Foundational Issues Research Articles

Everyday life information seeking: A systematic review with bibliometric analysis

This study presents the first comprehensive systematic review and bibliometric analysis of the Everyday Life Information Seeking (ELIS) research domain, spanning nearly three decades of academic contributions. Initiated by Savolainen’s groundbreaking study in 1995, ELIS research has significantly progressed; however, to date, no researchers have undertaken a thorough overview of this field. Employing a mixed-methods approach, this study combines systematic review techniques with bibliometric analysis, aiming to bridge this gap. The methodology includes rigorous data filtration from the Web of Science and Scopus databases, amassing a total of 345 articles published between 1995 and 2023. Findings indicate a marked increase in ELIS publications and citations, particularly after 2008, underscoring a growing interest in everyday life information seeking. Analysis identified significant contributions from the United States, Canada, the United Kingdom, Finland, and Australia. Thematic analysis unveiled three main research directions: the influence of digital technology on ELIS, information seeking in health scenarios, and diverse information needs and sources among specific user groups. Furthermore this study also proposes an integrative framework, emphasizing the importance of understanding information-seeking behaviors within the complex and diverse context of everyday life. It recognizes the necessity of incorporating various sociocultural perspectives and adapting to the continuously evolving digital environment. This framework serves as a valuable resource for scholars and practitioners dedicated to improving information services and interventions in daily life. The limitations of this study include language and database restrictions, as well as the exclusion of gray literature. Additionally, given the significant potential of integrating information seeking with technology to improve daily life, future research should focus on the foundational theoretical issue of how artificial intelligence technology is reshaping users’ ELIS behaviors.

COVID-19 Modeling: A Review

The SARS-CoV-2 viruses and their triggered COVID-19 pandemic have fundamentally reshaped the world in almost every aspect, their evolution and influences remain. While over a million of literature have been produced on these unprecedented, overwhelming global disaster, one critical question is open: How has COVID-19 been quantified globally? This further inspires many other questions: What COVID-19 problems have been modeled? How have modeling methods in areas such as epidemiology, artificial intelligence (AI), data science, machine learning, deep learning, mathematics and social science played their roles in characterizing COVID-19? Where are the gaps and issues of these COVID-19 modeling studies? What are the lessons for quantifying future disasters? Answering these questions involves the analysis of a very broad spectrum of literature across different disciplines and domains. Distinguishing from specific efforts, this review takes the first attempt to generate a systematic, structured and contrastive landscape and taxonomy of global COVID-19 modeling. First, the surveyed problems span over a full range of COVID-19, including epidemic transmission processes, case identification and tracing, infection diagnosis and medical treatments, non-pharmaceutical interventions and their influence, drug and vaccine development, psychological, economic and social influence and impact, and misinformation, and so on. Second, the reviewed modeling methods traverse all relevant disciplines, from statistic modeling to epidemic modeling, medical analysis, biomedical analysis, AI, deep and machine learning, analytics, and simulation. Critical analyses further identify significant issues and gaps, for example, simple techniques and similar problems have been overwhelmingly addressed everywhere, while intrinsic and foundational issues and deep insights have been overlooked. The review discloses significant opportunities for more deeply, effectively and uniquely quantifying COVID-19-like global disasters from their intrinsic working mechanisms, interactions and dynamics.

Soluble Model of a Nonequilibrium Steady State: The Van Kampen Objection and Other Lessons.

A simple model of charge transport is provided by a classical particle in a random potential and a dissipative coupling to the environment. The corresponding nonequilibrium steady state (NESS) can be determined analytically when both the disorder and dissipation are weak. We use it to illuminate some foundational issues in nonequilibrium statistical mechanics. We show that at nonlinear level dissipative response sensitively depends on the system-environment coupling, and the range of validity of the linear response theory is set by this coupling. This validates the Van Kampen objection. We also show that the principle of minimum entropy production does not determine the NESS beyond linear order in the electric field, while entropy maximization fails to produce the correct NESS already at linear order.

Reasons and root causes: Conventional characterizations of doctoral engineering attrition obscure underlying structural issues

AbstractBackgroundAlthough most engineering graduate students are funded and usually complete their degrees faster than other disciplines, attrition remains a problem in engineering. Existing research has explored the psychological and sociological factors contributing to attrition but not the structural factors impacting attrition.Purpose/HypothesisUsing systems theory, this study seeks to understand nuance in how underlying structural causes affect engineering graduate students' attrition experiences in ways that may differ from their official reasons for departure.Design/MethodsData were collected through semi‐structured interviews with seven departing or already departed engineering doctoral students from R1 graduate programs across the United States. Using thematic analysis, root cause analyses were conducted to understand participants' attrition experiences to explore how structures influence causes of departure.ResultsThe ways participants discuss root causes of their departure indicate differences in formal reasons for departure and underlying causes of departure. We highlight the role of informal and formal policy as root causes of a different attrition rationale often passed off as interpersonal issues. When interpreted as evidence of structural issues, the causes of departure show ways in which action–inaction, policy–“null” policy serve as structural features governing student attrition decision processes. We also highlight a form of benign neglect toward struggling graduate students.ConclusionThis study reveals important nuances underlying face‐value reasons of attrition indicating foundational structural issues contributing to engineering graduate student attrition. Coaching faculty in team management and encouraging close revision of departmental policies could help mitigate students' negative graduate experiences and decrease unnecessary attrition.

On Optimality of Mallows Model Averaging*†

In the past decades, model averaging (MA) has attracted much attention as it has emerged as an alternative tool to the model selection (MS) statistical approach. Hansen (2007) introduced a Mallows model averaging (MMA) method with model weights selected by minimizing a Mallows’ C p criterion. The main theoretical justification for MMA is an asymptotic optimality (AOP), which states that the risk/loss of the resulting MA estimator is asymptotically equivalent to that of the best but infeasible averaged model. MMA’s AOP is proved in the literature by either constraining weights in a special discrete weight set or limiting the number of candidate models. In this work, it is first shown that under these restrictions, however, the optimal risk of MA becomes an unreachable target, and MMA may converge more slowly than MS. In this background, a foundational issue that has not been addressed is: When a suitably large set of candidate models is considered, and the model weights are not harmfully constrained, can the MMA estimator perform asymptotically as well as the optimal convex combination of the candidate models? We answer this question in both nested and non-nested settings. In the nested setting, we provide finite sample inequalities for the risk of MMA and show that without unnatural restrictions on the candidate models, MMA’s AOP holds in a general continuous weight set under certain mild conditions. In the non-nested setting, a sufficient condition and a negative result are established for the achievability of the optimal MA risk. Implications on minimax adaptivity are given as well. The results from simulations and real data analysis back up our theoretical findings.

Bibliographical foundations of information science: a review essay

PurposeThe narrow purpose of this article is to review de Fremery’s (2024) book about the bibliographic foundations of information science. The broader purpose is to consider the actual as well as the potential relevance of the field(s) of bibliography for information science besides the book under review.Design/methodology/approachThis review essay examines the arguments put forward by de Fremery (2024), introduces concepts and traditional lore from the study of bibliography and presents internal conflicts or paradigms in the field of bibliography. It relates this information to foundational issues in information science.FindingsDe Fremery’s basic ambition of basing information science in the field of bibliography is important, and so is the attempt to consider bibliography in relation to contemporary information technologies such as machine learning and data science. The book under review fails, however, to describe the relations between different positions in bibliography, such as enumerative, analytical, descriptive, critical and historical bibliography in relation to information science. It rather tends to make problematic claims, for example, that scientific experiments are based on bibliographical methods, and to describe the relation of bibliography to information science on the basis of such interpretations. Nonetheless, the book is a serious attempt to consider the field of bibliography and thereby support the focus on documents in information science.Originality/valueInformation science often suffers because of ambiguities in the concept of information. When information science is understood as the study of literature-based answering, much else falls into place. The field of bibliography is a core concept for this understanding and re-orientation of information science, for example, by establishing the core relation between bibliography, information searching and knowledge organization.

“These two worlds are antithetical”: epistemic tensions in integrating computational thinking in K12 humanities and arts

ABSTRACT Background While advocates for integrating Computational Thinking (CT) into existing K12 classrooms have acknowledged and aimed to address various barriers to implementation, we contend that a more foundational issue – tensions between the epistemology of computing and those of existing disciplines – has largely been overlooked. Studies of contact between heterogeneous disciplinary perspectives in both pedagogical and real world professional settings point to other risks, and harms, that educators may need to consider as they attempt to integrate CT into their teaching. As such, designing for integrated CT pedagogies does not simply require addressing functional problems such as teacher professional learning and limited classroom time, but rather implicates complex epistemological navigations. Objective This manuscript explores epistemic tensions between Computational Thinking (CT) and K12 humanities and arts disciplines and possibilities for their resolution. Method Based on a Delphi study with 43 experts from three disciplines – language arts, social studies, and arts – as they engaged in 20 hours of focus group conversations exploring potential approaches to integrating CT these disciplines, analysis focused on identifying perceived epistemic tensions that can arise in the context of instruction and directions for their resolution. Findings We found 5 epistemic tensions that are explored in detail: contextual reductionism, procedural reductionism, epistemic chauvinism, threats to epistemic identities, and epistemic convergence, as well as a number of potential directions for navigating them. Implications The study’s findings provide insights that bear on both scholarship and pedagogical design aimed at promoting substantive interdisciplinary learning with CT, and, critically, navigating potential tensions that can arise within it.

Development of Tax Avoidance Research in Asia through Bibliometric Analysis

This research employs a bibliometric analysis to investigate the development and trends in tax avoidance research, focusing specifically on the Asian context. Utilizing data from Google Scholar, the study covers literature published between 1938 and 2024. The analysis identifies key thematic clusters including corporate tax avoidance, international tax strategies, and legal frameworks, highlighting the evolution of research focus from foundational legal issues to complex multinational tax practices and ethical considerations. The study also uncovers underexplored areas such as the incentives driving tax avoidance behavior and the role of audit committees, presenting opportunities for future research. Furthermore, the author collaboration network reveals a landscape with significant yet underutilized potential for interdisciplinary cooperation. This comprehensive overview not only enhances understanding of the tax avoidance research landscape but also underscores the need for continued scholarly exploration and collaboration to address emerging challenges in the field.

The Jurisprudential (Fiqh) Opinions of Ibn Al-Fars Al-Andalusi (d. 597 AH) in His Book Ahkam Al-Quran [The Rulings of Quran]: The Capability to Perform Hajj as a Model

This research aims to conduct a comparative study of some Hajj-related issues pertaining to the capability to perform Hajj according to the Maliki scholar Ibn Al-Fars Al-Andalusi in his book "Ahkam Al-Quran [The Rulings of Quran]." This book is considered an encyclopedia in its field, encompassing numerous jurisprudential and foundational issues. Ibn Al-Fars presents valuable opinions in the book, aligning with the Maliki school of thought without blind adherence. The researcher chose to focus on the capability to perform Hajj due to its significance and the importance of the Hajj pilgrimage itself. The research falls into two sections: the first introduces Ibn Al-Far’s biography, and the second examines the issues of the capability to perform Hajj comparatively with other Islamic schools of thought. The researcher favors the strongest arguments and those closest to the contemporary context.

On the issue of the value foundations of nation-building in Russia (based on materials from the plenary session of the X All-Russian Conference “The Path to Science”)

On the issue of the value foundations of nation-building in Russia (based on materials from the plenary session of the X All-Russian Conference “The Path to Science”)

A human-centred approach to symbiotic AI: Questioning the ethical and conceptual foundation

This paper advocates for a constructivist approach to symbiosis to restore human-centredness in the governance of Symbiotic Artificial Intelligence (SAI). Challenging rigid, deterministic foundational methods warns against the risk of divorcing ethics from mere adherence to moral principles. Instead, it calls for a shift towards a distributed, contextual, relational, and dialectical structure to embody human-centredness. Through an analysis of the SAI landscape and its interplay between social and technological factors, the paper argues for a reconceptualisation of theoretical foundation and human responsibility within the socio-technical perspective. Chapter 2 delves into foundational issues of SAI, questioning the application of biological categories and proposing patterns of SAI based on definitions of intelligent life. Chapter 3 explores the potential of a constructivist approach, emphasising flexibility and context awareness, and presents a framework for understanding and evaluating SAI systems, components of an evolving methodology.

Shallow strategic thinking: findings from a multinational problem-based learning pilot study

PurposeResearchers piloted a problem-based learning (PBL) activity in a master’s degree-granting strategic studies program to explore how students apply knowledge and skills learned from the curriculum to their formulation of a strategy addressing a real-world global security scenario.Design/methodology/approachThis mixed-methods pilot study used ethnographic observation, participant feedback, document analysis and surveys to assess the learning and engagement of multinational postgraduate students in the context of a PBL environment.FindingsFindings revealed gaps in students’ causal logic and literacy, as well as student discomfort with ambiguity and reliance upon heuristic frameworks over willingness to conduct substantive, current and relevant research. Additionally, observed group dynamics represented a lack of inclusive collaboration in mixed gender and multinational teams. These findings suggest foundational issues with the curriculum, teaching methodologies and evaluation practices of the studied institution.Originality/valueThis study highlights the need to include explicit instruction in problem-solving and causal literacy (i.e. logical reasoning) in postgraduate programs for national and global security professionals, as well as authentic opportunities for those students to practice interpersonal communication.

Multihazard resilience and economic loss evaluation method for cable-stayed bridges under the combined effects of scour and earthquakes

Cable-stayed bridges (CSBs) commonly experience scour-induced foundation issues during their service life, impacting both structural seismic resilience and economic losses. Nonetheless, these aspects remain inadequately addressed in existing seismic codes. This paper presents a comprehensive probabilistic multihazard fragility, resilience, and economic loss evaluation method for CSBs influenced by scour and earthquakes. Numerical models with various scour depths considering epistemic uncertainties in loads, structural properties, and soil conditions are first established using the Latin-hypercube sampling (LHS) method. Incremental dynamic analyses (IDAs) are then conducted on these models in cases with near-fault and far-field bidirectional ground motions, yielding probabilistic multihazard demand models and component- and system-level multihazard fragility surfaces for diverse limit states. Subsequently, resilience and economic losses are comparatively evaluated by integrating damage probabilities with corresponding uncertain functional recovery functions. Eventually, a rapid bridge traffic capacity evaluation method based on the critical traffic capacity surface concept is devised to effectively assess CSB open patterns under various peak ground accelerations (PGAs), scour depths, and repair times. The numerical results show apparent shifts in the nonmonotonic seismic fragility, resilience, and economic loss of the case CSB due to scour effects, with the rates of change reaching 31.4 %, 34 %, and 24.8 %, respectively, associated with a critical scour depth of 12 m at IM = 0.8 g. The developed analysis framework provides a reference for the life-cycle design and maintenance of CSBs affected by multihazard scour and earthquakes.

Exploring ice Ic nucleation and structural relaxation in supercooled water

Despite intensive research efforts, understanding how water freezes remains an open and relevant question with profound implications. In this study, we examine ice Ic nucleation and water relaxation at the atomic level, employing molecular dynamics (MD) simulations and Classical Nucleation Theory (CNT). Our key findings address the following foundational issues: (i) Routes to cubic ice. Ice Ic seeding liquid water results in equal amounts of ice Ic and Ih structures at T<235K, while ice Ic predominates at T⩾235K along zero isobar. Moreover, ice produced from spontaneous nucleation at T=205-215K is more cubic compared with that grown on ice Ic seeds; (ii) CNT validity. Using MD-generated data, CNT accurately predicts ice nucleation rates without any fitting parameter, thereby bridging the gap between simulations and experiments; (iii) Kinetic crossroads. We determined a kinetic spinodal for high-density water as an intersection of relaxation and nucleation time curves at TKS=199K for a MD sample and TKS=233K for a macroscopic sample, which coincides with the experimental homogenous freezing limit; (iv) Kauzmann conundrum. Finally, we indicated that if the Kauzmann temperature exists, estimated as TK=190K, it might be inaccessible for high-density water due to the kinetic spinodal at a higher temperature, TKS>TK, thus resolving the long-standing entropy paradox. Overall, this research provides valuable insights into fundamental aspects related to water crystallization.

We must discuss research environments.

A major challenge facing the biomedical community is creating and sustaining high-quality research environments. A literature search identified five common themes underlying biomedical research environments comprising collaboration, data access, user-led innovation, data provenance and a deep commitment to public and scientific benefit. Club theory is used to develop a model describing social structures that underpin these themes. It is argued that collaboration underlies impactful science and that collaboration is hindered by high transaction costs. This, combined with poorly defined property rights surrounding publicly funded data, limits the ability of data markets to operate efficiently. Although the science community is best placed to provide solutions for these issues, incentivization by funding agencies to increase the benefits of collaboration and reduce uncoordinated activity will be an accelerator. Given the complexity of emerging datasets and the collaborations needed to exploit them, trust-by-design solutions are suggested. The underlying motivational 'glue' that holds this activity together is the aesthetic and ethical value base underlying good science. The model has implications for data-driven science more generally. As biomedical science in the Global South develops, there is an opportunity to address foundational structural issues prospectively rather than inherit unwanted constraints of current practice.

A link between static and dynamical perturbation theory

Dynamics, the physical change in time and a pillar of natural sciences, can be regarded as an emergent phenomenon when the system of interest is part of a larger, static one. This ‘relational approach to time’, in which the system’s environment provides a temporal reference, does not only provide insight into foundational issues of physics, but holds the potential for a deeper theoretical understanding as it intimately links statics and dynamics. Reinforcing the significance of this connection, we demonstrate, based on recent progress (Gemsheim and Rost 2023 Phys. Rev. Lett. 131 140202), the role of emergent time as a vital link between time-independent and time-dependent perturbation theory in quantum mechanics. We calculate first order contributions, which are often the most significant, and discuss the issue of degenerate spectra. Based on our results, we envision future applications for the calculation of dynamical phenomena based on a single pure energy eigenstate.

Data Equity as a Building Block for Health Equity: Improving Surveillance Data for People With Disabilities, With Substance Use Disorder, or Experiencing Homelessness, United States.

People with disabilities, people experiencing homelessness, and people who have substance use disorders face unique health challenges. Gaps in public health surveillance data limit the identification of public health needs of these groups and data-driven action. This study aimed to identify current practices, challenges, and opportunities for collecting and reporting COVID-19 surveillance data for these populations. We used a rapid qualitative assessment to explore COVID-19 surveillance capacities. From July through October 2021, we virtually interviewed key informants from the Centers for Disease Control and Prevention, state and local health departments, and health care providers across the United States. We thematically analyzed and contextualized interview notes, peer-reviewed articles, and participant documents using a literature review. We identified themes centered on foundational structural and systems issues that hinder actionable surveillance data for these and other populations that are disproportionately affected by multiple health conditions. Qualitative data analysis of 61 interviews elucidated 4 primary challenges: definitions and policies, resources, data systems, and articulation of the purpose of data collection to these groups. Participants noted the use of multisector partnerships, automated data collection and integration, and data scorecards to circumvent challenges. This study highlights the need for multisector, systematic improvements in surveillance data collection and reporting to advance health equity. Improvements must be buttressed with adequate investment in data infrastructure and promoted through clear communication of how data are used to protect health.

Philosophy of cognitive science in the age of deep learning.

Deep learning has enabled major advances across most areas of artificial intelligence research. This remarkable progress extends beyond mere engineering achievements and holds significant relevance for the philosophy of cognitive science. Deep neural networks have made significant strides in overcoming the limitations of older connectionist models that once occupied the center stage of philosophical debates about cognition. This development is directly relevant to long-standing theoretical debates in the philosophy of cognitive science. Furthermore, ongoing methodological challenges related to the comparative evaluation of deep neural networks stand to benefit greatly from interdisciplinary collaboration with philosophy and cognitive science. The time is ripe for philosophers to explore foundational issues related to deep learning and cognition; this perspective paper surveys key areas where their contributions can be especially fruitful. This article is categorized under: Philosophy > Artificial Intelligence Computer Science and Robotics > Machine Learning.

Foundational Issues in Group Field Theory

In this paper I offer an introduction to group field theory (GFT) and to some of the issues affecting the foundations of this approach to quantum gravity. I first introduce covariant GFT as the theory that one obtains by interpreting the amplitudes of certain spin foam models as Feynman amplitudes in a perturbative expansion. However, I argue that it is unclear that this definition of GFTs amounts to something beyond a computational rule for finding these transition amplitudes and that GFT doesn’t seem able to offer any new insight into the foundations of quantum gravity. Then, I move to another formulation of GFT which I call canonical GFT and which uses the standard structures of quantum mechanics. This formulation is of extended use in cosmological applications of GFT, but I argue that it is only heuristically connected with the covariant version and spin foam models. Moreover, I argue that this approach is affected by a version of the problem of time which raises worries about its viability. Therefore, I conclude that there are serious concerns about the justification and interpretation of GFT in either version of it.

The equivalence of Axiom (∗)+ and Axiom (∗)++

Asperó and Schindler have completely solved the Axiom [Formula: see text] vs. [Formula: see text] problem. They have proved that if [Formula: see text] holds then Axiom [Formula: see text] holds, with no additional assumptions. The key question now concerns the relationship between [Formula: see text] and Axiom [Formula: see text]. This is because the foundational issues raised by the problem of Axiom [Formula: see text] vs. [Formula: see text] arguably persist in the problem of Axiom [Formula: see text] vs. [Formula: see text]. The first of our two main theorems is that Axiom [Formula: see text] is equivalent to Axiom [Formula: see text], and as a corollary we show that Axiom [Formula: see text] fails in all the known models of [Formula: see text]. This suggests that [Formula: see text] actually refutes Axiom [Formula: see text]. Our second main theorem is that the [Formula: see text] Conjecture holds assuming [Formula: see text]. This is the strongest partial result known on this conjecture which is one of the central open problems of [Formula: see text]-theory and [Formula: see text]-logic. These results identify a fundamental asymmetry between the Continuum Hypothesis and any axiom which is both [Formula: see text]-expressible and which implies [Formula: see text], on the basis of generic absoluteness for the simplest of the nontrivial sentences of Third-Order Number Theory. These are the [Formula: see text]-sentences with no parameters. Such sentences are those which simply assert the existence of a set [Formula: see text] for which some property involving only quantification over [Formula: see text] holds.