Affective dimensions of pandemic life: The mediatised cultivation of outrage

2021 ◽  
Author(s):  
David Conradson
Keyword(s):  
2008 ◽  
Author(s):  
W. Li ◽  
M. Louwet ◽  
I. Van Diest ◽  
S. De Peuter ◽  
K. Bogaerts ◽  
...  
Keyword(s):  

2017 ◽  
Vol 46 (3-4) ◽  
pp. 18-23 ◽  
Author(s):  
Courtney O'Dell-Chaib

Evolutionary biologist Edward O. Wilson’s biophilia hypothesis, that humans have a genetically influenced emotional affiliation with life and life-like processes, for some time has invigorated a prominent strain of scholarship within religion and ecology that taps into the affective dimensions of our evolutionary histories. Our biophilic tendencies coupled with the awe, wonder, and reverence evoked by these religiously resonant cosmologies, they argue, provide occasions for cultivating ethical investments rooted in genetic kinship. However, much of this work that adopts biophilia assumes a “healthy” animal-other and rarely affiliates with the ill, disabled, and mutated creatures impacted by ecological degradation. In conversation with Donovan Schaefer’s provocative new book Religious Affects: Animality, Evolution, and Power and his engagement with biophilia, this paper considers possibilities for addressing aversion to animals impacted by ecological collapse through Schaefer’s understanding of affects as not merely adaptive, but embedded within complex economies of embodiment and power.


Author(s):  
Kristian Miok ◽  
Blaž Škrlj ◽  
Daniela Zaharie ◽  
Marko Robnik-Šikonja

AbstractHate speech is an important problem in the management of user-generated content. To remove offensive content or ban misbehaving users, content moderators need reliable hate speech detectors. Recently, deep neural networks based on the transformer architecture, such as the (multilingual) BERT model, have achieved superior performance in many natural language classification tasks, including hate speech detection. So far, these methods have not been able to quantify their output in terms of reliability. We propose a Bayesian method using Monte Carlo dropout within the attention layers of the transformer models to provide well-calibrated reliability estimates. We evaluate and visualize the results of the proposed approach on hate speech detection problems in several languages. Additionally, we test whether affective dimensions can enhance the information extracted by the BERT model in hate speech classification. Our experiments show that Monte Carlo dropout provides a viable mechanism for reliability estimation in transformer networks. Used within the BERT model, it offers state-of-the-art classification performance and can detect less trusted predictions.


2020 ◽  
pp. 107780042091889
Author(s):  
Erin Leach

This autoethnographic poetry collection provides an entry into the socialization of part-time doctoral students by centering the lived experience of the author, a part-time doctoral student employed full-time at the university where she studies. In the writing of this poetry collection, the author sought to enter into conversation with the doctoral socialization literature and to uncover the various parts of her fractured identity. Through an examination of her own fractured identity, the author engages with the places where scholarly identity formation is stalled in part-time doctoral students especially in comparison with their full-time peers and considers affective dimensions of the work of scholarly identity formation.


Leonardo ◽  
2020 ◽  
Vol 53 (3) ◽  
pp. 321-326 ◽  
Author(s):  
Lizzie Muller ◽  
Lynn Froggett ◽  
Jill Bennett

The locus of encounter between art, science and the public can be conceptualized as third space—a generative site of shared experience. This article reports on a group-based psychosocial method led by imagery and affect—the visual matrix—that enables researchers to capture and characterize knowledge emerging in third space, where disciplinary boundaries are fluid and there is no settled discourse. It presents an account of the visual matrix process in the context of an artscience collaboration on memory and forgetting. The authors show how the method illuminates aesthetic and affective dimensions of participant experience and captures the emerging, empathic and ethical knowing that is characteristic of third space.


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