The housing deficit in Chile has led to an explosive growth of informal settlements. Although investment in housing subsidies has been a priority in public policy, informal settlements continue to grow, reflecting a multidimensional and dynamic problem. Using a qualitative approach that combines focus groups and interviews with residents of settlements in the Metropolitan Area of Valparaíso and municipal officials, the study analyzes the knowledge and strategies mobilized by communities, as well as the municipalities’ perspectives on this process. Organized actions are observed for land subdivision, street layout, housing construction, infrastructure network connections, and public spaces. Additionally, mechanisms for conflict resolution and negotiation strategies with public and private actors are discussed. These knowledge and practices in the construction and management of habitat enable valuable community-public institutional articulations, which are key to advancing a new policy for settlement and community management. This self-management of habitat challenges the State’s structure in ways that demonstrate participatory, mobilizing, and democratic management. Urban informality is not a homogeneous process but different assemblages between institutions and communities generating agreements, processes, and differentiated and dynamic spaces.
Jonathan Hanson, Ciaran Collins, Tiziana O’Hara
et al.
This paper explores the extent to which community farming can be a component of a community-based circular food system. Community farming is part of a broader pattern of civic agriculture, whereby more localized food production and consumption are linked to a wider, and sometimes global, set of economic, social and environmental factors. However, although aspects of community farming, notably community supported agriculture (CSA) and care (or social) farming have been well defined and studied, community farming as a broader process of civic agriculture has not. Furthermore, there is a limited number of published studies on the social, economic, and environmental impacts of the varied components of community farming. In this study, a focus group was used to generate the following definition of community farming: a process of collaborative transformation at the intersection of land, community, and enterprise; and a definition of a community farm: a place of collaborative transformation at the intersection of land, community and enterprise. This study also presents data from nine diverse community farming projects in Northern Ireland that are part of the Cultivating Community Farming (CCF) project. Over a two-year period, social return on investment (SROI) methodology was used to quantify their cumulative impacts, employing 12 metrics: 11 monetized and one nonmonetized. The overall SROI ratio for the nine projects was 3.52:1, with 90% of this value being social, followed by 8% environmental and 2% economic. This study provides valuable insights into some of the value generated by community farming, notably social, as well as an operational definition that can catalyse further research, practice, and advocacy among stakeholders. It also articulates community farming as a continuum or umbrella term which can incorporate more multifunctional approaches such as care and social farming, and more food production-oriented practices such as CSA.
Research shows that youth participating in engaged agricultural learning gain important practical skills and knowledge. The physicality, setting, and social aspects of agricultural and horticultural projects are opportune for improving mental, emotional, and social well-being—yet the psychosocial and metacognitive impacts of agricultural learning are still unclear. This study examines psychosocial impacts among youth participants, ages 13–17, in the Felege Hiywot Center’s 2023 STEAM (science, technology, engineering, agriculture, and math) Farm Camp. The Farm Camp combines hands-on urban agriculture with employable skills training while addressing food insecurity in an urban neighborhood with limited access to affordable and nutritious foods. During the camp, students design and maintain garden plots where they grow food, prepare shared meals, and participate in integrative science projects. Using a mix of quantitative and qualitative data collected from surveys and facilitated journaling, we explored the positive psychosocial and metacognitive impacts of camp participation. We found gardening instilled positive feelings and was perceived as a source of stress relief and accomplishment among participants. Teens also gained social support through the development of friendships and mentorships. Furthermore, their participation in the program was associated with metacognitive skills development, including self-awareness and reflection. This case study provides a compelling example of how to engage youth from an underserved area in sustainable urban agriculture while fostering metacognitive skills development and positive psychosocial experiences. We conclude that urban youth agricultural learning programs have valuable impacts on participants that go beyond agricultural education and the achievement of practical skills. These findings—which highlight the potential to contribute to psychosocial well-being, social support, and metacognitive abilities associated with maturation and personal development—may be particularly useful for other programs addressing at-risk and vulnerable youth.
Tom Kouwenhoven, Max Peeperkorn, Roy de Kleijn
et al.
Languages are shaped by the inductive biases of their users. Using a classical referential game, we investigate how artificial languages evolve when optimised for inductive biases in humans and large language models (LLMs) via Human-Human, LLM-LLM and Human-LLM experiments. We show that referentially grounded vocabularies emerge that enable reliable communication in all conditions, even when humans \textit{and} LLMs collaborate. Comparisons between conditions reveal that languages optimised for LLMs subtly differ from those optimised for humans. Interestingly, interactions between humans and LLMs alleviate these differences and result in vocabularies more human-like than LLM-like. These findings advance our understanding of the role inductive biases in LLMs play in the dynamic nature of human language and contribute to maintaining alignment in human and machine communication. In particular, our work underscores the need to think of new LLM training methods that include human interaction and shows that using communicative success as a reward signal can be a fruitful, novel direction.
Ardian Selmonaj, Giacomo Del Rio, Adrian Schneider
et al.
We present a system that enables real-time interaction between human users and agents trained to control fighter jets in simulated 3D air combat scenarios. The agents are trained in a dedicated environment using Multi-Agent Reinforcement Learning. A communication link is developed to allow seamless deployment of trained agents into VR-Forces, a widely used defense simulation tool for realistic tactical scenarios. This integration allows mixed simulations where human-controlled entities engage with intelligent agents exhibiting distinct combat behaviors. Our interaction model creates new opportunities for human-agent teaming, immersive training, and the exploration of innovative tactics in defense contexts.
Elizabeth Anne Watkins, Emanuel Moss, Ramesh Manuvinakurike
et al.
In this short paper we address issues related to building multimodal AI systems for human performance support in manufacturing domains. We make two contributions: we first identify challenges of participatory design and training of such systems, and secondly, to address such challenges, we propose the ACE paradigm: "Action and Control via Explanations". Specifically, we suggest that LLMs can be used to produce explanations in the form of human interpretable "semantic frames", which in turn enable end users to provide data the AI system needs to align its multimodal models and representations, including computer vision, automatic speech recognition, and document inputs. ACE, by using LLMs to "explain" using semantic frames, will help the human and the AI system to collaborate, together building a more accurate model of humans activities and behaviors, and ultimately more accurate predictive outputs for better task support, and better outcomes for human users performing manual tasks.
Settlements operate across a wide range of densities and do so for every socio- economic mode of life from those based on hunter-gatherer economies to those which are based on industrial production. Human beings also live across a range of residential densities from very high to very low. Why they do so is a function of many factors, especially differing socio-cultural ways of managing interaction and communication and the associated social and political practices of the communities. Settlement forms are seen as a derivative of many factors because they are. But they are not thereby an epiphenomenon - especially as they become larger, more durable, and bulkier. That gives them inertia and, as a consequence, they become an agency in their own right which produces outcomes with consequences for the communities, which inhabit them. They are not a neutral background. Instead, their materiality, their sizes, and their densities have an impact on the viability of social life. This paper considers the outcomes generated by the regional networks of low-density, urban settlements larger than 100 sq km in extent. The implications of what happened to agrarian-based low-density urban settlements, like Greater Angkor and the Classic Maya settlements, such as Caracol, are of consequence for the risk faced by the regional networks of present-day, low-density urban giants – the megalopoleis and desa-kota. A further perspective is provided by placing these great cities of the past and the present in the larger context of the trajectories and outcomes of smaller low-density settlements over the previous six millennia. The concern is the implications for the viability of low-density urbanism in contexts of the rapid, extreme climate change we are now beginning to experience. The implications are ominous, yet the past also indicates that social and cultural systems are robust, that human beings can survive, and that they retain and continue to remake their social traditions as they adjust to seriously changing circumstances.
With the emergence of a green environment and green business, the banking sector has also enforced green practices. This study aims to explore the impact of motivational factors and green behaviors on the environmental performance of banking sector employees. This is a quantitative study and data has been collected through a cross-sectional survey of the questionnaire in the banking sector. 300 questionnaires were distributed to the bank employees. PLS-SEM was used to find the statistical results. The study finds a positive impact of Extrinsic motivation and Intrinsic motivation on Employee Environmental Performance, the mediating effect of Task-related Green Behaviors was also found to be positive. The study does not support the effect of Voluntary Green Behaviors on Employee Environment Performance and its mediating effect was also not supported. The study findings and deep knowledge of the impact of motivational and behavioral employee environmental performance on banking sector employees have provided new directions for researchers and policymakers. This study will help the policymakers in strategically developing rewarding policies for the employees that would definitely create a positive impact on performance. The results of the study have provided empirical confirmation of employees’ motivational needs and their impact on green behaviors that collectively impact employee environmental performance.
Cities. Urban geography, Urbanization. City and country
Nikhil Hulle, Stéphane Aroca-Ouellette, Anthony J. Ries
et al.
Effective collaboration between humans and AIs hinges on transparent communication and alignment of mental models. However, explicit, verbal communication is not always feasible. Under such circumstances, human-human teams often depend on implicit, nonverbal cues to glean important information about their teammates such as intent and expertise, thereby bolstering team alignment and adaptability. Among these implicit cues, two of the most salient and fundamental are a human's actions in the environment and their visual attention. In this paper, we present a novel method to combine eye gaze data and behavioral data, and evaluate their respective predictive power for human proficiency, trust, and intent. We first collect a dataset of paired eye gaze and gameplay data in the fast-paced collaborative "Overcooked" environment. We then train models on this dataset to compare how the predictive powers differ between gaze data, gameplay data, and their combination. We additionally compare our method to prior works that aggregate eye gaze data and demonstrate how these aggregation methods can substantially reduce the predictive ability of eye gaze. Our results indicate that, while eye gaze data and gameplay data excel in different situations, a model that integrates both types consistently outperforms all baselines. This work paves the way for developing intuitive and responsive agents that can efficiently adapt to new teammates.
David Helmer, Michael Boardman, S. Kate Conroy
et al.
The REAIM 2024 Blueprint for Action states that AI applications in the military domain should be ethical and human-centric and that humans must remain responsible and accountable for their use and effects. Developing rigorous test and evaluation, verification and validation (TEVV) frameworks will contribute to robust oversight mechanisms. TEVV in the development and deployment of AI systems needs to involve human users throughout the lifecycle. Traditional human-centred test and evaluation methods from human factors need to be adapted for deployed AI systems that require ongoing monitoring and evaluation. The language around AI-enabled systems should be shifted to inclusion of the human(s) as a component of the system. Standards and requirements supporting this adjusted definition are needed, as are metrics and means to evaluate them. The need for dialogue between technologists and policymakers on human-centred TEVV will be evergreen, but dialogue needs to be initiated with an objective in mind for it to be productive. Development of TEVV throughout system lifecycle is critical to support this evolution including the issue of human scalability and impact on scale of achievable testing. Communication between technical and non technical communities must be improved to ensure operators and policy-makers understand risk assumed by system use and to better inform research and development. Test and evaluation in support of responsible AI deployment must include the effect of the human to reflect operationally realised system performance. Means of communicating the results of TEVV to those using and making decisions regarding the use of AI based systems will be key in informing risk based decisions regarding use.
To facilitate human--robot interaction (HRI) tasks in real-world scenarios, service robots must adapt to dynamic environments and understand the required tasks while effectively communicating with humans. To accomplish HRI in practice, we propose a novel indoor dynamic map, task understanding system, and response generation system. The indoor dynamic map optimizes robot behavior by managing an occupancy grid map and dynamic information, such as furniture and humans, in separate layers. The task understanding system targets tasks that require multiple actions, such as serving ordered items. Task representations that predefine the flow of necessary actions are applied to achieve highly accurate understanding. The response generation system is executed in parallel with task understanding to facilitate smooth HRI by informing humans of the subsequent actions of the robot. In this study, we focused on waiter duties in a restaurant setting as a representative application of HRI in a dynamic environment. We developed an HRI system that could perform tasks such as serving food and cleaning up while communicating with customers. In experiments conducted in a simulated restaurant environment, the proposed HRI system successfully communicated with customers and served ordered food with 90\% accuracy. In a questionnaire administered after the experiment, the HRI system of the robot received 4.2 points out of 5. These outcomes indicated the effectiveness of the proposed method and HRI system in executing waiter tasks in real-world environments.
Paula Akemi Aoyagui, Sharon Ferguson, Anastasia Kuzminykh
An essential aspect of evaluating Large Language Models (LLMs) is identifying potential biases. This is especially relevant considering the substantial evidence that LLMs can replicate human social biases in their text outputs and further influence stakeholders, potentially amplifying harm to already marginalized individuals and communities. Therefore, recent efforts in bias detection invested in automated benchmarks and objective metrics such as accuracy (i.e., an LLMs output is compared against a predefined ground truth). Nonetheless, social biases can be nuanced, oftentimes subjective and context-dependent, where a situation is open to interpretation and there is no ground truth. While these situations can be difficult for automated evaluation systems to identify, human evaluators could potentially pick up on these nuances. In this paper, we discuss the role of human evaluation and subjective interpretation to augment automated processes when identifying biases in LLMs as part of a human-centred approach to evaluate these models.
Rodents are known to be reservoir hosts for at least 60 zoonotic diseases and are known to play an important role in their transmission and spread in different ways. We sampled different rodent communities within and around human settlements in Northern Senegal, an area subjected to major environmental transformations associated with global changes. Herein, we conducted an epidemiological study on their bacterial communities. One hundred and seventy-one (171) invasive and native rodents were captured, 50 from outdoor trapping sites and 121 rodents from indoor habitats, consisting of five species. The DNA of thirteen pathogens was successfully screened on the rodents’ spleens. We found: 2.3% of spleens positive to Piroplasmida and amplified one which gave a potentially new species Candidatus “Theileria senegalensis”; 9.35% of Bartonella spp. and amplified 10, giving three genotypes; 3.5% of filariasis species; 18.12% of Anaplasmataceae species and amplified only 5, giving a new potential species Candidatus “Ehrlichia senegalensis”; 2.33% of Hepatozoon spp.; 3.5% of Kinetoplastidae spp.; and 15.2% of Borrelia spp. and amplified 8 belonging all to Borrelia crocidurae. Some of the species of pathogens carried by the rodents of our studied area may be unknown because most of those we have identified are new species. In one bacterial taxon, Anaplasma, a positive correlation between host body mass and infection was found. Overall, male and invasive rodents appeared less infected than female and native ones, respectively.
Adrian S.Z. Chase, Amy E. Thompson, John P. Walden
et al.
Abstract Inequality is present in all human societies, but building a robust understanding of how that inequality developed and persisted for centuries requires historical and archaeological data. Identifying the degree of inequality (or disparity) in ancient communities can be addressed through a variety of methods. One method becoming standard practice in archaeology evaluates inequality through quantitative analysis of robust settlement data. In this Compact Special Section, we assess household size as a potential reflection of wealth inequality among Classic period (a.d. 250–900) Maya settlements. First, we generate house-size data from both pedestrian and remotely sensed LiDAR surveys. Then we use those data to calculate Gini coefficients and Lorenz curves, which provide measures of variation. Gini coefficients range from 0 to 1, where 0 reflects perfect equality and 1 indicates perfect inequality, regardless of the actual values in the distribution. Both area (m2) and volume (m3) provide different, complementary metrics to investigate residential size as a metric for wealth inequality among Classic Maya Lowland settlements. Proposed mechanisms that generate inequality include the intergenerational transmission of wealth and differential access to resources; however, addressing these and other pathways for how inequality develops and persists, and how it was maintained in the past provides insight into similar processes of systemic inequality worldwide.
Alyssa S. Thomas, Francisco J Escobedo, M. R. Sloggy
et al.
Larger and more severe wildfires are becoming more frequent and impacting different communities and human settlements. Much of the scientific literature and media on wildfires has focused on area of ecosystems burned and numbers of structures destroyed. Equally unprecedented, but often less reported, are the increasing socioeconomic impacts different people and communities face from wildfires. Such information seems to indicate an emerging need to account for wildfire effects on peri-urban or wildland urban interface (WUI) areas, newer socio-demographic groups, and disadvantaged communities. To address this, we reviewed the socio-demographic dimensions of the wildfire literature using an environmental justice (EJ) lens. Specifically using a literature review of wildfires, human communities, social vulnerability, and homeowner mitigation, we conducted bibliometric and statistical analyses of 299 publications. The majority of publications were from the United States, followed by Canada and Australia, and most dealt with homeowner mitigation of risk, defensible space, and fuel treatments in WUI areas. Most publications studied the direct effects of wildfire related damage. Secondary impacts such as smoke, rural and urban communities, and the role of poverty and language were less studied. Based on a proposed wildfire-relevant EJ definition, the first EJ publication was in 2004, but the term was first used as a keyword in 2018. Studies in WUI communities statistically decreased the likelihood that a publication was EJ relevant. There was a significant relationship between EJ designation and inclusion of race/ethnicity and poverty variables in the study. Complexity across the various definitions of EJ suggest that it should not be used as a quantitative or binary metric; but as a lens to better understand socio-ecological impacts to diverse communities. We present a wildfire-relevant definition to potentially guide policy formulation and account for social and environmental justice issues.
Dr. Keneth Iceland Kasozi, G. Zirintunda, F. Ssempijja
et al.
While both human and animal trypanosomiasis continue to present as major human and animal public health constraints globally, detailed analyses of trypanosome wildlife reservoir hosts remain sparse. African animal trypanosomiasis (AAT) affects both livestock and wildlife carrying a significant risk of spillover and cross-transmission of species and strains between populations. Increased human activity together with pressure on land resources is increasing wildlife–livestock–human infections. Increasing proximity between human settlements and grazing lands to wildlife reserves and game parks only serves to exacerbate zoonotic risk. Communities living and maintaining livestock on the fringes of wildlife-rich ecosystems require to have in place methods of vector control for prevention of AAT transmission and for the treatment of their livestock. Major Trypanosoma spp. include Trypanosoma brucei rhodesiense, Trypanosoma brucei gambiense, and Trypanosoma cruzi, pathogenic for humans, and Trypanosoma vivax, Trypanosoma congolense, Trypanosoma evansi, Trypanosoma brucei brucei, Trypanosoma dionisii, Trypanosoma thomasbancrofti, Trypanosma elephantis, Trypanosoma vegrandis, Trypanosoma copemani, Trypanosoma irwini, Trypanosoma copemani, Trypanosoma gilletti, Trypanosoma theileri, Trypanosoma godfreyi, Trypansoma simiae, and Trypanosoma (Megatrypanum) pestanai. Wildlife hosts for the trypansomatidae include subfamilies of Bovinae, Suidae, Pantherinae, Equidae, Alcephinae, Cercopithecinae, Crocodilinae, Pteropodidae, Peramelidae, Sigmodontidae, and Meliphagidae. Wildlife species are generally considered tolerant to trypanosome infection following centuries of coexistence of vectors and wildlife hosts. Tolerance is influenced by age, sex, species, and physiological condition and parasite challenge. Cyclic transmission through Glossina species occurs for T. congolense, T. simiae, T. vivax, T. brucei, and T. b. rhodesiense, T. b. gambiense, and within Reduviid bugs for T. cruzi. T. evansi is mechanically transmitted, and T. vixax is also commonly transmitted by biting flies including tsetse. Wildlife animal species serve as long-term reservoirs of infection, but the delicate acquired balance between trypanotolerance and trypanosome challenge can be disrupted by an increase in challenge and/or the introduction of new more virulent species into the ecosystem. There is a need to protect wildlife, animal, and human populations from the infectious consequences of encroachment to preserve and protect these populations. In this review, we explore the ecology and epidemiology of Trypanosoma spp. in wildlife.
AbstractThis chapter introduces the concept of the ‘digital polis’ as the focus of this edited collection, which investigates the idea along the dimensions of subjectivity and reality as well as in terms of exclusion and cooperation in communities across physical and virtual urban spaces. Tracing back to Mumford’s description of the city as media and its development by Kittler, the chapter launches the ‘digital polis’ as a key concept underpinning a new theoretical framework that brings to the fore the (re)production of power, knowledge, and space by physically and virtually networked communities, thereby expanding the scope of research for Urban Humanities in contemporary urban environments. The questions we explore in the book revolve around how people, urban spaces, and technologies relate to and affect each other in an urban future. With the advent of a digital divide that produces cyberspace as a kind of gated community, what will our urban future be like? What is the ‘digital polis’ and what kinds of new subjectivity does it produce? How do digital technology and its virtuality reshape the city and our spatial awareness of it? What kinds of exclusion and cooperation are at work in communities and spaces in the digital age? This introduction helps readers navigate the following chapters to open avenues for research and to build new discourses on the ‘digital polis’ as the grounds for a genuinely humanizing urbanism in latent futures, or in other words, futures in the making that are ‘on the way’.