phase.

Metapragmatics and genre: Connecting the strands

Genre analysis involves at least a foray into the social/contextual dimension framing genre-exemplars. One way to explore this dimension is drawing on the concept of metapragmatics, which is primarily associated with (American) linguistic anthropology. However, with a few exceptions, genre studies have not consistently operationalized metapragmatics, either theoretically or practically. The purpose of this article is, therefore, to explore one possible angle of such operationalization by means of studying discourse fragments reflecting on fragments of (these very or other) discourses (so-called metapragmatic discourses) vis--vis any generic properties of the reflected discourse. Specifically, we analyzed comments sections for a number of YouTube videos exemplifying several lifestyle genres. The results indicate that generic references can range from simply using a generic label to refer to the discourse in question (as a token of a certain type/genre) to actually discussing the generic characteristics of the genre it instantiates, as well as projecting certain (generic) metapragmatic stances. Another observation is that different wordings used by the discourse community to refer to generic models can be, as it were, proper generic labels, but they can also be words and phrases that would hardly qualify as proper names of genres from an analysts point of view. Both these proper and other - genre-like - labels are also often used in conjunction with or are replaced by other ways of metapragmatically referring to what the speaker does or even what they are in/by dint of using the discourse in question. This suggests that any generic labels or cues are just part of a large pool of other possible metapragmatic meanings, knowledge, and ideologies circulating in discourse communities. More broadly, the results may indicate that genre studies should see genre as an even less stabilized entity because what a genre is depends on what people who actually use it make of it, as well as augment their standard toolkits with methods aimed at exploring metapragmatic discourse.

CoPart: a context-based partitioning technique for big data

The MapReduce programming paradigm is frequently used in order to process and analyse a huge amount of data. This paradigm relies on the ability to apply the same operation in parallel on independent chunks of data. The consequence is that the overall performances greatly depend on the way data are partitioned among the various computation nodes. The default partitioning technique, provided by systems like Hadoop or Spark, basically performs a random subdivision of the input records, without considering the nature and correlation between them. Even if such approach can be appropriate in the simplest case where all the input records have to be always analyzed, it becomes a limit for sophisticated analyses, in which correlations between records can be exploited to preliminarily prune unnecessary computations. In this paper we design a context-based multi-dimensional partitioning technique, called CoPart, which takes care of data correlation in order to determine how records are subdivided between splits (i.e., units of work assigned to a computation node). More specifically, it considers not only the correlation of data w.r.t. contextual attributes, but also the distribution of each contextual dimension in the dataset. We experimentally compare our approach with existing ones, considering both quality criteria and the query execution times.

An Organizational Change With Quarantined Members

This study tackles the extent to which employees’ attributions and acknowledgments of the innovation implementation’s urgency play a role in their acceptance and readiness behavior during a crisis. Moreover, it highlights the importance of support and knowledge sharing among organization members on social media, given that an organizational change is taking place during a crisis while everyone is being quarantined. Qualitative data are collected from semi-structured interviews as well as from the chats on the WhatsApp group created for this quick innovation implementation decision. Findings reveal that during a crisis, employees’ sensemaking of the organization’s innovation adoption is triggered by attribution to constructive intentionality. The urgency imposed boosts the contextual dimension of the readiness for change, which enhances organization members’ commitment to implement the change. Moreover, when everyone is quarantined, social media is found to be the only means for maintaining social relations, ensuring colleagues’ support and sharing knowledge; and consequently boosting members’ readiness. The value of this research lies in the topic addressed, and in the unusual context in which the innovation implementation took place.

CoPart: A Context-based Partitioning Technique for Big Data

The MapReduce programming paradigm is frequently used in order to process and analyse huge amount of data. This paradigm relies on the ability to apply the same operation in parallel on independent chunks of data. The consequence is that the overall performances greatly depend on the way data are partitioned among the various computation nodes. The default partitioning technique provided by systems like Hadoop or Spark, basically performs a random subdivision of the input records, without considering the nature and correlation between them. Even if such approach can be appropriate in the simplest case where all the input records have to be always analysed, it becomes a limit for sophisticated analyses that imply correlations between records that can be exploited to preliminary prune unnecessary computations.In this paper we propose a partitioning technique which exploits the notion of context for partitioning data. We design a context-based multi-dimensional partitioning technique, called \copart, which considers not only the correlation of data w.r.t. contextual attributes, but also the distribution of each contextual dimension in the dataset. We experimentally compare our approach with existing ones, considering both quality criteria and the query execution times.

Ideological Complexes on Disability in The Iberian Literary Tradition of Galician-Portuguese Songs

Literature has been especially important in the construction of human thought and development. From this perspective, ideology, as a contextual dimension of a higher order, gets into the literary text and, at the same time, becomes shaped by the genius of authors throughout the centuries. Therefore, when we face ideological social dilemmas, such as the emergence, change, perpetuation and consequences of prejudice, stereotyping and discrimination on disability in our society, it is natural to question the role of the literature in the formation of foundational ideological paradigms. This article intends to marry a literary analysis with the functional linguistic approach of Appraisal –dealing with the semantics of evaluation– in order to present an initial set of ideas of our literary tradition in Galician-Portuguese medieval songs. Research goals include: the identification of (mis)representations of disability in the corpus; the detection of ideology(ies) scaffolding prejudicial representations; and the determination of the role of Galician Portuguese songs in consolidating or strengthening this type of prejudice. Results revealed this body of art presenting a misrepresentation of disabled people that, ultimately, composed a corollary of ideological heritage that have influenced the Iberian and Western literary tradition until the present time.

Critical Reflections on Selected Local Narratives of Contextual South African Indigenous Knowledge

Every humanity has some form of indigeneity – whether conscious or unconscious. It behooves all humanity to redefine and reflect on its indigenous roots. Indigenous Knowledge (IK) has been termed in different ways. These include traditional, cultural, local, community knowledge, etc. All these are interlinked and imply that IK is a body of “knowledge” owned by local people in their specific communities and passed on from generation to generation. Therefore, IK is that knowledge which is known to a group of people or is embedded in a community. It could be rural or urban. The chapter aims to present and reflect on selected local narratives to construct a context. This chapter argues for the ‘contextual' dimension when looking at IK. For the past eighteen years the researcher has worked with a number of practitioners and knowledge holders whose experience has shaped his understanding of the South African IK dialogues, debates, research and studies. The approach adopted for this study is a reflexive one.

CRM campaigns with choice for enhanced business process performance

Purpose A substantial body of research evidence has now accumulated in the cause-related marketing (CRM) literature. Yet, research on positive word of mouth (WOM) in the CRM domain is scarce. Based on this, the purpose of this paper is to present a framework that enhances positive WOM persuasion in a CRM context. Design/methodology/approach Specifically, the authors explore collectivism as a contextual dimension for positive WOM persuasion in a CRM setting and discusses three novel constructs for effectively designing such campaigns, namely, cause proximity, choice of donation type and choice variety of donation types in a single offering frame. Based on conceptual logic and drawing on literature from a variety of disciplines, this framework should provide deeper insight into achieving positive WOM persuasion with CRM strategy and implementation. Findings Additionally, the analysis leads to specific research questions regarding the associations between these contrasts and positive WOM persuasion in a CRM context. Originality/value Finally, the managerial and theoretical contributions are discussed, as well as directions for further research.