Contextual Grounding Research Articles

“Staying isolated indoors means that nobody sees me”: ontological (in)security and living with significant appearance concerns before, during, and “since” COVID-19

ABSTRACT Purpose Though a worldwide period of uncertainty (COVID-19) has “ended”, there exists a legacy of maladaptive experiences among people with significant appearance concerns (SAC) that requires care and attention. Methods Using Giddens’ concept of ontological security, we explored how people experienced their SAC before, during and “since” COVID-19. Qualitative surveys allowed us to capture diverse perspectives from individuals transnationally, analysed with deductive reflexive thematic analysis using ontological security as our theoretical foundation. Results Themes named “More Mirror(ed) Time” and “Locked Out, Shut Down, and Shut Out” gave a contextual grounding for the embodied experiences of this group through times of social restrictions, and the theme “Redefining Relevance” explored the continued legacy of COVID-19 – and continued global uncertainties such as economic hardship and warfare – that impact the wellbeing of people with SAC. Conclusions People with SAC are still “locked out” from essential healthcare support as those providing healthcare are overworked, under-resourced and rely on efficient interactive methods such as tele-health that may be triggers for people with SAC. Care providers may consider expanding appearance concerns verbiage, look to involve trusted others in the care-seeking process, and utilize modalities beyond digital health to support people with SAC.

Innovations in Time Related Expression Recognition Using LSTM Networks

The proposed architecture leverages the strengths of both Convolutional Neural Network (CNN) and Bidirectional Long Short-Term (BLSTM) to create a robust model for temporal expression recognition in clinical texts. The CNN component effectively captures morphological and orthographic features at the character level, which enriches the semantic understanding of complex medical terminologies that are often abbreviated or have unique suffixes and prefixes. The BLSTM component excels in capturing long-range dependencies in text, which is crucial for understanding the context in which temporal expressions occur. By integrating these models with a CRF layer, the system not only predicts discrete labels but also ensures that the sequence of predicted labels is coherent and contextually appropriate, addressing the limitations of models that predict labels independently. The integration of pre-trained biomedical word vectors provides significant contextual grounding tailored to the medical domain, enhancing the model's ability to discern and interpret the nuances of medical language. This is crucial in clinical contexts where accurate interpretation of temporal phrases can be critical for patient management and treatment timelines. Further, experiments conducted on the dataset validate the effectiveness of the proposed model, demonstrating a notable improvement over traditional methods that rely heavily on hand-crafted features and rule-based approaches. Future work could explore the adaptability of this model to other subdomains of the medical field and its efficacy in processing multilingual texts, potentially increasing its applicability in global healthcare settings, with further refinement of the neural architecture and optimization of training strategies potentially yielding even better performance and faster processing times essential for real-time clinical decision support systems.

Improving Large Language Model (LLM) fidelity through context-aware grounding: A systematic approach to reliability and veracity

As Large Language Models (LLMs) become increasingly sophisticated and ubiquitous in natural language processing (NLP) applications, ensuring their robustness, trustworthiness, and alignment with human values has become a critical challenge. This paper presents a novel framework for contextual grounding in textual models, with a particular emphasis on the Context Representation stage. Our approach aims to enhance the reliability and ethical alignment of these models through a comprehensive, context-aware methodology. By explicitly capturing and representing relevant situational, cultural, and ethical contexts in a machine-readable format, we lay the foundation for anchoring a model's behavior within these contexts. Our approach leverages techniques from knowledge representation and reasoning, such as ontologies, semantic web technologies, and logic-based formalisms. We evaluate our framework on real-world textual datasets, demonstrating its effectiveness in improving model performance, fairness, and alignment with human expectations, while maintaining high accuracy. Furthermore, we discuss the other key components of the framework, including context-aware encoding, context-aware learning, interpretability and explainability, and continuous monitoring and adaptation. This research contributes to the growing body of work on responsible AI, offering a practical approach to developing more reliable, trustworthy, and ethically-aligned language models. Our findings have significant implications for the deployment of LLMs in sensitive domains such as healthcare, legal systems, and social services, where contextual understanding is paramount.

Board competence and green innovation—Does external governance matter?

AbstractPrevious research examining the link between board attributes and ecological strategies such as green innovation has primarily focused on structural board attributes, yielding mixed findings. Moreover, the critical contextual grounds that shape the relationship between board attributes and green innovation have often been overlooked, leading to potential biases in empirical investigations. Considering that competence drives outstanding performance, we developed a unique measure of board competence that represents the board's intrinsic ability to perform in corporate strategies. Drawing on a holistic perspective of agency, resource dependence, and stakeholder theories, we posit a strong relationship between board competence and green innovation. Furthermore, we contend that this association is moderated by external governance mechanisms, namely audit quality, media coverage, and imitative pressure. Through our analysis of publicly traded Chinese companies, we found compelling evidence to support our assertions. These findings have important implications for policymakers, practitioners, and managers.

Understanding human nature through taste: Dasan Jeong Yak‐yong's account of human‐nature‐as‐taste

AbstractThis essay investigates Dasan Jeong Yak‐yong's (1762–1836) account of human‐nature‐as‐taste, by comparing his commentaries on significant chapters in the Mengzi to Zhu Xi's commentaries. Dasan argues that human nature is understood through giho, taste sentiments and desires, and not as Principle (li). I first introduce Dasan's account of human‐nature‐as‐taste in his commentaries to 3A1 and 7A4. Next, I argue that giho is most appropriately translated as “taste,” because this term captures the dispositional characteristics of giho as a mental faculty as well as its mental effects, such as desires, sentiments, and preferences. I then examine Dasan's and Zhu Xi's commentaries on 6A7 and 6A6, to illustrate how Dasan's view of human‐nature‐as‐taste interprets the chapters differently from Zhu Xi's metaphysical account of human‐nature‐as‐Principle, which Dasan considers as unsupported by the philological and contextual grounds. This exploration of Dasan's empirical account of human‐nature‐as‐taste, serving as a preliminary for a philosophical study of his reinterpretation of the Confucian Classics and his performative account of moral self‐cultivation, will provide us with an alternative perspective to the Neo‐Confucian metaphysic‐epistemic account of human nature.

‘The law is very, very outdated and not keeping up with the technology’: novel forms of assisted gestation, legal challenges, and perspectives of reproductive rights advocates in England and Wales

Abstract A growing body of literature examines the ethico-legal challenges resulting from novel forms of assisted gestation like uterus transplantation and artificial placentas (also known as ‘artificial wombs’). However, there has not yet been consideration of reproductive rights organizations/advocates’ understandings of novel forms of assisted gestation and their challenges. These perspectives provide critical insight into how novel procreative practices are understood and the problems and pressures that might arise from their use. This is the first legal article to engage with reproductive rights organizations/advocates and thus it provides important contextual grounding to existing scholarship about assisted gestation. Focus group discussion epitomized the need for legal reform in key areas surrounding reproduction. Themes were constructed that exemplify what participants highlighted as critical: the need to re-evaluate the fundamentals of legal parenthood, consideration of how novel technologies could further enable the policing of gestation, and the space and time needed for law-making.

Deep-Fuzz: A synergistic integration of deep learning and fuzzy water flows for fine-grained nuclei segmentation in digital pathology.

Robust semantic segmentation of tumour micro-environment is one of the major open challenges in machine learning enabled computational pathology. Though deep learning based systems have made significant progress, their task agnostic data driven approach often lacks the contextual grounding necessary in biomedical applications. We present a novel fuzzy water flow scheme that takes the coarse segmentation output of a base deep learning framework to then provide a more fine-grained and instance level robust segmentation output. Our two stage synergistic segmentation method, Deep-Fuzz, works especially well for overlapping objects, and achieves state-of-the-art performance in four public cell nuclei segmentation datasets. We also show through visual examples how our final output is better aligned with pathological insights, and thus more clinically interpretable.

Why Biblical Arguments for Abortion Fail

Abstract While the traditional Christian teaching opposing abortion has been relatively unanimous until the twentieth century, it has been claimed in more recent decades that certain Biblical passages support the view that the fetus, or unborn child, has a lesser moral status than a born child, in a way that might support the permissibility of abortion. In this paper, I address the foremost three texts used to argue this point: Genesis 2:7; Exodus 21:22–25; and Numbers 5:11–31. I argue that interpreting the former in the literal way necessary to support abortion leads to untenable moral and exegetical conclusions, indeed straightforwardly contradicting other Biblical texts. I then demonstrate that the most plausible readings of the other passages—on textual and contextual grounds—do not support a lesser moral status, one of the passages plausibly even supporting full moral status, for the unborn child.

A research broker for a third‐culture researcher: Experiences conducting field research in urban Pakistan

AbstractAlthough much debate has been undertaken about the insider–outsider and in‐betweener positionalities within social science research, the third‐culture researcher (TCR) represents an under‐researched identity which demands greater attention. Conducting doctoral fieldwork in Islamabad as a TCR gave rise to challenges that were navigated through a research broker. The TCR positionality represents one who visits their country of ethnicity for the purposes of conducting research having mostly lived abroad, or as one who conducts research in a country where they have mostly lived but do not share ethnicity. I argue that research brokers are particularly important for TCRs—and in‐betweener researchers more generally—because they provide contextual grounding, protection, and access to people and places where TCRs have partial familiarity with local conditions and where all actors involved are embedded within a context of risk. Research brokers also supplement TCRs' in‐between status by negotiating and managing their own positionality and skillset to facilitate interaction between the researcher and participants. This process can be challenging and has its limitations. I assert this by drawing on joint reflections and an interview with my research broker, as well as personal anecdotes. The TCR–broker relationship transforms knowledge production in multiple ways. Firstly, working with an actor with a unique positionality and skillset offers insight into how different identities interact and engage to shape research relations and outcomes. Secondly, it highlights how the research site is experienced differently and carries various meanings, significance and consequences for those involved. Finally, the TCR–broker relationship offers the opportunity to engage in candid discussions about the benefits and limitations involved in working with others. The broker creates a significant impression on the research during fieldwork and beyond. Highlighting their voices adds to our scholarly understanding of the impact of positionality on qualitative social science methodological research.

The Heavenly Field: A Reconsideration of Mother Earth in the Æcerbot Rite

The Heavenly Field: A Reconsideration of Mother Earth in the <i>Æcerbot</i> Rite

A code-mixed task-oriented dialog dataset for medical domain

In the healthcare domain, medical and patient interactions form a crucial part of the diagnosis. Initially, the AI models developed for healthcare centered only on monolingual data. However, such models do not cater to the multilingual regions, where most conversations are Code-Mixed. We present the Code-Mixed Medical Task-Oriented Dialog Dataset to facilitate the research and development of Code-Mixed medical dialog systems. We analyzed the dataset using medical, conversational, and linguistic theories. The dataset contains 3005 Telugu–English Code-Mixed dialogs between patients and doctors with 29 k utterances covering ten specializations with an average code-mixing index (CMI) of 33.3%. We manually annotated the conversational dataset with intents and slot labels. We also present baselines to establish benchmarks on the dataset using existing state-of-the-art Natural Language Understanding (NLU) models. We improved the existing baselines using contextual ground truth intent labels and processing the slots as chunks. The data is made publically available.11https://github.com/suman101112/Code-Mixed-TOD-Medical-Dataset.git.

Twenty-first century bioarchaeology: Taking stock and moving forward.

This article presents outcomes from a Workshop entitled "Bioarchaeology: Taking Stock and Moving Forward," which was held at Arizona State University (ASU) on March 6-8, 2020. Funded by the National Science Foundation (NSF), the School of Human Evolution and Social Change (ASU), and the Center for Bioarchaeological Research (CBR, ASU), the Workshop's overall goal was to explore reasons why research proposals submitted by bioarchaeologists, both graduate students and established scholars, fared disproportionately poorly within recent NSF Anthropology Program competitions and to offer advice for increasing success. Therefore, this Workshop comprised 43 international scholars and four advanced graduate students with a history of successful grant acquisition, primarily from the United States. Ultimately, we focused on two related aims: (1) best practices for improving research designs and training and (2) evaluating topics of contemporary significance that reverberate through history and beyond as promising trajectories for bioarchaeological research. Among the former were contextual grounding, research question/hypothesis generation, statistical procedures appropriate for small samples and mixed qualitative/quantitative data, the salience of Bayesian methods, and training program content. Topical foci included ethics, social inequality, identity (including intersectionality), climate change, migration, violence, epidemic disease, adaptability/plasticity, the osteological paradox, and the developmental origins of health and disease. Given the profound changes required globally to address decolonization in the 21st century, this concern also entered many formal and informal discussions.

Dream, Bliss, and the Shaping of Emotional Meaning in Beowulf

<i>Dream</i>, <i>Bliss</i>, and the Shaping of Emotional Meaning in <i>Beowulf</i>

Hijrah of Our Time: Islamic Concept of Religious Emigration in Contemporary Salafism

This study presents a comparison of the religious-legal concept of the hijrah in the approach of schools of Salafism, which are the Islamic State in Iraq and the Levant and the Muhammad al-Albani’s and his disciples’ teachings. The first, theoretical section of the submitted material, intends to provide a contextual ground on which the analytical chapter of this article is built up. The subsequent analytical section focuses on the breakdown of Salafist’s take on the hijrah through a qualitative content analysis of several texts that include, on one hand, the production of Muhammad al-Albani and his students, and on the other hand, the magazines Dabiq and Rumiyah, which were published on behalf of the Islamic State of Iraq and the Levant. The reason for choosing these particular authors and their conception of hijrah as the main research intention of the presented study is that on one hand the Islamic State represents the latest entity that conceptually grasped the topic and, above all, made it one of the pillars of its general ideology and on the other hand teachings of al-Albani are extremely influential in mainstream Salafism. The analysis showed that in general, both scrutinized Salafist schools are similar in the main principles, ie. both consider the hijrah to be an ongoing religious duty. However, they differ in details and also in the emphasis on violence, with the Islamic State emphasizing that hijrah and jihad are two stages of a single process, with the only possible destination for the hijrah being Islamic State territory.

Why should we cultivate “the difference” in everyday practices of the university?

AbstractThe paper explores the phenomenon of the local‐worldly university. Why should we cultivate “the Difference” in everyday practices of the university? The author refers to the Derridean “différance,” to the idea of wonder (το θαυμα) and the Herderean concept of Heimat. By putting these terms in the university's specific context, the author asks questions about an autonomous space for thinking and experiencing. The university cannot be homeless, unanchored or uncommitted. The more intensively the universalising procedures of the control of universities are implemented, the more we are convinced that the world does not need any global institutions of higher education and research. This is because a human being is more localised than we would be willing to admit. What is important is difference, the untranslatability of knowledge and languages, the contextual grounding of thinking and action, as well as the experience of the fragility of what is “locally human,” which makes us observe closely a local human being, attached to a place, wandering about with the notion of home, and thus dispelling his or her doubts here and now, even when they tend to recur eternally.

First 1000 days: first-time mothers’ understanding and experiences of nutritional care

ABSTRACT Within South Africa, approximately 1.5 million children suffer from malnutrition and stunting with dire effects on their early development and thriving potential. Nutritional care within the first 1000 days of children's life plays pivotal role in their holistic development when a stable, safe, nurturing and responsive relationship is provided by their mothers. This study explored first-time mothers’ understanding and experiences of nutrition within the first 1000 days of their child's life. A total of 12 first-time mothers with infants aged 4–21 months living in low-income communities in Cape Town completed semi-structured interviews. A thematic analysis suggested that mothers generally acknowledged nutrition as crucial for the development of young children; however, many were unfamiliar with the phrase ‘first 1000 days’. The findings provide contextual grounding for the gap in knowledge and awareness of the first 1000 days within South African low-income communities.

Multilingual support in HIV/ STD counselling in Flanders

ABSTRACT In this article, we explore the multiple challenges faced by health service providers and immigrant patients when addressing sensitive issues in the context of HIV/STD counselling. To do so, we adopt a case-study approach which enables a deeply contextualised examination of the interactional process. The analysis will draw particular attention to the issue of contextual common ground, or the lack thereof, and how this correlates with the complex interactional conditions of the encounter. These conditions entail a combination of challenges, including the use of ad hoc interpreters on sensitive topics, in a remote, non-face-to-face constellation and with the use of digital support tools that are not equally accessible for all participants. We argue that this accumulation of multilingual, multimodal and multi-contextual challenges engenders the emergence of parallel tracks and limited consonance between institutional-counselling concerns on the one hand and experiential-patient concerns on the other.

The Sin of the Angels in 2 Peter 2:4 and Jude 6

The angelic sin of 2 Pet 2:4 and Jude 6 is thought to reflect the Watcher myth of the Book of the Watchers on the grounds of the popularity of the myth in early Judaism and the literary relationship between 1 En. 1:9 and Jude 14-15. A critical reexamination of the evidence, however, suggests contrasting approaches to the myth and a variety of traditions in the Enoch literature undermining both of the above assumptions. The nature of the angelic sin of 2 Pet 2:4 and Jude 6 can best be confirmed on contextual grounds. In this respect, the intentional parallel between examples of punishment and the sins of the false teachers in both 2 Peter and Jude identifies the angelic sin in question as blasphemy—an aspiration to the position of God—in agreement with a long tradition of angelic blasphemy in Jewish and early Christian exposition.

The Sin of the Angels in 2 Peter 2:4 and Jude 6

The angelic sin of 2 Pet 2:4 and Jude 6 is thought to reflect the Watcher myth of the Book of the Watchers on the grounds of the popularity of the myth in early Judaism and the literary relationship between 1 En. 1:9 and Jude 14–15. A critical reexamination of the evidence, however, suggests contrasting approaches to the myth and a variety of traditions in the Enoch literature undermining both of the above assumptions. The nature of the angelic sin of 2 Pet 2:4 and Jude 6 can best be confirmed on contextual grounds. In this respect, the intentional parallel between examples of punishment and the sins of the false teachers in both 2 Peter and Jude identifies the angelic sin in question as blasphemy—an aspiration to the position of God—in agreement with a long tradition of angelic blasphemy in Jewish and early Christian exposition.

An empirical characterization of fair machine learning for clinical risk prediction

The use of machine learning to guide clinical decision making has the potential to worsen existing health disparities. Several recent works frame the problem as that of algorithmic fairness, a framework that has attracted considerable attention and criticism. However, the appropriateness of this framework is unclear due to both ethical as well as technical considerations, the latter of which include trade-offs between measures of fairness and model performance that are not well-understood for predictive models of clinical outcomes. To inform the ongoing debate, we conduct an empirical study to characterize the impact of penalizing group fairness violations on an array of measures of model performance and group fairness. We repeat the analysis across multiple observational healthcare databases, clinical outcomes, and sensitive attributes. We find that procedures that penalize differences between the distributions of predictions across groups induce nearly-universal degradation of multiple performance metrics within groups. On examining the secondary impact of these procedures, we observe heterogeneity of the effect of these procedures on measures of fairness in calibration and ranking across experimental conditions. Beyond the reported trade-offs, we emphasize that analyses of algorithmic fairness in healthcare lack the contextual grounding and causal awareness necessary to reason about the mechanisms that lead to health disparities, as well as about the potential of algorithmic fairness methods to counteract those mechanisms. In light of these limitations, we encourage researchers building predictive models for clinical use to step outside the algorithmic fairness frame and engage critically with the broader sociotechnical context surrounding the use of machine learning in healthcare.