In his The Road to Reality as well as in his Fashion, Faith and Fantasy, Roger Penrose criticises string theory and its practitioners from a variety of angles ranging from conceptual, technical, and methodological objections to sociological observations about the string theoretic scientific community. In this article, we assess Penrose's conceptual/technical objections to string theory, focussing in particular upon those which invoke the notion of `functional freedom'. In general, we do not find these arguments to be successful.
Novelty modeling and detection is a core topic in Natural Language Processing (NLP), central to numerous tasks such as recommender systems and automatic summarization. It involves identifying pieces of text that deviate in some way from previously known information. However, novelty is also a crucial determinant of the unique perception of relevance and quality of an experience, as it rests upon each individual's understanding of the world. Social factors, particularly cultural background, profoundly influence perceptions of novelty and innovation. Cultural novelty arises from differences in salience and novelty as shaped by the distance between distinct communities. While cultural diversity has garnered increasing attention in artificial intelligence (AI), the lack of robust metrics for quantifying cultural novelty hinders a deeper understanding of these divergences. This gap limits quantifying and understanding cultural differences within computational frameworks. To address this, we propose an interdisciplinary framework that integrates knowledge from sociology and management. Central to our approach is GlobalFusion, a novel dataset comprising 500 dishes and approximately 100,000 cooking recipes capturing cultural adaptation from over 150 countries. By introducing a set of Jensen-Shannon Divergence metrics for novelty, we leverage this dataset to analyze textual divergences when recipes from one community are modified by another with a different cultural background. The results reveal significant correlations between our cultural novelty metrics and established cultural measures based on linguistic, religious, and geographical distances. Our findings highlight the potential of our framework to advance the understanding and measurement of cultural diversity in AI.
Matt Victor Dalziel, Krystal Schaffer, Neil Martin
This review began with the modest goal of drafting a brief commentary on how the social work profession engages with and is impacted by artificial intelligence (AI). However, it quickly became apparent that a deeper exploration was required to adequately capture the profound influence of AI, one of the most transformative and debated innovations in modern history. As a result, this review evolved into an interdisciplinary endeavour, gathering seminal texts, critical articles, and influential voices from across industries and academia. This review aims to provide a comprehensive yet accessible overview, situating AI within broader societal and academic conversations as 2025 dawns. We explore perspectives from leading tech entrepreneurs, cultural icons, CEOs, and politicians alongside the pioneering contributions of AI engineers, innovators, and academics from fields as diverse as mathematics, sociology, philosophy, economics, and more. This review also briefly analyses AI's real-world impacts, ethical challenges, and implications for social work. It presents a vision for AI-facilitated simulations that could transform social work education through Advanced Personalised Simulation Training (APST). This tool uses AI to tailor high-fidelity simulations to individual student needs, providing real-time feedback and preparing them for the complexities of their future practice environments. We maintain a critical tone throughout, balancing our awe of AI's remarkable advancements with necessary caution. As AI continues to permeate every professional realm, understanding its subtleties, challenges, and opportunities becomes essential. Those who fully grasp the intricacies of this technology will be best positioned to navigate the impending AI Era.
Understanding the complex nature of spatial information is crucial for problem solving in social and environmental sciences. This study investigates how the underlying patterns of spatial data can significantly influence the outcomes of spatial predictions. Recognizing unique characteristics of spatial data, such as spatial dependence and spatial heterogeneity, we delve into the fundamental differences and similarities between spatial and non-geospatial prediction models. Through the analysis of six different datasets of environment and socio-economic variables, comparing geospatial models with non-geospatial models, our research highlights the pervasive nature of spatial dependence beyond geographical boundaries. This innovative approach not only recognizes spatial dependence in geographic spaces defined by latitude and longitude but also identifies its presence in non-geographic, attribute-based dimensions. Our findings reveal the pervasive influence of spatial dependence on prediction outcomes across various domains, and spatial dependence significantly influences prediction performance across all spaces. Our findings suggest that the strongest spatial dependence is typically found in geographic space for environment variables, a trend that does not uniformly apply to socio-economic variables. This investigation not only advances the theoretical framework for spatial data analysis, but also proposes new methodologies for accurately capturing and expressing spatial dependence under complex conditions. Our research extends spatial analysis to non-geographic dimensions such as social networks and gene expression patterns, emphasizing the role of spatial dependence in improving prediction accuracy, thereby supporting interdisciplinary applications across fields such as geographic information science, environmental science, economics, sociology, and bioinformatics.
Maciej J Mrowinski, Kamil P. Orzechowski, Agata Fronczak
et al.
Granovetter's weak ties theory is a very important sociological theory according to which a correlation between edge weight and the network's topology should exist. More specifically, the neighbourhood overlap of two nodes connected by an edge should be positively correlated with edge weight (tie strength). However, some real social networks exhibit a negative correlation - the most prominent example is the scientific collaboration network, for which overlap decreases with edge weight. It has been demonstrated that the aforementioned inconsistency with Granovetter's theory can be alleviated in the scientific collaboration network through the use of asymmetric measures. In this paper, we explain that while asymmetric measures are often necessary to describe complex networks and to confirm Granovetter's theory, their interpretation is not simple, and there are pitfalls that one must be wary of. The definitions of asymmetric weights and overlaps introduce structural correlations that must be filtered out. We show that correlation profiles can be used to overcome this problem. Using this technique, not only do we confirm Granovetter's theory in various real and artificial social networks, but we also show that Granovetter-like weight-topology correlations are present in other complex networks (e.g. metabolic and neural networks). Our results suggest that Granovetter's theory is a sociological manifestation of more general principles governing various types of complex networks.
Edgar Gutiérrez-Gómez, Ketty Marilú Moscoso-Paucarchuco, Diana Luján-Pérez
et al.
The present field research focuses on the native potato varieties, Wira pasña and Llumchuy waqachi, cultivated in the Peruvian highlands at roughly 4,000 m above sea level. The objective is to analyze the macho essence of the names assigned to the native potato, names that represent the social manifestation of women in Quechua culture. Participant observation and interviews about the different daily activities of the participants facilitated the research on the macho essence of the names of the native potato in the Quechua culture. The preponderant Quechua oral sources in the Peruvian Andes did not allow us to identify exactly how names associated with the macho way of social life were assigned to the native potatoes.
This article examines the Canadian and international legal frameworks for the repatriation of objects and for aboriginal land claim, both organised around the collective dimension of rights, a dimension that structures repatriation requests and territorial claim processes, to the detriment of more complex local normative practices. This article questions the legal frameworks, using data produced as part of a research project that shed light on the relationship maintained by members of the Ilnu community of Mashteuiatsh (Lac-Saint-Jean, Quebec, Canada) with a teuehikan (drum). This case underpins a relationship with the object and a normative system of relational ownership, a relationship erased by the current system of collective ownership.
Law in general. Comparative and uniform law. Jurisprudence, Sociology (General)
This paper revises previous work and introduces changes in spatio-temporal scales. The paper presents a model that includes layers A and B with varying degrees of forgetting and dependence over time. We also model changes in dependence and forgetting in layers A, A', B, and B' under certain conditions. In addition, to discuss the formation of opinion clusters that have reinforcing or obstructive behaviors of forgetting and dependence and are conservative or brainwashing or detoxifying and less prone to filter bubbling, new clusters C and D that recommend, obstruct, block, or incite forgetting and dependence over time are Introduction. This introduction allows us to test hypotheses regarding the expansion of opinions in two dimensions over time and space, the state of development of opinion space, and the expansion of public opinion. Challenges in consensus building will be highlighted, emphasizing the dynamic nature of opinions and the need to consider factors such as dissent, distrust, and media influence. The paper proposes an extended framework that incorporates trust, distrust, and media influence into the consensus building model. We introduce network analysis using dimerizing as a method to gain deeper insights. In this context, we discuss network clustering, media influence, and consensus building. The location and distribution of dimers will be analyzed to gain insight into the structure and dynamics of the network. Dimertiling has been applied in various fields other than network analysis, such as physics and sociology. The paper concludes by emphasizing the importance of diverse perspectives, network analysis, and influential entities in consensus building. It also introduces torus-based visualizations that aid in understanding complex network structures.
Given that Indigenous populations globally are impacted by similar colonial global legacies, their health and other disaprities are usually worse than non-indigenous people. Indigenous peoples of Australia have been seriously impacted by colonial legacies and as a result, their health has negatively been affected. If Indigenous health and wellbeing are to be promoted within the existing Australian health services, a clear understanding of what preventive health means for Indigenous peoples is needed. The aim of this scoping review was to explore the available literature on the uptake/engagement in health assessments or health checks by Indigenous Australian peoples and to determine the enablers and barriers and of health assessment/check uptake/engagement. Specifically, we aimed to: investigate the available evidence reporting the uptake/engagement of health checks/assessments for Australian Indigenous; assess the quality of the available evidence on indigenous health checks/assessments; and identify the enablers or barriers affecting Indigenous persons’ engagement and access to health assessment/health checks. A systematic search of online databases (such as Cinhl, Scopus, ProQuest health and medicine, PubMed, informit, google scholar and google) identified 10 eligible publications on Indigenous preventive health assessments. Reflexive thematic analysis identified three major themes on preventive health assessments: (1) uptake/engagement; (2) benefits and limitations; and (3) enablers and barriers. Findings revealed that Indigenous peoples’ uptake and/or engagement in health assessments/check is a holistic concept varied by cultural factors, gender identity, geographical locations (living in regional and remote areas), and Indigenous clinical leadership/staff’s motivational capacity. Overall, the results indicate that there has been improving rates of uptake of health assessments by some sections of Indigenous communities. However, there is clearly room for improvement, both for aboriginal men and women and those living in regional and remote areas. In addition, barriers to uptake of health asessments were identified as length of time required for the assessment, intrusive or sensitive questions and shame, and lack of access to health services for some. Indigenous clinical leadership is needed to improve services and encourage Indigenous people to participate in routine health assessments.
Desde un análisis crítico, en este artículo abordamos un corpus secundario que se refirió a la historia centenaria de la ciudad de Buenos Aires, evitando la denominación Belle époque. No obstante, para comprender este período (1880-1910) proponemos utilizar el concepto moda, no por su arquetipo (la indumentaria), sino como fenómeno, cuyo proceder jánico evidenciaría los tres tempos históricos de una ciudad, esto es, mirando el pasado, instalándose en el presente, a fin de fenecer en el futuro para convertirse en una nueva tradición. Así la moda arquitectónica, urbanística, pueda renacer e incorporar otra innovación.
Architecture, Urban groups. The city. Urban sociology
Giacomo Beccari, Henri M. J. Boffin, Paola Andreani
et al.
Being one of the most fascinating and ancient sciences, astronomy has always played a special role in society. In 2022 ESO organised an online conference to offer the community a platform to discuss astronomical topics of sociological and philosophical relevance in a professional atmosphere. The talks touched on several crucial aspects, moving from the methodology of science to the use of metrics, to the importance of diversity in evaluation processes, and to the link between astronomy and society.
Aurelien Pelissier, Miroslav Phan, Didier Le Bail
et al.
Discrete stochastic processes are prevalent in natural systems, with applications in physics, biochemistry, epidemiology, sociology, and finance. While analytic solutions often cannot be derived, existing simulation frameworks can generate stochastic trajectories compatible with the dynamical laws underlying the random phenomena. Still, most simulation algorithms assume the system dynamics are memoryless (Markovian assumption), under which assumption, future occurrences only depend on the system's present state. This enables efficient and exact simulation via the Gillespie algorithm. However, many real-world systems are inherently non-Markovian and exhibit memory effects. Such systems are difficult to study analytically, and current numerical methods are often computationally expensive or limited by strong simplifying assumptions that conflict with empirical data. To address these limitations, we introduce the Rejection-based Gillespie algorithm for non-Markovian Reactions (REGIR), a general and scalable framework for simulating non-Markovian stochastic systems with arbitrary inter-event time distributions. REGIR provides user-defined accuracy while preserving the same asymptotic computational complexity as the classical Gillespie algorithm. We derive a lower bound on REGIR's approximation accuracy and demonstrate its capabilities across three representative classes of non-Markovian systems: (1) reaction channels with delays, (2) stochastic processes driven by individual reactant properties, and (3) temporal networks governed by node activity. In all cases, REGIR accurately captures memory-dependent dynamics and outperforms existing approaches in terms of flexibility and efficiency.
This article investigates the role music and sound played in Harpo Marx’s singular ability to traverse complex, controversial social and political boundaries—an ability that influenced Harpo’s selection as the first American to perform in the USSR after its formal recognition by the USA. The Marx Brothers burst into cinema during Hollywood’s transition from silent films to talkies—a transition essential to the effective translation of Harpo’s character from stage to screen. Although Harpo never spoke in his movies, he was anything but silent. His character was a creature of sound, dependent on an emotive level of communication accessible to all with little need for translation—emotions he expressed in honks, whistles and, most eloquently, in his music. This allowed Harpo to transcend class and wartime politics; a freedom not afforded his brothers, or any character explicitly tied to verbal language and, by extension, a specific cultural outlook.
Sebastian Deri, Jeremie Rappaz, Luca Maria Aiello
et al.
The richness that characterizes relationships is often absent when they are modeled using computational methods in network science. Typically, relationships are represented simply as links, perhaps with weights. The lack of finer granularity is due in part to the fact that, aside from linkage and strength, no fundamental or immediately obvious dimensions exist along which to categorize relationships. Here we propose a set of dimensions that capture major components of many relationships -- derived both from relevant academic literature and people's everyday descriptions of their relationships. We first review prominent findings in sociology and social psychology, highlighting dimensions that have been widely used to categorize social relationships. Next, we examine the validity of these dimensions empirically in two crowd-sourced experiments. Ultimately, we arrive at a set of ten major dimensions that can be used to categorize relationships: similarity, trust, romance, social support, identity, respect, knowledge exchange, power, fun, and conflict. These ten dimensions, while not dispositive, offer higher resolution than existing models. Indeed, we show that one can more accurately predict missing links in a social graph by using these dimensions than by using a state-of-the-art link embeddedness method. We also describe tinghy.org, an online platform we built to collect data about how social media users perceive their online relationships, allowing us to examine these dimensions at scale. Overall, by proposing a new way of modeling social graphs, our work aims to contribute both to theory in network science and practice in the design of social-networking applications.
Arrow's `impossibility' theorem asserts that there are no satisfactory methods of aggregating individual preferences into collective preferences in many complex situations. This result has ramifications in economics, politics, i.e., the theory of voting, and the structure of tournaments. By identifying the objects of choice with mathematical sets, and preferences with Hausdorff measures of the distances between sets, it is possible to extend Arrow's arguments from a sociological to a mathematical setting. One consequence is that notions of reversibility can be expressed in terms of the relative configurations of patterns of sets.
Vassilis N. Ioannidis, Yanning Shen, Georgios B. Giannakis
Network science provides valuable insights across numerous disciplines including sociology, biology, neuroscience and engineering. A task of major practical importance in these application domains is inferring the network structure from noisy observations at a subset of nodes. Available methods for topology inference typically assume that the process over the network is observed at all nodes. However, application-specific constraints may prevent acquiring network-wide observations. Alleviating the limited flexibility of existing approaches, this work advocates structural models for graph processes and develops novel algorithms for joint inference of the network topology and processes from partial nodal observations. Structural equation models (SEMs) and structural vector autoregressive models (SVARMs) have well-documented merits in identifying even directed topologies of complex graphs; while SEMs capture contemporaneous causal dependencies among nodes, SVARMs further account for time-lagged influences. This paper develops algorithms that iterate between inferring directed graphs that "best" fit the data, and estimating the network processes at reduced computational complexity by leveraging tools related to Kalman smoothing. To further accommodate delay-sensitive applications, an online joint inference approach is put forth that even tracks time-evolving topologies. Furthermore, conditions for identifying the network topology given partial observations are specified. It is proved that the required number of observations for unique identification reduces significantly when the network structure is sparse. Numerical tests with synthetic as well as real datasets corroborate the effectiveness of the novel approach.
Questo articolo si propone di analizzare i processi di flessibilizzazione e digitalizzazione che definiscono le molteplici forme contemporanee di organizzazione del lavoro, considerando i rapporti tra gli attori (imprese, lavoratori e territori) e gli impatti sulle condizioni di lavoro, al fine di descrivere le sfide per l’affermazione soggettiva. L’intensificazione dei carichi, i meccanismi capillari di sorveglianza e controllo, l’atomizzazione, la precarietà e la frammentazione si contrappongono alle opportunità di realizzazione personale, valorizzazione delle conoscenze, partecipazione, cooperazione, tracciando dei percorsi di soggettivazione e de-soggettivazione non univoci. Questi processi interessano l’ambito lavorativo quanto i più ampi contesti sociali, determinando delle sfide a livello individuale e collettivo, nel rapporto tra soggettività, democrazia e sviluppo tecnologico delle reti produttive.
Sociology has been taught in Paraguay since 1900. In those years, it was included in the training of other humanities, such as law. Despite this early appearance, the education of sociology is now only 30 years old and exhibits an evolutionary lethargy. The discipline was institutionalized not because it was taught as a major course of study, but because of the publication of two national journals that have existed for more than four decades: Revista Paraguaya de Sociología (Paraguayan Journal of Sociology) and Estudios Paraguayos (Paraguayan Studies). These were the means through which the first sociological articles appeared and currently remain principal channels of knowledge in the field. The objective of this essay is to describe national sociological academic production by analyzing the last five issues of both publications. The classification of topics, methodologies, approaches, use of bibliographies, and types of articles was carried out using hand-coded qualitative text analysis.