Hasil untuk "Anthropology"

P. Bourdieu, Richard Nice

Outline of a Theory of Practice is recognized as a major theoretical text on the foundations of anthropology and sociology. Pierre Bourdieu, a distinguished French anthropologist, develops a theory of practice which is simultaneously a critique of the methods and postures of social science and a general account of how human action should be understood. With his central concept of the habitus, the principle which negotiates between objective structures and practices, Bourdieu is able to transcend the dichotomies which have shaped theoretical thinking about the social world. The author draws on his fieldwork in Kabylia (Algeria) to illustrate his theoretical propositions. With detailed study of matrimonial strategies and the role of rite and myth, he analyses the dialectical process of the 'incorporation of structures' and the objectification of habitus, whereby social formations tend to reproduce themselves. A rigorous consistent materialist approach lays the foundations for a theory of symbolic capital and, through analysis of the different modes of domination, a theory of symbolic power.

B. Pfaffenberger

Giorgia Sampò, Saverio Giallorenzo, Zelda Alice Franceschi

Why do some community-cooperation projects catalyse participation through durable, resilient collaboration networks while others result in negligible impact and leave the local social fabric unchanged? We argue outcomes hinge on participation architecture: simple, visible routines -- onboarding help, templated tasks, lightweight contribution/benefit tracking -- that create easy ``entry portals'' and route work across clusters without heavy hierarchy. We introduce Project Intervention Response Analysis (PIRA), a mixed anthropological-network-analysis framework that compares observed community networks with counterfactual networks absent from project-induced ties. PIRA also adds a new egocentric metric to detect ``architectural alters'' -- latent facilitators and boundary spanners. We begin validating PIRA in a three-month field study in Pomerini, Tanzania, where NGOs coordinated citizens, associations, and specialists. Findings indicate that sociotechnical participation architectures -- not charismatic hubs -- underwrite durable coordination. PIRA offers a reusable method to link organizational design mechanisms to formal network signatures.

Olha Ivashchenko, Oleg Khudolii, Mykola Khudolii

Objectives. To synthesize contemporary scientific approaches to interpreting physical education of schoolchildren within the logic of a managed learning process and to clarify the role of pedagogical control, modelling, and age-related developmental regularities in shaping learning outcomes. Materials and Methods. The study was conducted as a narrative review of publications addressing physical education theory, pedagogical control, modelling of the learning process, age-related developmental regularities, and the teaching of physical exercises in general secondary education. The analysis was carried out from systems-based and learning-oriented perspectives on the organisation of physical education. Results. The review supports interpreting physical education of schoolchildren as a managed learning process in which learning outcomes emerge through the interaction of pedagogical control, modelling, and learners’ age-related developmental characteristics. Age-related regularities are best treated as parameters of learning models that define the boundaries for valid interpretation of pedagogical-control results. Pedagogical control acquires a regulatory function only when embedded within a model of the learning process. The synthesis also allows the learning of physical exercises to be interpreted as the formation and dynamics of learning states that can serve as objects of pedagogical control and regulation. Conclusions. The proposed synthesis enables interpreting outcomes of physical education as consequences of the organisation of the learning process rather than as autonomous normative indicators. This narrative review delineates theoretical and methodological frames for further research aimed at empirically testing models of managed physical education and refining tools of pedagogical control in general secondary education practice.

Gianluca De Ninno, Paola Inverardi, Francesca Belotti

This study investigates a novel approach to eliciting users' moral decision-making by combining immersive roleplaying games with LLM analysis capabilities. Building on the distinction introduced by Floridi between hard ethics inspiring and shaping laws-and soft ethics-moral preferences guiding individual behavior within the free space of decisions compliant to laws-we focus on capturing the latter through contextrich, narrative-driven interactions. Grounded in anthropological methods, the role-playing game exposes participants to ethically charged scenarios in the domain of digital privacy. Data collected during the sessions were interpreted by a customized LLM ("GPT Anthropologist"). Evaluation through a cross-validation process shows that both the richness of the data and the interpretive framing significantly enhance the model's ability to predict user behavior. Results show that LLMs can be effectively employed to automate and enhance the understanding of user moral preferences and decision-making process in the early stages of software development.

Diana Mykhaylychenko, Maisha Thasin, Dunya Baradari et al.

Animist worldviews treat beings, plants, landscapes, and even tools as persons endowed with spirit, an orientation that has long shaped human-nonhuman relations through ritual and moral practice. While modern industrial societies have often imagined technology as mute and mechanical, recent advances in artificial intelligence (AI), especially large language models (LLMs), invite people to anthropomorphize and attribute inner life to devices. This paper introduces A(I)nimism, an interactive installation exploring how large language objects (LLOs) can mediate animistic relationships with everyday things. Housed within a physical 'portal', the system uses GPT-4 Vision, voice input, and memory-based agents to create evolving object-personas. Encounters unfold through light, sound, and touch in a ritual-like process of request, conversation, and transformation that is designed to evoke empathy, wonder, and reflection. We situate the project within anthropological perspectives, speculative design, and spiritual HCI. AI's opacity, we argue, invites animistic interpretation, allowing LLOs to re-enchant the mundane and spark new questions of agency, responsibility, and design.

Santhosh Kumar Ravindran

Building on the affective dream-replay reinforcement learning framework of CosmoCore, we introduce CosmoCore-Evo, an extension that incorporates evolutionary algorithms to enhance adaptability and novelty in code generation tasks. Inspired by anthropological aspects of human evolution, such as natural selection and adaptation in early hominids, CosmoCore-Evo treats RL trajectories as ``genomes'' that undergo mutation and selection during the nocturnal replay phase. This mechanism allows agents to break free from trained patterns, fostering emergent behaviors and improved performance in distribution-shifted environments, such as changing APIs or novel libraries. We augment the Dream Queue with evolutionary operations, including mutation of high-fitness trajectories and enterprise-tuned fitness functions that incorporate efficiency, compliance, and scalability metrics. Evaluated on extended benchmarks including HumanEval variants with shifts, BigCodeBench, and a custom PySpark pipeline simulation, CosmoCore-Evo achieves up to 35% higher novelty in solutions and 25% faster adaptation compared to the original CosmoCore and baselines like PPO and REAMER. Ablations confirm the role of evolutionary components in bridging the sentient gap for LLM agents. Code for replication, including a toy simulation, is provided.

W. Furian, T. Sauter

<p>This study investigates simulated glacial lake outburst floods (GLOFs) at five glacial lakes in the Everest region of Nepal using the three-dimensional model OpenFOAM. It presents the evolution of GLOF characteristics in the 21st century considering different moraine breach scenarios and two Shared Socioeconomic Pathways scenarios. The results demonstrate that in low-magnitude scenarios, the five lakes generate GLOFs that inundate between 0.35 and 2.23 km<span class="inline-formula">²</span> of agricultural land with an average water depth of 0.9 to 3.58 m. These GLOFs reach distances of 59 to 84 km, affect 30 to 88 km of roads or trails, and inundate 183 to 1699 buildings with 1.2 to 4.9 m of water. In higher scenarios, GLOFs can extend over 100 km and also affect larger settlements in the foothills. Between 80 and 100 km of roads, 735 to 1989 houses and 0.85 to 3.52 km<span class="inline-formula">²</span> of agricultural land could be inundated, with average water depths of up to 10 m. The high precision of the 3D flood modeling, with detailed simulations of turbulence and viscosity, provides valuable insights into 21st-century GLOF evolution, supporting more accurate risk assessments and effective adaptation strategies.</p>

Jacopo Armini, Fabio Gianni, Stefano Niccolai

Georeferenced Access Points as a Strategic Node in the Evolution of Territorial Information Systems - This paper explores the strategic role of georeferenced access points and civic numbering as foundational components of advanced Territorial Information Systems (SIT) within Italian public administrations. The quality and consistency of georeferenced street and building numbers represent a fundamental component of territorial data infrastructures, enabling reliable integration between cadastral datasets, administrative services and emergency response systems. Drawing from the experience of LdP Progetti GIS — involving more than 130 municipalities across five regions — the article demonstrates how the integration of Accesses, Buildings and Street Toponyms enables an interoperable Web-GIS ecosystem supporting digital services, data governance and operational decision-making. Real case studies from the municipalities of Siena, Arezzo, Empoli and Pistoia illustrate concrete applications such as emergency management, fiscal intelligence (TARI compliance), housing planning and economic activity monitoring. The results highlight significant improvements in administrative efficiency, transparency and open-data availability, positioning geospatial infrastructures as a key enabler of digital transformation in the Public Sector.

M. Lock

Wm. Matthew Kennedy, Daniel Vargas Campos

Operationalizing AI ethics and safety principles and frameworks is essential to realizing the potential benefits and mitigating potential harms caused by AI systems. To that end, actors across industry, academia, and regulatory bodies have created formal taxonomies of harm to support operationalization efforts. These include novel holistic methods that go beyond exclusive reliance on technical benchmarking. However, our paper argues that such taxonomies must also be transferred into local categories to be readily implemented in sector-specific AI safety operationalization efforts, and especially in underresourced or high-risk sectors. This is because many sectors are constituted by discourses, norms, and values that "refract" or even directly conflict with those operating in society more broadly. Drawing from emerging anthropological theories of human rights, we propose that the process of "vernacularization"--a participatory, decolonial practice distinct from doctrinary "translation" (the dominant mode of AI safety operationalization)--can help bridge this gap. To demonstrate this point, we consider the education sector, and identify precisely how vernacularizing a leading holistic taxonomy of harm leads to a clearer view of how harms AI systems may cause are substantially intensified when deployed in educational spaces. We conclude by discussing the generalizability of vernacularization as a useful AI safety methodology.

Anna Kawakami, Amanda Coston, Hoda Heidari et al.

As public sector agencies rapidly introduce new AI tools in high-stakes domains like social services, it becomes critical to understand how decisions to adopt these tools are made in practice. We borrow from the anthropological practice to ``study up'' those in positions of power, and reorient our study of public sector AI around those who have the power and responsibility to make decisions about the role that AI tools will play in their agency. Through semi-structured interviews and design activities with 16 agency decision-makers, we examine how decisions about AI design and adoption are influenced by their interactions with and assumptions about other actors within these agencies (e.g., frontline workers and agency leaders), as well as those above (legal systems and contracted companies), and below (impacted communities). By centering these networks of power relations, our findings shed light on how infrastructural, legal, and social factors create barriers and disincentives to the involvement of a broader range of stakeholders in decisions about AI design and adoption. Agency decision-makers desired more practical support for stakeholder involvement around public sector AI to help overcome the knowledge and power differentials they perceived between them and other stakeholders (e.g., frontline workers and impacted community members). Building on these findings, we discuss implications for future research and policy around actualizing participatory AI approaches in public sector contexts.

M. Burgess, R. I. M. Dunbar

The human capacity for working together and with tools builds on cognitive abilities that, while not unique to humans, are most developed in humans both in scale and plasticity. Our capacity to engage with collaborators and with technology requires a continuous expenditure of attentive work that we show may be understood in terms of what is heuristically argued as`trust' in socio-economic fields. By adopting a `social physics' of information approach, we are able to bring dimensional analysis to bear on an anthropological-economic issue. The cognitive-economic trade-off between group size and rate of attention to detail is the connection between these. This allows humans to scale cooperative effort across groups, from teams to communities, with a trade-off between group size and attention. We show here that an accurate concept of trust follows a bipartite `economy of work' model, and that this leads to correct predictions about the statistical distribution of group sizes in society. Trust is essentially a cognitive-economic issue that depends on the memory cost of past behaviour and on the frequency of attentive policing of intent. All this leads to the characteristic `fractal' structure for human communities. The balance between attraction to some alpha attractor and dispersion due to conflict fully explains data from all relevant sources. The implications of our method suggest a broad applicability beyond purely social groupings to general resource constrained interactions, e.g. in work, technology, cybernetics, and generalized socio-economic systems of all kinds.

Jack Tacchi, Parisa Jamadi Khiabani, Arkaitz Zubiaga et al.

Understanding human interactions and social structures is an incredibly important task, especially in such an interconnected world. One task that facilitates this is Stance Detection, which predicts the opinion or attitude of a text towards a target entity. Traditionally, this has often been done mainly via the use of text-based approaches, however, recent work has produced a model (CT-TN) that leverages information about a user's social network to help predict their stance, outperforming certain cross-target text-based approaches. Unfortunately, the data required for such graph-based approaches is not always available. This paper proposes two novel tools for Stance Detection: the Ego Network Model (ENM) and the Signed Ego Network Model (SENM). These models are founded in anthropological and psychological studies and have been used within the context of social network analysis and related tasks (e.g., link prediction). Stance Detection predictions obtained using these features achieve a level of accuracy similar to the graph-based features used by CT-TN while requiring less and more easily obtainable data. In addition to this, the performances of the inner and outer circles of the ENM, representing stronger and weaker social ties, respectively are compared. Surprisingly, the outer circles, which contain more numerous but less intimate connections, are more useful for predicting stance.

Elena-Andreea Trandafirescu, Vladimir Potop, Ilie Mihai et al.

Background and Study Aim. Fear of failure, choking under pressure, financial disparities in income, and concerns related to body image and social pressure may intensify on-field challenges. These factors make the competitive environment particularly demanding for female soccer players. The aim of the current review is to map the available evidence on anxiety in women's football over the past decade and to identify interventions designed to manage anxiety among female soccer players. Material and Methods. A scoping review was conducted following the PRISMA-ScR guidelines. An extensive search was carried out across four major databases for publications dated between 2014 and 2024. Two independent reviewers screened titles and abstracts, followed by full-text screening and data extraction. Any disagreements were resolved by a third researcher. The findings were tabulated and synthesized in a narrative format. The study was pre-registered on the Open Science Framework. Results. The search yielded 2885 unique records. A total of 21 texts were reviewed in full, and the final sample included 14 studies. Some of the records included mentioned modifications to psychosocial interventions, such as Virtual Reality (VR) relaxation sessions, pre-exercise sporting massage, and psychological training programs (including psycho-neuromuscular theory and visualization techniques). These interventions led to a reduction in anxiety, though their effectiveness varied significantly across different approaches. Our results suggest that research on women's football may disproportionately focus on psychological interventions for managing anxiety. This highlights the need for broader investigations into other factors that influence athletes' performance and well-being. Conclusions. This scoping review helps clarify the current landscape of anxiety research in women's soccer. It highlights both promising interventions and gaps in the research over the past decade. Although the body of evidence on anxiety interventions is small, it suggests that psychological interventions may be effective in reducing anxiety among female soccer players.

Qihang Liu, Li Pan, Huijing He et al.

Background: Studies about the combined effects of gaseous air pollutants and particulate matters are still rare. Objectives: This study was performed based on baseline survey of the Diverse Life-Course Cohort in the Beijing-Tianjin-Hebei (BTH) Region of North China to evaluate the association of long-term air pollutants with blood pressure and the combined effect of the air pollutants mixture among 32821 natural han population aged 20 years or above. Methods: Three-year average exposure to air pollutants (PM10, PM2.5, PM1, O3, SO2, NO2, and CO) and PM2.5 components [black carbon (BC), ammonium (NH4+), nitrate (NO3−), sulfate (SO42−), and organic matter (OM)] of residential areas were calculated based on well-validated models. Generalized linear mixed models (GLMMs) were used to estimate the associations of air pollutants exposure with the systolic blood pressure (SBP), diastolic blood pressure (DBP), Mean arterial pressure (MAP), pulse pressure (PP) and prevalent hypertension. Quantile g-Computation and Bayesian Kernel Machine Regression (BKMR) were employed to assess the combined effect of the air pollutant mixture. Results: We found that long-term exposures of O3, PM2.5, and PM2.5 components were stably and strongly associated with elevated SBP, DBP, and MAP and prevalent hypertension. O3 increased SBP, DBP, and MAP at a similar extent, but with greater effects; while, PM2.5 and PM2.5 components had a greater impact on SBP than DBP, which increased PP simultaneously. In multi-pollutant models, the combined effects of the air pollutant mixture on blood pressure and prevalent hypertension was predominantly influenced by O3, PM2.5, and O3, OM in different models, respectively. For example, O3, PM2.5 contributed 57.25 %, 39.22 % of the positive combined effect of the air pollutant mixture on SBP; and O3, OM positively contributed 70.00 %, 30.00 % on prevalent hypertension, respectively. There were interactions between O3, CO, SO2 and PM2.5 components on hbp, SBP and PP. Conclusions: The results showed positive associations of air pollutant mixtures with blood pressure, where O3 and PM2.5 (especially OM) might be primary contributors. There were interactions between gaseous air pollutants and PM2.5 components on blood pressure and prevalent hypertension.

P. Rabinow

This collection of essays explains the author's project to anthropologize the West. His goal is to exoticize the Western constitution of reality, emphasize those domains most taken for granted as universal, and show how their claims to truth are linked to particular social practices, hence becoming effective social forces. This text poses questions about how scientific practice can be understood in terms of ethics as well as in terms of power. The topics covered in the text include how French socialist urban planning in the 1930s engineered the transition from city planning to life planning; how the discursive and nondiscursive practices of the Human Genome Project and biotechnology have refigured life, labour and language; and how a debate over patenting cell lines and over the dignity of life required secular courts to invoke medieval notions of the sacred. The final essay is concerned with the place of science on modernity, on science as a vocation, and on the differences between the human and natural sciences.

Tom Savage, Ehecatl Antonio del Rio Chanona

Domain experts often possess valuable physical insights that are overlooked in fully automated decision-making processes such as Bayesian optimisation. In this article we apply high-throughput (batch) Bayesian optimisation alongside anthropological decision theory to enable domain experts to influence the selection of optimal experiments. Our methodology exploits the hypothesis that humans are better at making discrete choices than continuous ones and enables experts to influence critical early decisions. At each iteration we solve an augmented multi-objective optimisation problem across a number of alternate solutions, maximising both the sum of their utility function values and the determinant of their covariance matrix, equivalent to their total variability. By taking the solution at the knee point of the Pareto front, we return a set of alternate solutions at each iteration that have both high utility values and are reasonably distinct, from which the expert selects one for evaluation. We demonstrate that even in the case of an uninformed practitioner, our algorithm recovers the regret of standard Bayesian optimisation.

Nicolas Perreaux

This article examines the importance of graphic representations in the social sciences, and particularly in (medieval) history, taking as its starting point a reflection by {É}tienne-Jules Marey, a physiologist and pioneer of 19th-century photography and cinema. Marey believed that the visual should replace language in many fields. Indeed, the twentieth and early twenty-first centuries saw an exponential multiplication of visual media, particularly with the advent of digital technology. However, this ''graphics revolution'' has not affected all disciplines equally. Significant differences remain between scientific fields such as astrophysics, anthropology, chemistry and medieval history, despite their shared commitment to describing dynamic processes and changes of state. Yet, while historians have already digitized a large part of the cultural heritage from Antiquity to the 10th-13th centuries, exploration of this corpus using visualizations remains limited. There is therefore untapped potential in this field.This article begins by outlining a typology and quantification of the past and potential roles of visual representations in medieval history. It examines two distinct intellectual approaches: 1. the use of visuals to support a scientific discourse (majority) and 2. the construction of a historical discourse based on observations made from visual figures with the aim of modeling phenomena invisible to the naked eye. The author thus examines the use of ''images'' in medievalism, focusing on the annual volumes of the Soci{é}t{é} des historiens m{é}di{é}vistes de l'enseignement sup{é}rieur (SHMESP), up to 2006. Two other parts of the text look at the still-rare forms of visual representation in medieval history, particularly those with a ''heuristic vocation'', using iconographic objects, parchments, buildings and digitized texts. The article suggests various visualization techniques, such as network analysis, the creation of ''stemmas 2.0'' and interactive chronologies, which could benefit the discipline. These methods could potentially profoundly change our understanding of ancient societies, by showing the dynamic relationships between different aspects of these societies. One of the most important advances expected from these visual methods is a better understanding of the patterns of development in medieval Europe, which varied from region to region. The hypothesis is that the scarcity of heuristic graphics in medieval history stems from the relationship with ancient documents and the historical method based on narration and exemplarity. The article thus questions the value of ''visual modelling'' in medieval history, and highlights the challenges associated with the widespread adoption of this approach in the humanities and social sciences. Finally, the text invites us to reflect on the nature and functioning of heuristic visual devices, by comparing medieval ''images'' and contemporary scientific visuals. In both cases, the point is to materialize the invisible in order to show something that exists beyond the visual. The author suggests that this way of approaching visuals could play a growing role in the decades to come, particularly in the field of data science.

Tamás Dávid-Barrett, Sebastian Diaz, Carlos Rodriguez-Sickert et al.

Mobile call networks have been widely used to investigate communication patterns and the network of interactions of humans at the societal scale. Yet, more detailed analysis is often hindered by having no information about the nature of the relationships, even if some metadata about the individuals are available. Using a unique, large mobile phone database with information about individual surnames in a population in which people inherit two surnames: one from their father, and one from their mother, we are able to differentiate among close kin relationship types. Here we focus on the difference between the most frequently called alters depending on whether they are family relationships or not. We find support in the data for two hypotheses: (1) phone calls between family members are more frequent and last longer than phone calls between non-kin, and (2) the phone call pattern between family members show a higher variation depending on the stage of life-course compared to non-family members. We give an interpretation of these findings within the framework of evolutionary anthropology: kinship matters even when demographic processes, such as low fertility, urbanisation and migration reduce the access to family members. Furthermore, our results provide tools for distinguishing between different kinds of kin relationships from mobile call data, when information about names are unavailable.