hierarchical groups
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2021 ◽  
pp. 53-81
Author(s):  
Harvey Whitehouse

Collective rituals tend to come in two kinds: frequently performed but relatively lowkey; rarely enacted but emotionally intense. According to the theory of modes of religiosity, high-frequency but low-arousal rituals produce large-scale hierarchical groups (the doctrinal mode), while low-frequency but high-arousal rituals produce small-scale highly cohesive groups (the imagistic mode). This chapter describes how that theory was first developed while carrying out fieldwork in the New Guinea rainforest. But then the author realized it could help to explain how groups throughout the world take shape and spread, and it could also help to explain how complex societies evolved.


2021 ◽  
pp. 136754942110557
Author(s):  
Elaine Swan

The category of the ‘everyday’ has been relatively un-theorised in studies of digital food culture. Drawing on theories that the everyday is not just a backdrop but through which race, class and gender are constituted, and the cultural production of whiteness, I analyse digital photographs from the Welcome Dinner Project’s webpages and social media. The Welcome Dinner Project is an Australian food hospitality activism charity, which organises and facilitates one-off dinners to bring ‘newly arrived’ and ‘established Australians’ together over potluck hospitality to address isolation and racism. My overall argument is that Welcome Dinner Project representations and media representations of Welcome Dinner Project are underscored by conflicting representations of race, diversity and privilege. Despite the good intentions of the Welcome Dinner Project, the formal images it disseminates work to service the status quo by enacting and reinforcing dominant notions of middle-class whiteness in Australia, moderating the transgressive potential of its activism. However, these processes are subverted by less formal and unruly images depicting people outside, in mess, in non-hierarchical groups and migrant hosting. Such imagery can be understood as a form of visual activism which challenges the iconographies of whiteness in digital food culture and normative ideals of race-neutral domesticity and everydayness.


2021 ◽  
Vol 83 (3) ◽  
pp. 161-164
Author(s):  
Christopher G. Brown

Students sometimes struggle to organize complex concepts and visualize the connectedness of hierarchical groups, yet much of the biological sciences depends on ranking, ordering, or grouping of information. Diagnosing disease, converting units, and evolutionary relationships all follow stepwise ranking of groups of information. This article presents a cooperative, low-stakes, inexpensive method for novice students to organize hierarchical information. As an example, students work together placing and rearranging animal cards according to taxonomic and evolutionary relationships along a string using shared characteristics. The cards provided address Next Generation Science Standards pertaining to inheritance/variation (LS3) and unity and diversity (LS4). I provide a detailed description of the activity as well as the tools needed to perform this lesson.


2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Sören Henning ◽  
Wilhelm Hasselbring

Abstract Ever-increasing amounts of data and requirements to process them in real time lead to more and more analytics platforms and software systems designed according to the concept of stream processing. A common area of application is processing continuous data streams from sensors, for example, IoT devices or performance monitoring tools. In addition to analyzing pure sensor data, analyses of data for entire groups of sensors often need to be performed. Therefore, data streams of the individual sensors have to be continuously aggregated to a data stream for a group. Motivated by a real-world application scenario of analyzing power consumption in Industry 4.0 environments, we propose that such a stream aggregation approach has to allow for aggregating sensors in hierarchical groups, support multiple such hierarchies in parallel, provide reconfiguration at runtime, and preserve the scalability and reliability qualities of stream processing techniques. We propose a stream processing architecture fulfilling these requirements, which can be integrated into existing big data architectures. As all state-of-the-art stream processing frameworks have to handle a trade-off between latency, resource-efficiency, and correctness, our proposed architecture can be configured for low latency and resource-efficient computation or for always ensuring correct results. To assist adopters in choosing appropriate configuration options, we provide an experimental comparison. We present a pilot implementation of our proposed architecture and show how it is used in industry. Furthermore, in experimental evaluations we show that our solution scales linearly with the amount of sensors and provides adequate reliability in the presence of faults.


2020 ◽  
Vol 74 (3) ◽  
pp. 453-484
Author(s):  
Yegor Grebnev

Abstract In this paper, I compare the material in the Pāli canon of Theravada Buddhism, a textual tradition famous for the abundance of numerical lists, with certain chapters of the Yi Zhou shu 逸周書 and chapter “Hong fan” 洪範 of the Shang shu 尚書, where numerical lists are equally important. I propose a classification of the insufficiently studied numerical lists in the Yi Zhou shu and point out the divergences in them, suggesting that they were produced by competing communities that developed slightly discordant systems of knowledge. I compare the evolution of complex frameworks of numerical lists in the Buddhist traditions and in early China, arguing that both created comprehensive systems of knowledge-practice out of simpler lists. The peculiar form of numerical lists as vehicles of systematised knowledge-practice attested in both cultures may have originated in hierarchical communities with indisputable knowledge authority. Such communities are known to have existed in early Buddhism, and they have convincing parallels in China’s contemporary political practice, where numerical lists are used to unify the patterns of thinking and behaviour in hierarchical groups.


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