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A contextual model of delusions drawing on discourse analysis is explored, which changes current attributional models to more concrete and observable forms of language-in-context. Most current models view delusions as internal beliefs that are the result of faulty reasoning or cognitive errors, whereas the present model treats delusions as natural discourses that have gone wrong or become exaggerated as strategies shaped by the person’s bad life situations and negative social relationships. Brief reviews are made of the properties attributed to delusional beliefs (Table 1) and of the current explanations for delusions (Table 2). An outline of a discursive contextual analysis is then given along with a review of the life contexts for those with “mental health” issues. Discourse analysis is used to account for the delusional properties as discursive properties (Table 3). Delusions are then analyzed in two ways as normal discourse strategies gone wrong when trying to live in bad life contexts: (1) by analyzing “beliefs” as a way of doing social behavior with language; and (2) by analyzing delusions as normal storytelling gone wrong from being shaped by bad social relationships. Table 5 gives some practical questions for therapists and researchers to explore people’s delusions as discursive strategies.

In this study, we chose to conduct a gender-based contextual analysis of research-performing organizations (RPOs) in the higher-education sector in Albania as a first step toward the implementation of gender budgeting (GB). Our rationale for conducting such a contextual analysis is the overarching need to achieve the European Commission's strategic objectives regarding gender equality in research and innovation. To carry out this analysis, we used reports from She Figures to calculate dominant gender indicators; these reports were produced in collaboration with the statistics published by the Institute of Statistics of Albania. Our methodology is based on a mixed-methods approach that aims to better our understanding of the situation in Albania. The quantitative findings provided by our contextual analysis within academia were synthesized with qualitative findings resulting from a comparative analysis of the content of gender equality plans (GEPs) currently being implemented by thirteen universities in Albania. The results of our contextual analysis study show that even though women account for more than half of the total population of researchers at the national level, playing a significant role in research and innovation, we recommend that the government develop its first national GEP to counteract the inequality that persists in the career trajectories of women and men. GB represents an effective strategy for reducing gender inequality in this context. The supporting results of the content analysis indicate that the phenomenon of vertical segregation has been identified in the great majority of RPOs that have carried out gender-based contextual analyses; moreover, we observed the interaction of GB with GEPs within three such organizations' approach to the gender-based allocation of finances.

Economic models of decision making assume that people have a stable way of thinking about value. In contrast, psychology has shown that people's preferences are often malleable and influenced by normatively irrelevant contextual features. Whereas economics derives its predictions from the assumption that people navigate a world of scarce resources, recent psychological work has shown that people often do not attend to scarcity. In this article, we show that when scarcity does influence cognition, it renders people less susceptible to classic context effects. Under conditions of scarcity, people focus on pressing needs and recognize the trade-offs that must be made against those needs. Those trade-offs frame perception more consistently than irrelevant contextual cues, which exert less influence. The results suggest that scarcity can align certain behaviors more closely with traditional economic predictions.

Defining and measuring readability in the context of financial disclosures becomes important with the increasing use of textual analysis and the Securities and Exchange Commission's plain English initiative. We propose defining readability as the effective communication of valuation-relevant information. The Fog Index—the most commonly applied readability measure—is shown to be poorly specified in financial applications. Of Fog's two components, one is misspecified and the other is difficult to measure. We report that 10-K document file size provides a simple readability proxy that outperforms the Fog Index, does not require document parsing, facilitates replication, and is correlated with alternative readability constructs.

This paper proposes a systematic framework for the analysis of tensions in corporate sustainability. The framework is based on the emerging integrative view on corporate sustainability, which stresses the need for a simultaneous integration of economic, environmental and social dimensions without, a priori, emphasising one over any other. The integrative view presupposes that firms need to accept tensions in corporate sustainability and pursue different sustainability aspects simultaneously even if they seem to contradict each other. The framework proposed in this paper goes beyond the traditional triad of economic, environmental and social dimensions and argues that tensions in corporate sustainability occur between different levels, in change processes and within a temporal and spatial context. The framework provides vital groundwork for managing tensions in corporate sustainability based on paradox strategies. The paper then applies the framework to identify and characterise four selected tensions and illustrates how key approaches from the literature on strategic contradictions, tensions and paradoxes—i.e., acceptance and resolution strategies—can be used to manage these tensions. Thereby, it refines the emerging literature on the integrative view for the management of tensions in corporate sustainability. The framework also provides managers with a better understanding of tensions in corporate sustainability and enables them to embrace these tensions in their decision making.

Unlike traditional citation analysis, which assumes that all citations in a paper are equivalent, citation context analysis considers the contextual information of individual citations. However, citation context analysis requires creating a large amount of data through annotation, which hinders its widespread use. This study explored the applicability of Large Language Models (LLM)—particularly Generative Pre-trained Transformer (GPT)—to citation context analysis by comparing LLM and human annotation results. The results showed that LLM annotation is as good as or better than human annotation in terms of consistency but poor in terms of its predictive performance. Thus, having LLM immediately replace human annotators in citation context analysis is inappropriate. However, the annotation results obtained by LLM can be used as reference information when narrowing the annotation results obtained by multiple human annotators down to one; alternatively, the LLM can be used as an annotator when it is difficult to prepare sufficient human annotators. This study provides basic findings important for the future development of citation context analysis.

I present a brief review of problems in the sociological study of culture, followed by an integrated, interdisciplinary view of culture that eschews extreme contextualism and other orthodoxies. Culture is defined as the conjugate product of two reciprocal, componential processes. The first is a dynamically stable process of collectively made, reproduced, and unevenly shared knowledge structures that are informational and meaningful, internally embodied, and externally represented and that provide predictability, coordination equilibria, continuity, and meaning in human actions and interactions. The second is a pragmatic component of culture that grounds the first, and it has its own rules of usage and a pragmatically derived structure of practical knowledge. I also offer an account of change and draw on knowledge activation theory in exploring the microdynamics of cultural practice and propose the concept of cultural configuration as a better way of studying cultural practice in highly heterogeneous modern societies where people shift between multiple, overlapping configurations.

While present bias is an old idea, it only took hold in economics following David Laibson's (1994) dissertation. Over the past 20 years, research has led to a much better theoretical understanding of present bias, when and how to apply it, and which ancillary assumptions are appropriate in different contexts. Empirical analyses have demonstrated how present bias can improve our understanding of behavior in various economic field contexts. Nonetheless, there is still much to learn. In this paper, we give our assessment of some lessons learned, and to be learned.

Cause-related marketing (C-RM) has risen to become a popular strategy to increase business value through profit-motivated giving. Despite the growing number of articles published in the last decade, no comprehensive analysis of the most discussed constructs of cause-related marketing is available. This paper uses an advanced Text Mining methodology (a Bayesian contextual analysis algorithm known as Correlated Topic Model, CTM) to conduct a comprehensive analysis of 246 articles published in 40 different journals between 1988 and 2013 on the subject of cause-related marketing. Text Mining also allows quantitative analyses to be performed on the literature. For instance, it is shown that the most prominent long-term topics discussed since 1988 on the subject are \"brand-cause fit\", \"law and Ethics\", and \"corporate and social identification\", while the most actively discussed topic presently is \"sectors raising social taboos and moral debates\". The paper has two goals: first, it introduces the technique of CTM to the Marketing area, illustrating how Text Mining may guide, simplify, and enhance review processes while providing objective building blocks (topics) to be used in a review; second, it applies CTM to the C-RM field, uncovering and summarizing the most discussed topics. Mining text, however, is not aimed at replacing all subjective decisions that must be taken as part of literature review methodologies.

Although research shows that students with autism spectrum disorder (ASD) can develop abilities and skills associated with self-determination (e.g., decision making, problem solving, goal setting and attainment) when opportunities and supports are provided, students with ASD tend to show lower levels of self-determination compared to their peers without disabilities or with other disabilities. Researchers have suggested that common ASD characteristics may influence the development and expression of self-determination and that there may be less focus on self-determination and its development in ASD. Therefore, the aim of this review was to investigate existing studies that examined factors impacting the development of self-determination for students with ASD or implemented self-determination interventions with students with ASD. We reviewed existing empirical studies related to self-determination and students with ASD published in peer-reviewed journals. We examined the thematic categories of research studies, rigor of research, and influential factors. Among the 18 included studies, three distinct thematic categories were identified: (a) intervention research, (b) stakeholders’ perceptions, and (c) contextual analysis. Intervention articles were the most prevalent, followed by articles that reported stakeholders’ perceptions. Contextual analysis articles were less common. Several factors have been identified that influence student self-determination (e.g. age, gender, hours spent with peers, educational placement). This review suggests that self-determination of students with ASD can be promoted through instructional methods, and there are personal and environmental factors that are important to consider when supporting the self-determination of students with ASD. However, there is a need for enhanced rigor of research in future studies.