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This paper explores the reader-oriented approaches to literary theory through the perspectives of Norman Holland and Wolfgang Iser, focusing on their theories of reader-text interaction. Holland, drawing from psychoanalytic theory, emphasizes the role of the reader's unconscious mind and psychological experiences in shaping the reading process. Through his transactive theory, he argues that readers project their identity issues onto the text, influencing their interpretations. Iser, on the other hand, adopts a phenomenological approach, highlighting the reader's active engagement with the text and the interplay between their expectations and the text's structures. His concepts, such as the implied reader and the wandering viewpoint, underscore the dynamic nature of meaning-making during reading. Despite their differences, both theorists challenge text-oriented approaches, emphasizing the vital role of the reader in creating meaning. This comparative analysis aims at enriching the understanding of reader-oriented literary theory and underscores the complexity of reader-text interaction in the process of interpretation. [ABSTRACT FROM AUTHOR]

The rising university enrollment rate and the growing number of types of university admission examinations have allowed students who lack fundamental knowledge to enter universities in Japan. Providing students with the necessary knowledge to continue studying at universities is referred to as remedial education. Remedial student motivation is among the most frequently studied topics in this field. This study examined Japanese remedial students’ motivational development in English classes using complex dynamic systems theory. Fifteen Japanese university freshmen participated in the study for one year, for a total of 20 sessions. Data were collected from weekly questionnaires, semi-structured retrospective interviews, teaching journals, and classroom observations. The data were analyzed using retrodictive qualitative modelling procedures and change-point analyses. After discerning the eight motivational patterns, they were categorized into three groups. Examination of each group’s cases suggested a hypothetical motivational developmental path for remedial students. This path had some similarities to another motivational developmental path hypothesized in a previous study [ABSTRACT FROM AUTHOR]

The article discusses the importance of foresight and future thinking for evaluators in the wake of the pandemic. It emphasizes the need for evaluators to anticipate and prepare for unexpected events and to develop nimble, forward-thinking designs for interventions. The article also highlights the emerging field of foresight evaluation and the potential for collaboration between evaluators and foresight practitioners. It provides examples of evaluations of foresight initiatives and the use of foresight methods in evaluation. The article concludes by suggesting the need for bridge-building between the disciplines of evaluation and foresight to support the development of new and innovative practices. [Extracted from the article]

This article discusses the challenges and complexities associated with managing mega infrastructure projects. These projects, such as transportation systems and sports complexes, have significant impacts on political, economic, social, and environmental aspects of a nation or region. The article highlights the need for specialized management theories tailored to the unique characteristics of mega infrastructure projects. The special issue of the journal focuses on three main aspects: management methods, sustainability and environmental protection, and organizational behavior and strategies. The research presented in the special issue provides valuable insights and guidance for the management of mega infrastructure projects. [Extracted from the article]

Zero knowledge plays a central role in cryptography and complexity. The seminal work of Ben-Or et al. (STOC 1988) shows that zero knowledge can be achieved unconditionally for any language in NEXP, as long as one is willing to make a suitable physical assumption: if the provers are spatially isolated, then they can be assumed to be playing independent strategies. Quantum mechanics, however, tells us that this assumption is unrealistic, because spatially-isolated provers could share a quantum entangled state and realize a non-local correlated strategy. The MIP* model captures this setting. In this work, we study the following question: Does spatial isolation still suffice to unconditionally achieve zero knowledge even in the presence of quantum entanglement? We answer this question in the affirmative: we prove that every language in NEXP has a 2-prover zero knowledge interactive proof that is sound against entangled provers; that is, NEXP ⊆ ZK-MIP*. Our proof consists of constructing a zero knowledge interactive probabilistically checkable proof with a strong algebraic structure, and then lifting it to the MIP* model. This lifting relies on a new framework that builds on recent advances in low-degree testing against entangled strategies, and clearly separates classical and quantum tools. Our main technical contribution is the development of new algebraic techniques for obtaining unconditional zero knowledge; this includes a zero knowledge variant of the celebrated sumcheck protocol, a key building block in many probabilistic proof systems. A core component of our sumcheck protocol is a new algebraic commitment scheme, whose analysis relies on algebraic complexity theory. [ABSTRACT FROM AUTHOR]

Background: This research delves into the complexity management of collaborative networks and interorganizational systems in the health innovation ecosystem on the basis of a best practice in the coronavirus disease 2019 (COVID-19) crisis. The objective is to offer specific solutions and guidelines to stakeholders in the health innovation ecosystem to control the chaos resulting from unexpected events along the ecosystem development and evolution path. Methods: For this purpose, the performance of the Health Innovation Ecosystem in Iran (the Every Home is a Health Base plan) has been examined through a detailed and in-depth analysis of events and actions taken using documents, reports and interviews with experts. The practical application of chaos and complex adaptive system features (adaptation, time horizons, edge of chaos, sensitivity to initial conditions, state space and strange attractors) is introduced to identify and manage the transition from a state where the health innovation ecosystem is on the edge of chaos and prone to failure. Data were collected through studying documents, reports and interviews with experts, and then analysed using qualitative content analysis techniques, open and axial coding and metaphors derived from complexity and chaos theories. Results: The findings indicate that to understand and embrace the complexity of the health innovation ecosystem throughout its development and evolution and manage and lead it through the edge of chaos towards successful interorganizational systems performance, it is necessary to use gap analysis to achieve consensus, establish a highly interactive governance structure with key stakeholders of the ecosystem, maintain flexibility to control bifurcations (butterfly effect), prevent transforming emergency solutions into standard routines and ensure the sustainability of the ecosystem against future threats by long-term financial security. Conclusions: This research provides insights into the dynamics of complex health systems and offers strategies for promoting successful innovation through collaborative networks and interorganizational systems in the development and evolution of the health innovation ecosystem. By embracing complexity and chaos, healthcare professionals, policy-makers and researchers can collaboratively address complex challenges and improve outcomes in health network activities. The conclusion section provides guidelines for successfully managing the complexity of the ecosystem and offers suggestions for further research. [ABSTRACT FROM AUTHOR]

A new era of lunar exploration has begun with participation of all major space agencies. This activity brings opportunities for revolutionary science experiments and observatories on the Moon. The idea of a lunar gravitational-wave detector was already proposed during the Apollo programme. The key characteristic of the Moon is that it is seismically extremely quiet. It was also pointed out that the permanently shadowed regions at the lunar poles provide ideal conditions for gravitational-wave detection. In recent years, three different detector concepts were proposed with varying levels of technological complexity and science potential. In this paper, we confront the three concepts in terms of their observational capabilities based on a first more detailed modelling of instrumental noise. We identify important technological challenges and potential show-stoppers. This article is part of a discussion meeting issue 'Astronomy from the Moon: the next decades (part 2)'. [ABSTRACT FROM AUTHOR]

The current recommended developmental Bobath practice within the Bobath Clinical Reasoning Framework (BCRF) can be conceptualized using the lens of systems science, thereby providing a holistic perspective on the interrelatedness and interconnectedness of the variables associated with childhood‐onset disability. The BCRF is defined as an in‐depth clinical reasoning framework that can be applied to help understand the relationships between the domains of the International Classification of Functioning, Disability and Health, how those domains can be influenced, and how they impact each other. The BCRF is a transdisciplinary observational system and practical reasoning approach that results in an intervention plan. This provides a holistic understanding of the complexity of situations associated with disorders such as cerebral palsy (CP) and the basis for the lifelong management and habilitation of people living with neurological disorders. The clinical reasoning used by the BCRF draws on the important contextual factors of the individual and their social environment, primarily the family unit. It is rooted in an understanding of the interrelationships between typical and atypical development, pathophysiology (sensorimotor, cognitive, behavioural), and neuroscience, and the impact of these body structure and function constructs on activity and participation. The systems science model integral to the BCRF is a useful way forward in understanding and responding to the complexity of CP, the overarching goal being to optimize the lived experience of any individual in any context. [ABSTRACT FROM AUTHOR]

Never has the domain of sports coaching been so inundated with secondary information. In high-performance contexts, for example, coaches are routinely presented with detailed reports specifying features about an athlete's or team's performance. Here, we question whether such detailed secondary information has led us to know too much, obscuring what the world has to share directly with us. To over-rely on secondary information is to narrow in on certainty, on cause-effects that are oft-espoused through de-contextualised 'performance' tests and metrics. This indirect approach eschews opening up to uncertainty, to ongoing inquiry embedded in primary experience. For where certainty risks closures, uncertainty opens to the possibility of carrying on with and alongside others. We explore this thesis through the reflections of an Olympic Canoe Slalom coach, meandering through three sections: (i) on paying attention; (ii) on knowing better; (iii) on guidance without specification. In presenting this thesis, we hope to encourage others - in sports coaching and beyond - to embrace an ethos of not-knowing, opening up to the 'goings on' of what interests them, actively attending and directly responding with genuine care and curiosity. Indeed, while embracing an ethos of not-knowing can be unsettling, vulnerably exposing oneself to changing power relations in a world perpetually on the move, it can facilitate primary experience of the surrounding ecology. The accompanying growth of responsiveness to one's surroundings emerges from listening to what it has share, joining in conversation to find ways of carrying on. It is in this responsiveness, we contend, that a wisdom can be found; a wisdom of not-knowing. [ABSTRACT FROM AUTHOR]

Summary: Despite evidence for the effectiveness of policies that target obesogenic environments, their adoption remains deficient. Using methods and concepts from complexity and political science (Stock‐and‐Flow analysis and Punctuated Equilibrium Theory) and a qualitative literature review, we developed system maps to identify feedback loops that hinder policymaking on mitigating obesogenic environments and feedback loops that could trigger and sustain policy change. We found numerous self‐reinforcing feedback loops that buttress the assumption that obesity is an individual problem, strengthening the biomedical and commercial weight‐loss sectors' claim to "ownership" over solutions. That is, improvements in therapies for individuals with obesity reinforces policymakers' reluctance to target obesogenic environments. Random events that focus attention on obesity (e.g., celebrities dismissing soda) could disrupt this cycle, when actors from outside the medical and weight‐loss sector (e.g., anti‐weight stigma activists) successfully reframe obesity as a societal problem, which requires robust and politically relevant engagement with affected communities prior to such events taking place. Sustained prioritization of policies targeting obesogenic environments requires shared problem ownership of affected communities and nonhealth government sectors, by emphasizing cobenefits of policies that target obesogenic environments (e.g., ultraprocessed food taxation for raising revenue) and solutions that are meaningful for affected communities. [ABSTRACT FROM AUTHOR]

The geographical concepts of scale, space and place have informed and refined the theory of "framing" in the social movement literature. Going beyond the conventional approach of understanding social movements, this article aims to bring discussions on relational ontology into conversation with the geographical literature on scale and spatial strategies in social movements, proposing a theoretical framework that goes beyond established approaches in the literature on collective action framing. This article proposes for a holistic cross‐disciplinary dialog among political and development geographers and with activists and scholars from other cognate disciplines of social science to understand the complexities of framing in social movements. [ABSTRACT FROM AUTHOR]

As urbanization accelerates, cities become more complex, coming along with more complex urban issues. Agent‐based model (ABM) is a traditional method to simulate activities in a complex system, which has been widely applied in urban studies. However, due to its rigid initial settings, ABM has been criticized for its lack of intelligence, especially in dealing with modern urban issues. With the success of artificial intelligence (AI) and complexity science, it is generally agreed that ABM can be enhanced with AI agents, a promising technology that can bridge the gaps. For that, this article provides a systematic review, in which 10 subsections correspond to 10 different ways that AI can work with ABM in the methodological framework. The sections include that (1) ABM is Al; (2) ABM provides training data for Al; (3) Al provides data for ABM; (4) ABM is a submodule in the ensemble Al; (5) Al leads an optimization framework with ABM participation; (6) Al tunes ABM initialization parameters; (7) Al provides the environment for ABM; (8) Al aids in choosing the agent's attributes; (9) Al provides behaviors for agents in ABM; (10) Al helps to evaluate the performance of ABM. For each case, some typical works are examined for illustration. Finally, we discuss some of the current limitations and prospects for future development. [ABSTRACT FROM AUTHOR]

In a spirit of collegial support, this paper argues that Beckett and Hager's theoretical justification and empirical exemplifications do not do full justice to the complexity of group or team learning. We firstly reaffirm our support for the theoretical argument Becket and Hager make, though expressing some reservations about Complexity Theory, to explain the taken-for-granted assumptions that learning by an individual is the paradigm case of learning and that context plays a minimal role in this process. Drawing on our joint and separate work, we demonstrate that Becket and Hager's argument is less radical than it may initially seem because it is predicated on: (i) cognitive-bounded rather than "distributed" or "extended" conception of mind; (ii) material rather than a "immaterial" conception of activity; and (iii) co-present rather than a "fractional" or "connective" conception of ontology. Despite making this critique, we conclude by making the case that we are adding further substance to Becket and Hager's overarching argument and, in doing so, encouraging them to be more radical about how they conceptualise the complexity of learning. [ABSTRACT FROM AUTHOR]

In the post-Apartheid era South Africa's universities have faced serious questions about the quality of their student learning in the face of near impossible challenges. The University of Cape Town, widely seen as the country's leading higher education institution, has shown remarkable resilience, however, in the range of initiatives it has launched to support and enhance student learning. These initiatives, designed with a common purpose, are of course intended to work together so that their effects might be compounded and realized in enhanced student learning outcomes. Drawing substantially on the power of compounding (which is itself redolent of the claim made by complexity theory that relations and emergence are crucial concepts), complexity theory offers unique insights into how and why things change – and also into how and why things remain largely the same or inexorably grind towards failure. The networked initiatives undertaken by the University of Cape Town constitute a case of learning refurbishment that is also well explained and understood in terms of complexity theory. This paper draws on concepts from complexity theory both to understand how learning might be enhanced in higher education institutions in severely straitened circumstances and to offer insights for education leaders and policy-makers in this domain. [ABSTRACT FROM AUTHOR]

Complex spatiotemporal patterns in nature significantly challenge reductionism-based modern science. The lack of a paradigm beyond reductionism hinders our understanding of the emergence of complexity. The diversity of countless patterns undermines any notion of universal mechanisms. Here, however, we show that breaking the symmetry of three simple and self-organization rules gives rise to nearly all patterns in nature, such as a wide variety of Turing patterns, fractals, spiral, target and plane waves, as well as chaotic patterns. The symmetry breaking is rooted in the basic physical quantities, such as positive and negative forces, space, time and bounds. Besides reproducing the hallmarks of complexity, we discover some novel phenomena, such as abrupt percolation of Turing patterns, phase transition between fractals and chaos, chaotic edge in traveling waves, etc. Our asymmetric self-organization theory established a simple and unified framework for the origin of complexity in all fields, and unveiled a deep relationship between the first principles of physics and the complex world. [ABSTRACT FROM AUTHOR]

The concept of complexity has become pivotal in multiple disciplines, including quantum information, where it serves as an alternative metric for gauging the chaotic evolution of a quantum state. This paper focuses on Krylov complexity, a specialized form of quantum complexity that offers an unambiguous and intrinsically meaningful assessment of the spread of a quantum state over all possible orthogonal bases. This study is situated in the context of Gaussian quantum states, which are fundamental to both Bosonic and Fermionic systems and can be fully described by a covariance matrix. While the covariance matrix is essential, it is insufficient alone for calculating Krylov complexity due to its lack of relative phase information is shown. The relative covariance matrix can provide an upper bound for Krylov complexity for Gaussian quantum states is suggested. The implications of Krylov complexity for theories proposing complexity as a candidate for holographic duality by computing Krylov complexity for the thermofield double States (TFD) and Dirac field are also explored. [ABSTRACT FROM AUTHOR]

Interdisciplinary communication and collaboration are crucial in the care of people with multiple long-term conditions (MLTCs) yet are often experienced as insufficient. Through the lens of complexity science, this study aims to explain how healthcare professionals (HCPs) adapt to emerging situations in the care of patients with MLTC by examining interdisciplinary communication and collaboration in the outpatient hospital setting. We used the constant comparative method to analyze transcribed data from seven focus groups with twenty-one HCPs to generate a constructivist grounded theory of 'interdisciplinary communication and collaboration in the outpatient setting of the hospital for patients with multiple long-term conditions'. Our theory elucidates the various pathways of communication and collaboration. Why, when, and how team members choose to collaborate influences if and to what degree tailored care is achieved. There is great variability and unpredictability to this process due to internalized rules, such as beliefs on the appropriateness to deviate from guidelines, and the presence of an interprofessional identity. We identified organizational structures that influence the dynamics of the care team such as the availability of time and financial compensation for collaboration. As we strive for tailored care for patients with MLTC, our theory provides promising avenues for future endeavors. [ABSTRACT FROM AUTHOR]

There have been increasing calls for a paradigm shift in urban water management to a water sensitive cities (WSC) approach. Although it is well recognised that development of water sensitive communities is key to sustainable urban water transitions, there is no established definition for the "water sensitive community." This study conducts a systematic review to understand how water sensitive communities are characterised in the literature and applies a complex adaptive systems perspective to the findings. The review identifies 16 attributes that define water sensitive communities, involving elements of participation, collaboration, liveability, shared ownership and responsibility in transition processes, and resilience. We add to this by linking WSC research with complex adaptive systems theory and propose a new definition of the water sensitive community as a complex adaptive system. This presents a realistic framework in which to study the complex interactions and dynamic aspects of a water sensitive community. [ABSTRACT FROM AUTHOR]

There is a contemporary trend to apply the General Theory of Modal Aspects developed by Herman Dooyeweerd to different areas of knowledge. However, such uses do not always pay attention to the complexities of the theory, especially its empirical-transcendental nature and its broader framework in the Philosophy of the Cosmonomic Idea. This article is the outcome of qualitative bibliographic research with a basic, descriptive, and explanatory nature.The research adopted a survey of bibliographic data as its data collection instrument.The article seeks to demonstrate that the strictly methodological applications of the General Theory of Modal Aspects are limited for the following reasons: (1) terms such as ‘ontology’, ‘transcendental’ and ‘law’ are used without further clarification; (2) the ontic nature of modal aspects, of being meaning, permeates traditional ways of dividing philosophy into subdisciplines; (3) Dooyeweerd's ideas have a high degree of complexity in themselves; and (4) the idea of totality has a double connotation: one temporal (as cosmic coherence), the other as supratemporality. To this end, we have organized the article into four sections. In section 1 we briefly present the applications of the General Theory of Modal Aspects, specifically the work developed in Brazil in the fields of Education and Philosophy of Science. In section 2, we present some principles and assumptions of Dooyeweerd's thought and situate his General Theory of Modal Aspects within the Philosophy of the Cosmonomic Idea. In section 3 we discuss the idea of reality ordered by laws. In the last section, we highlight the boundaries of the methodological approach of this article in relation to the author's broader religious horizon of thought. We conclude by showing that Dooyeweerd's work contains an empirical-transcendental dimension, which concerns a priori totalities that structure reality and can only be known and affirmed through experience. [ABSTRACT FROM AUTHOR]

The Geography Textbook is an important support tool in the teaching learning process and is always present in the classroom, being indispensable at different times. It is in this sense that proposing an approach to the textbook based on the assumptions of the complexity theory, it is understood, could significantly favor the comprehension of a linked, connected and also uncertain geographic space, but of which we are part and that we can transforme. Therefore, the general objective of this work is to consider the arrangement of curriculum content in Geography textbooks on sustainability. The discussion will be based on bibliographical surveys and the analysis of a collection approved by the PNLD for the period from 2020 to 2023, from the 6th to the 9th year. The analysis of geography textbooks found that the contents are still presented in a fragmented and often incipient way. Based on the data obtained, we debate the need to formulate works that rely on complexity theory and its dialogical, hologrammatic and recursive aspects. [ABSTRACT FROM AUTHOR]

The present paper provides a historical context for chaos theory, originating in the 1960s with Edward Norton Lorenz's efforts to predict weather patterns. It introduces chaos theory, fractal geometry, nonlinear dynamics, and the butterfly effect, highlighting their exploration of complex systems. The authors aim to bridge the gap between chaos theory and oral and maxillofacial surgery (OMFS) through a literature review, exploring its applications and emphasizing the prevention of minor deviations in OMFS to avoid significant consequences. A comprehensive literature review was conducted on PubMed, Web of Science, and Google Scholar databases. The selection process adhered to the PRISMA-ScR guidelines and Leiden Manifesto principles. Articles focusing on chaos theory principles in health sciences, published in the last two decades, were included. The review encompassed 37 articles after screening 386 works. It revealed applications in outcome variation, surgical planning, simulations, decision-making, and emerging technologies. Potential applications include predicting infections, malignancies, dental fractures, and improving decision-making through disease prediction systems. Emerging technologies, despite criticisms, indicate advancements in AI integration, contributing to enhanced diagnostic accuracy and personalized treatment strategies. Chaos theory, a distinct scientific framework, holds potential to revolutionize OMFS. Its integration with advanced techniques promises personalized, less traumatic surgeries and improved patient care. The interdisciplinary synergy of chaos theory and emerging technologies presents a future in which OMFS practices become more efficient, less traumatic, and achieve a level of precision never seen before. [ABSTRACT FROM AUTHOR]

In applied linguistics, there has been a growing body of L2 pragmatics studies that investigate the intricate relationship between language learners' subjective pragmatic choices and various contextual factors. The current study contributes to the understanding of language learner agency by illustrating the complex processes through which language learners enact their agency in response to varying contextual factors when making their sociopragmatic interpretations and strategies. To capture the ecological nature of agency, this study conceptualizes agency as contextually, interpersonally, intrapersonally, spatially, and temporally embedded. Through the in-depth examination of the accounts of three L2 learners of Japanese regarding their interactions with religious group members during their study abroad in Japan, this study demonstrates language learners' divergent ways of enacting their agency, stemming from their orientations to the unique configurations of various contextual attributes in the L2 interactions. Such differences were rooted in and guided by their past experiences, present environments, and future aspirations that impacted their sociopragmatic perceptions, expectations, and choices. This study provides a complicated picture of language learner agency as a dialogic and reflexive process in which learners interact with contextual factors and adapt their sociopragmatic choices. Thus, it calls for an ecological, processual, and holistic approach to language learner agency through the close examination of the ways in which various contextual factors come together in L2 interactions, the process of how language learners orient to dynamic configurations of contextual factors, and what guides such orientations. [ABSTRACT FROM AUTHOR]

Although the theoretical–methodological complexity theory and transdisciplinary approach is increasingly accepted within sustainability science, its application at local-scale work with rural communities in the global south is still incipient and requires further research on its scope and limitations. The general objective of this work was to contribute to the knowledge on how a complexity and transdisciplinary approach applied to water problems at local scales can facilitate the process for water sustainability. The research took as study area the ejido of Coro Grande located in the municipality of Morelia, in the rural vicinity of Morelia City, capital of Michoacán State (Mexico). The theoretical–methodological scheme was based on the combination of the concepts of complexity–sustainability–transdisciplinarity to analyze the local water metabolism and generate actions to mitigate present and future water risk. The activities carried out involved a participatory diagnosis and the development of activities for the restoration of degraded environments with a double purpose: to generate conditions for the water sustainability of the system, and to promote the involvement of the population in a transdisciplinary research–action process. The results obtained show the effectiveness of the framework chosen to identify problems, achieve transformation in the short term, and improve both ecosystem functions and participation of the population in the solution of problems in the medium and long terms. [ABSTRACT FROM AUTHOR]

Copyright of Lua Nova is the property of CEDEC and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Cuadernos del Centro de Estudios de Diseño y Comunicación is the property of Cuadernos del Centro de Estudios de Diseno y Comunicacion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Cuadernos del Centro de Estudios de Diseño y Comunicación is the property of Cuadernos del Centro de Estudios de Diseno y Comunicacion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Cuadernos del Centro de Estudios de Diseño y Comunicación is the property of Cuadernos del Centro de Estudios de Diseno y Comunicacion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Through analysis and discussion of basic systemic properties of a rural municipality, this paper explores how aggregating data in planning and land use modeling can potentially obscure intricate real-world behavior. Complexity theory is applied as a theoretical framework for explaining this hypothesis. Thus, the aim of this study is to address the author's desire to understand systemic complexity when designing a data-driven decision-making model for rural planning. The novelty of this approach is two-fold: one, most studies on scalability issues in planning addresses spatial complexity, more so than systemic complexity within the complex system that the very act of planning strives to dictate. Two, although delimited to the scope of the study, the accessibility to and use of complete and valid socio-demographic data enables a rarely demonstrated accurate representation of an entire population. It is ultimately observed that on the disaggregated municipal level, systemic dispersion increases parallelly with population size, a correlation that is significantly influenced by gender ratio in any given parish – a characteristic that was not visible at the aggregated municipal level. In addition to advancing the understanding and placement of complexity science within spatial data science, these insights will make it easier to assess the generalizability of any given administrative unit by quantifying basic complexity attributes; in this case based on the correlation dispersion caused by the fragmentation of a municipality into its comprising parishes. [ABSTRACT FROM AUTHOR]

Purpose: Organizations will be key to realizing the "transformative change for humanity" now being called for. However, the complexity calls for new ways of facilitating change and organizational learning; it also calls for moving beyond sustainability to develop practices that restore and regenerate the world in which we live. Above all, it calls for the development of new frameworks, practices, mindset and capabilities to hold space for and facilitate such transformation, to dance with the "Logic of Life." The purpose of this study is to contribute to advancing the current leading frameworks and practices of facilitating learning and development towards the enabling of regenerative transformative change in organizations and society. Design/methodology/approach: This study is based on an exploratory qualitative analysis of a facilitation prototype that expands the current framework and practice of Appreciative Inquiry Summits toward regeneration. Findings: This study presents four paradoxes of regenerative facilitation to guide the dance for life in complex ecosystems. It also identifies that the dance needs to be widened, towards inviting more frequently the ends of the four paradoxes noted as regenerative, negative emotions, inner and more-than-human. Originality/value: This study explores the intersection of practices and frameworks for facilitating complexity with principles from regenerative leadership and complexity theory, potentially making an important contribution to the urgent and widespread need to facilitate a regenerative transformative change for humanity, society and our organizations. [ABSTRACT FROM AUTHOR]

International institutions strive to achieve their own objectives while operating within a complex network of interdependencies. These interdependencies create an extensive web of relationships that serve as potential pathways for broader institutional impacts. The actions taken by individual institutions, their mutual influences, and the pattern of connectivity collectively shape the overall performance of institutional complexes. Understanding the performance of these complexes is crucial, yet we currently lack a methodology to assess it. To address this gap, we have developed a conceptual framework that integrates three distinct areas of study on three different scales: institutional effectiveness, institutional interlinkages, and institutional networks. This framework enables us to consider what we call the latent net effectiveness, or collective problem-solving potential, of a group of interconnected institutions. To put this framework into practice, we have devised a heuristic model, drawing from the extensive literature on international environmental institutions. As an illustrative example, we have applied this model to a network of 378 multilateral environmental agreements with 810 known issue linkages. Our work underscores the relevance of considering the system-level properties of institutional complexes and emphasizes the need for timely network-based governance and policy interventions to enhance the overall effectiveness of institutional complexes. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

In this paper, we experimentally evaluate the zero-shot performance of GPT-4 against prior generations of GPT on the entire uniform bar examination (UBE), including not only the multiple-choice multistate bar examination (MBE), but also the open-ended multistate essay exam (MEE) and multistate performance test (MPT) components. On the MBE, GPT-4 significantly outperforms both human test-takers and prior models, demonstrating a 26% increase over ChatGPT and beating humans in five of seven subject areas. On the MEE and MPT, which have not previously been evaluated by scholars, GPT-4 scores an average of 4.2/6.0 when compared with much lower scores for ChatGPT. Graded across the UBE components, in the manner in which a human test-taker would be, GPT-4 scores approximately 297 points, significantly in excess of the passing threshold for all UBE jurisdictions. These findings document not just the rapid and remarkable advance of large language model performance generally, but also the potential for such models to support the delivery of legal services in society. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

This article explores the application of complexity science to the study of legal systems. It discusses how legal systems can be analyzed using complexity science methods and highlights the shift towards empirical research using computational tools. The article also provides a summary of articles in a special issue that apply complexity science to various aspects of legal systems. Additionally, the article discusses the intersection between artificial intelligence (AI) and the legal field, covering topics such as measuring innovation in legal language, the abilities of AI models to apply tax law, and the potential of AI to reduce disputes in litigation. The authors provide insights into the capabilities and limitations of AI in the legal profession, emphasizing the need for caution and ethical considerations. [Extracted from the article]

Litigation is a creature of disagreement. Our essay explores the potential of artificial intelligence (AI) to help reduce legal disagreements. In any litigation, parties disagree over the facts, the law, or how the law applies to the facts. The source of the parties' disagreements matters. It may determine the extent to which AI can help resolve their disputes. AI is helpful in clarifying the parties' misunderstanding over how well-defined questions of law apply to their facts. But AI may be less helpful when parties disagree on questions of fact where the prevailing facts dictate the legal outcome. The private nature of information underlying these factual disagreements typically fall outside the strengths of AI's computational leverage over publicly available data. A further complication: parties may disagree about which rule should govern the dispute, which can arise irrespective of whether they agree or disagree over questions of facts. Accordingly, while AI can provide clarity over legal precedent, it often may be insufficient to provide clarity over legal disputes. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

Law is a critical tool that humans have created to assist them in managing complex social interactions. Computational Law holds the potential to significantly enhance our capacity to express and manage legal complexity, and a number of advantages can result from restating public and private legal rules in computable form. Capturing that potential depends in part on the approaches taken to automation. One set of choices involves whether to translate directly into code from existing natural language statements of laws, regulations and contracts or whether to step back, envision the basic structure underlying those statements and build a software approach that reflects that structure in a code-native manner. We argue that many advantages can flow from the second approach, and we present a specific use case of a simplified insurance policy as an example of this approach. Large language models may assist in this process, but are not yet a replacement for a code-native utility. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

We apply network science principles to analyse the coalitions formed by European Union nations and institutions during litigation proceedings at the European Court of Justice. By constructing Friends and Foes networks, we explore their characteristics and dynamics through the application of cluster detection, motif analysis and duplex analysis. Our findings demonstrate that the Friends and Foes networks exhibit disassortative behaviour, highlighting the inclination of nodes to connect with dissimilar nodes. Furthermore, there is a correlation among centrality measures, indicating that member states and institutions with a larger number of connections play a prominent role in bridging the network. An examination of the modularity of the networks reveals that coalitions tend to align along regional and institutional lines, rather than national government divisions. Additionally, an analysis of triadic binary motifs uncovers a greater level of reciprocity within the Foes network compared to the Friends network. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

As more groups consider how AI may be used in the legal sector, this paper envisions how companies and policymakers can prioritize the perspective of community members as they design AI and policies around it. It presents findings of structured interviews and design sessions with community members, in which they were asked about whether, how, and why they would use AI tools powered by large language models to respond to legal problems like receiving an eviction notice. The respondents reviewed options for simple versus complex interfaces for AI tools, and expressed how they would want to engage with an AI tool to resolve a legal problem. These empirical findings provide directions that can counterbalance legal domain experts' proposals about the public interest around AI, as expressed by attorneys, court officials, advocates and regulators. By hearing directly from community members about how they want to use AI for civil justice tasks, what risks concern them, and the value they would find in different kinds of AI tools, this research can ensure that people's points of view are understood and prioritized, rather than only domain experts' assertions about people's needs and preferences around legal help AI. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

This paper investigates the potential for reducing the complexity of AI and Law and empirical legal studies projects through a novel annotation methodology that relies on GPT Family Models to assist human annotators. Improving the speed, cost and quality of annotation could greatly benefit such projects. In modelling types of legal claims, researchers in the fields of empirical legal studies and AI and Law have long relied on manually annotating factors in case texts. To demonstrate our methodology, we employ cases and factors regarding whether a police officer has constitutional authority to detain a motorist on the basis of the officer's suspicion that the motorist is trafficking drugs. Our results demonstrate how recent advances in text analytics can reduce the burden of identifying factors in large numbers of cases and improve machine learning models' predictions of case outcomes. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

From at least the early twentieth century, legal scholars have recognized that rights and other legal relations inhere between individual legal actors, forming a vast and complex social network. Yet, no legal scholar has used the mathematical machinery of network theory to formalize these relationships. Here, we propose the first such approach by modelling a rudimentary, static set of real property relations using network theory. Then, we apply our toy model to measure the level of modularity—essentially, the community structure—among aggregations of these real property relations and associated actors. In so doing, we show that even for a very basic set of relations and actors, law may employ modular structures to manage complexity. Property, torts, contracts, intellectual property, and other areas of the law arguably reduce information costs in similar, quantifiable ways by chopping up the world of interactions between parties into manageable modules that are semi-autonomous. We also posit that our network science approach to jurisprudential issues can be adapted to quantify many other important aspects of legal systems. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

Law sets out the rules for society and the economy, particularly important for interactions between strangers. Legal code is a form of non-rival infrastructure, a public good important for investment and innovation. This paper investigates whether legal code complexity scales with population size in US localities. We analyse a corpus of municipal codes from 3259 cities and measure legal complexity using various metrics, including number of words, bytes, and compressed bytes. We find that legal complexity scales geometrically with jurisdiction population, with a scaling parameter of approximately 0.2 and an R2 of approximately 0.2. The estimated scaling parameter is similar to gross domestic product percapita, consistent with an interpretation of legal codes as regulating social interactions per capita in cities. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

We propose and evaluate an automated pipeline for discovering significant topics from legal decision texts by passing features synthesized with topic models through penalized regressions and post-selection significance tests. The method identifies case topics significantly correlated with outcomes, topic-word distributions which can be manually interpreted to gain insights about significant topics, and case-topic weights which can be used to identify representative cases for each topic. We demonstrate the method on a new dataset of domain name disputes and a canonical dataset of European Court of Human Rights violation cases. Topic models based on latent semantic analysis as well as language model embeddings are evaluated. We show that topics derived by the pipeline are consistent with legal doctrines in both areas and can be useful in other related legal analysis tasks. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

We apply a dynamic influence model to the opinions of the US federal courts to examine the role of the US Supreme Court in influencing the direction of legal discourse in the federal courts. We propose two mechanisms for how the Court affects innovation in legal language: a selection mechanism where the Court's influence primarily derives from its discretionary jurisdiction, and an authorship mechanism in which the Court's influence derives directly from its own innovations. To test these alternative hypotheses, we develop a novel influence measure based on a dynamic topic model that separates the Court's own language innovations from those of the lower courts. Applying this measure to the US federal courts, we find that the Supreme Court primarily exercises influence through the selection mechanism, with modest additional influence attributable to the authorship mechanism. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

Complexity science provides a powerful framework for understanding physical, biological and social systems, and network analysis is one of its principal tools. Since many complex systems exhibit multilateral interactions that change over time, in recent years, network scientists have become increasingly interested in modelling and measuring dynamic networks featuring higher-order relations. At the same time, while network analysis has been more widely adopted to investigate the structure and evolution of law as a complex system, the utility of dynamic higher-order networks in the legal domain has remained largely unexplored. Setting out to change this, we introduce temporal hypergraphs as a powerful tool for studying legal network data. Temporal hypergraphs generalize static graphs by (i) allowing any number of nodes to participate in an edge and (ii) permitting nodes or edges to be added, modified or deleted. We describe models and methods to explore legal hypergraphs that evolve over time and elucidate their benefits through case studies on legal citation and collaboration networks that change over a period of more than 70 years. Our work demonstrates the potential of dynamic higher-order networks for studying complex legal systems, and it facilitates further advances in legal network analysis. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

The collective statistics of voting on judicial courts present hints about their inner workings. Many approaches for studying these statistics, however, assume that judges' decisions are conditionally independent: a judge reaches a decision based on the case at hand and his or her personal views. In reality, judges interact. We develop a minimal model that accounts for judge bias, depending on the context of the case, and peer interaction. We apply the model to voting data from the US Supreme Court. We find strong evidence that interaction is an important factor across natural courts from 1946 to 2021. We also find that, after accounting for interaction, the recovered biases differ from highly cited ideological scores. Our method exemplifies how physics and complexity-inspired modelling can drive the development of theoretical models and improved measures for political voting. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

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