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“This is a deepfake!” : Celebrity scandals, parodic deepfakes, and a critically speculative ethics of care for fandom research in the age of Artificial Intelligence
Get PDFFans are increasingly aware of deepfake—believable AI-fabricated videos—and are therefore more skeptical of unverified information, even when visual evidence appears convincing. This article offers a methodological reflection on analyzing a deepfake event in which fans produced and circulated AI-generated disinformation to playfully undermine the credibility of a celebrity’s video scandal. We explore the complex human-community-machine interactions (HCMI) between fans and AI-generated images, and we discuss how researchers can ethically (re)present their findings. We call for rethinking the “fan first” principle, a core tenet of ethical fandom research. Drawing on Puig de la Bellacasa’s technoscientific theorization of care, we propose a critically speculative ethics of care in fandom research, guided by three principles: (1) thinking with fans, (2) thinking for fandom, and (3) thinking beyond fans and fandom. This approach is particularly relevant in a digital media ecology where generative AI and fan practices mutually transform each other. Our discussion also serves as a springboard for further explorations of ethics related to AI, including its impact on trust, social relations, and power in fandom research
How much of a threat does Venezuela’s exiled opposition pose to the rule of Nicolás Maduro?
No full textVenezuela’s leader, Nicolás Maduro, will be sworn in as president for a record third term on January 10, four months after being declared the winner of the country’s highly contentious election. Maduro will receive the standard obeisance from his cronies and will hug the limelight, but plenty of Venezuelans will have very little to celebrate
Exploring Lie Frequency and Emotional Experiences of Deceptive Decision Making in Autistic Adults
Get PDFDeception is a multi-faceted social behaviour that is pervasive in human communication. Due to differences in social communication and experiences, autistic and non-autistic adults may contrast in how they respond to situations that elicit deceptive decision-making. This study examined whether autistic and non-autistic adults differed in their general lie frequency, their inclination to produce different lie types, and their emotional experiences of lying. Fifty-eight non-autistic and fifty-six autistic university students matched on age and gender completed self-report measures of their general lying patterns, how often they lied in the past 24 hours, and whether they would lie across hypothetical scenarios with differing beneficiaries (self, other, group) and motivations (protective, beneficial). The groups did not significantly differ in their general lying behaviour or frequency of lies told over 24 hours. Yet, autistic adults indicated that they would be significantly less likely to lie in group scenarios and would experience increased difficulty, more guilt, and greater concerns about their believability when lying. These results advance theoretical understanding by suggesting that autistic adults’ deceptive decision making may be context dependent. Future research may benefit from examining autistic deception across numerous social situations as more general lie frequency measures may be insensitive to nuanced population differences
Effects of ill-health and health shocks on labour market outcomes under social protection constraints
Get PDFThis thesis examines the effects of ill-health and health shocks on labour market outcomes. To achieve this, given the paucity of meta-analyses on the topic, a systematic review and meta-analysis was initially undertaken which is presented as chapter two of the thesis. The results from the review and meta-analysis show statistically significant pooled estimates of the effects of ill-health and health shocks on hours worked and the probability of employment. These results justified the research questions pursued in the thesis, including specific analysis of Malawi where no work of this nature has been undertaken before and where evidence could be useful in policy terms. To explore the effects of ill-health and health shocks on labour supply, in chapter three, data from Malawi were used to assess the effects of several proxies of health shocks and ill-health. This included illness/injury, hospital admission, and chronic illness, on the probabilities of wage employment, casual employment, job search and on hours of work. The chapter employed nearest neighbour propensity score matching to estimate Average Treatment Effects on the Treated (ATET). Overall, results of the analysis showed that a) individuals who reported to have suffered an illness or injury in the last fourteen days significantly reduced their probability of wage employment but increased the probability of casual employment; b) individuals who reported to have experienced a hospital admission in the last twelve months significantly reduced their probability of wage employment but increased their probability of casual employment; and c) individuals who reported that they suffered from a chronic disease significantly reduced both their probabilities of wage employment and casual employment. Furthermore, results showed that individuals who reported to have suffered an illness or injury in the last fourteen days, those who reported to have experienced a hospital admission in the last twelve months as well as those who reported that they suffered from a chronic disease, significantly reduced their weekly hours of work. Moreover, in terms of the probability of job search, the study found that individuals who reported to have suffered an illness or injury in the last fourteen days significantly reduced their probability of job search while those who reported that they suffered from a chronic disease significantly increased the probability of searching for a job. There was no statistically significant effect on the probability of job search for individuals who reported to have experienced a hospital admission in the last twelve months. In chapter four, a wide range of count data models including negative binomial, zero-inflated negative binomial, Poisson, zero-inflated Poisson, and a two-part model were used to assess the joint effects of ill-health and health shocks together with social protection on the intensive margin of labour supply using rich data from Malawi. A standard OLS model was also estimated to provide baseline estimates which were not based on a count data model. Weekly hours of work were employed in the analysis. Results showed that a) individuals who suffered an illness/injury and benefited from social protection reduced their hours of work; b) individuals who had experienced a hospital admission and benefited from social protection increased their hours of work; and c) individuals with chronic illnesses who benefited from social protection reduced their weekly hours of work. The results of the thesis have important policy implications for Malawi and other low- and middle-income countries (LMICs). More specifically, the evidence presented here can inform the development of health and labour policies, encompassing initiatives to facilitate job search through public employment services, enhance access to social protection, and strengthen primary healthcare and universal health coverage as well as the overall health infrastructure
Arabic Digits-In-Noise tests : Relations to hearing loss and comparison of diotic and antiphasic versions
Get PDFUnderstanding Early Career Academics’ Learning to Experience Teaching in Higher Education : Integrating Theory and Empirical (Poetic) Work
Get PDFEarly Career Academics (ECA) often find themselves starting a lecturing position in a Higher Education Institution (HEI) without knowing how to teach and/or with limited comparable previous experience. This is by itself a difficult task to face emotionally and cognitively speaking, and it adds to the already long list of demands that ECAs face when freshly starting the role. This issue leads us to wonder how ECAs experience teaching in Higher Education. This broad question has been tackled by offering descriptions in the literature as mixed feeling and overall negative emotions. In turn, this project contributes to the field by looking into how experiencing teaching may itself be inscribed in a learning process. Theory Work is undertaken to elaborate and argue for a constructivist and processual understanding of experience, emotions, and learning. Here, the argument is that experiences can be conceptually understood through perezhivanie (Vygotski, 1994) to highlight how they are learnt and lead to learning, while elaborating how learning is itself an emotional experience. Then, the project moves towards the empirical (re)creation/production of the experience of teaching with ECAs through the Art-Based Research method of Poetic Transcription done jointly with the lecturers. The experiences are presented as an exhibition of collected poems, curated and commented on by the researcher following an entrance and three rooms structure. Taking the theory and empirical work together, this project sheds some light on the experiencing of teaching as something that is learnt and worked-through as an experience. Here, experiences are complex as they integrate into larger processes. Thus, specific previous experiences and stories can be identified as anchors that relate to each other in particular ways for the reconstruction of the ECA’s experiences of teaching: their purposeful conjunction is identified as the precursors of the lecturer’s current way of (re)constructing the experiences of teaching
Plant root carbon inputs drive methane production in tropical peatlands
No full textTropical peatlands are carbon-dense ecosystems that are significant sources of atmospheric methane (CH4). Recent work has demonstrated the importance of trees as an emission pathway for CH4 from the peat to the atmosphere. However, there remain questions over the processes of CH4 production in these systems and how they relate to substrate supply. Principally, these questions relate to the relative contribution of recent photosynthetically fixed carbon, released as root exudates, versus carbon substrate supply from the slowly decomposing peat matrix to CH4 emissions within these ecosystems. Here, we examined the role of root inputs in regulating CH4 production inferred from soil emissions using a combination of in situ tree girdling, in situ13C natural abundance labelling via stem injections, and a 13CO2 labelling of transplanted plants of two contrasting plant functional types, a broadleaved evergreen tree, and a canopy palm. Girdling of broadleaved evergreen trees reduced CH4 fluxes by up to 67%. Stem injections of trees and palms with a natural abundance label resulted in significant isotopic enrichment of CH4 fluxes, reinforcing the link between root carbon inputs and peat CH4 fluxes. Ex situ13CO2 labelling of plants resulted in significant 13C enrichment of peat CH4 fluxes. Taken together, our results demonstrate for the first time that plant root exudates make a substantial contribution to CH4 production in tropical peatlands
A NOMA-Enhanced 2-Step RACH Procedure for Low-Latency Access in 5G Networks
No full textRandom access channel (RACH) procedure is critical to support a multitude of devices transmitting small data payloads while ensuring low-latency access. In 3GPP Release 16, a two-step RACH is proposed to alleviate signaling overhead and access latency. While benefits are noticeable, collisions still persist. In this paper, we propose a novel non-orthogonal multiple access (NOMA)-enhanced 2-step RACH scheme (NOMA-RACH) that jointly leverages the benefits of access class barring (ACB), 2-step RACH, and NOMA random access (NOMA-RA) to further enhance the performance. We conduct a holistic study that accounts for entire access latency. The scheme optimizes NOMA access probabilities, utilizes an adjustable barring mechanism for delay-sensitive devices, and identifies the optimal barring rate for low latency. We develop a Markov chain model to analyze NOMA access and derive the optimal access probabilities and throughput of NOMA blocks. To cope with the practical scenarios with constantly changing user equipment (UE) traffic, we propose a deep contextual multi-armed bandit (DCMAB) model that optimizes the NOMA throughput and dynamically adjusts the barring rate based on the observable channel feedback. Our simulation results demonstrate that the DCMAB model performs better than benchmark schemes and remains close to the optimal latency confirming the effectiveness of our proposed scheme under changing UE traffic
Exploring the Problems, their Causes and Solutions of AI Pair Programming : A Study on Git Huband Stack Overflow
Get PDFWith the recent advancement of Artificial Intelligence (AI) and Large Language Models (LLMs), AI-based code generation tools become a practical solution for software development. GitHub Copilot, the AI pair programmer, utilizes machine learning models trained on a large corpus of code snippets to generate code suggestions using natural language processing. Despite its popularity in software development, there is limited empirical evidence on the actual experiences of practitioners who work with Copilot. To this end, we conducted an empirical study to understand the problems that practitioners face when using Copilot, as well as their underlying causes and potential solutions. We collected data from 473 GitHub issues, 706 GitHub discussions, and 142 Stack Overflow posts. Our results reveal that (1) Operation Issue and Compatibility Issue are the most common problems faced by Copilot users, (2) Copilot Internal Error, Network Connection Error, and Editor/IDE Compatibility Issue are identified as the most frequent causes, and (3) Bug Fixed by Copilot, Modify Configuration/Setting, and Use Suitable Version are the predominant solutions. Based on the results, we discuss the potential areas of Copilot for enhancement, and provide the implications for the Copilot users, the Copilot team, and researchers
Improving hospital palliative care between COVID-19 waves : A retrospective cohort study
No full textA specialist palliative care service in an acute hospital characterized care patterns during the first wave of the COVID-19 pandemic. There were delayed referrals for minoritized ethnic groups. COVID-19 treatments (dexamethasone, anticoagulation, remdesivir) alongside service changes were introduced in the second wave. To examine changes in care patterns and trends in the context of COVID-19 treatments. A secondary objective is to examine differences in ethnic disparity between the first and second wave of COVID-19. Retrospective cohort study comparing patients referred to an acute hospital palliative care service with confirmed COVID-19 infection either at the peak of the first (Mar-Apr 2020, W1), or second (Dec 2020-Feb 2021, W2) wave of the pandemic. Demographic, clinical characteristics, and outcomes data were compared using statistical tests; generalized linear mixed models for modelling of elapsed time from admission to referral; and survival analysis. Data from 165 patients (W1 = 60, W2 =105) were included. Patients in W1 were referred earlier to palliative care than in W2, particularly in the first 10 days from admission. Receiving dexamethasone or anticoagulants, and absence of dementia, hypertension, and fever were associated with longer time to referral to palliative care. Delays in referrals of Black and Asian patients during W1 was no longer observable in W2. There was no association between socioeconomic status and care patterns and trends. The Australian-modified Karnofsky Performance Status (HR 3, 95% CI: 2 - 5) were good predictors of survival. Our findings have the potential to inform strategies that improve palliative care response and equity beyond COVID-19, and in future pandemics or crises. [Abstract copyright: Copyright © 2024. Published by Elsevier Inc.