scholarly journals Negotiating Authenticity in Technological Environments

2021 ◽  
Author(s):  
Siri Beerends ◽  
Ciano Aydin
Keyword(s):  
Social Control ◽  
Power Relations ◽  
Emerging Technologies ◽  
Data Driven ◽  
Culturally Informed ◽  
Inherent Quality ◽  
Interactionist Approach

AbstractEssentialists understand authenticity as an inherent quality of a person, object, artifact, or place, whereas constructionists consider authenticity as a social creation without any pre-given essence, factuality, or reality. In this paper, we move beyond the essentialist-constructionist dichotomy. Rather than focusing on the question whether authenticity can be found or needs to be constructed, we hook into the idea that authenticity is an interactive, culturally informed process of negotiation. In addition to essentialist and constructionist approaches, we discuss a third, less well-known approach that cannot be reduced to any of the two forms. This approach celebrates the authenticity of inauthenticity by amplifying the made. We argue that the value of (in)authenticity lies not in choosing for one of these approaches, but in the degree to which the process of negotiating authenticity enables a critical formation of selves and societies. Authenticity is often invoked as a method of social control or a mark of power relations: once something is defined as authentic, it is no longer questioned. Emerging technologies—especially data-driven technologies—have the capacity to conceal these power relations, propel a shift in power, and dominate authentication processes. This raises the question how processes of authentication can contribute to a critical formation of selves and societies, against the backdrop of emerging technologies. We argue in favor of an interactionist approach of authenticity and discuss the importance of creating space in authentication processes that are increasingly influenced by technology as an invisible actor.

scholarly journals A Survey on Machine Learning-Based Performance Improvement of Wireless Networks: PHY, MAC and Network Layer

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 318
Author(s):  
Merima Kulin ◽  
Tarik Kazaz ◽  
Eli De Poorter ◽  
Ingrid Moerman
Keyword(s):  
Machine Learning ◽  
Wireless Networks ◽  
Performance Improvement ◽  
Quality Of Experience ◽  
Data Driven ◽  
Protocol Stack ◽  
Comprehensive Survey ◽  
Network Prediction ◽  
Network Quality

This paper presents a systematic and comprehensive survey that reviews the latest research efforts focused on machine learning (ML) based performance improvement of wireless networks, while considering all layers of the protocol stack: PHY, MAC and network. First, the related work and paper contributions are discussed, followed by providing the necessary background on data-driven approaches and machine learning to help non-machine learning experts understand all discussed techniques. Then, a comprehensive review is presented on works employing ML-based approaches to optimize the wireless communication parameters settings to achieve improved network quality-of-service (QoS) and quality-of-experience (QoE). We first categorize these works into: radio analysis, MAC analysis and network prediction approaches, followed by subcategories within each. Finally, open challenges and broader perspectives are discussed.

Ethical infrastructure: Halal and the ecology of askesis in Muslim Russia

2021 ◽  
pp. 146349962110597
Author(s):  
Matteo (Teo) Benussi
Keyword(s):  
Ethical Consumption ◽  
Complex Environments ◽  
Inner Self ◽  
Conditions Of Possibility ◽  
Material Conditions ◽  
Material Religion ◽  
Late Modern ◽  
Inherent Quality ◽  
Methodological Ground

This article explores the ecology of late-modern askesis through the concept of ‘ethical infrastructure’: the array of goods, locales, technologies, procedures, and sundry pieces of equipment upon which the possibility of ethicists’ striving is premised. By looking at the ethnographic case of halal living among Muslim pietists in post-Soviet Tatarstan (Russia), I advance a framework that highlights the ‘profane’, often unassuming or religiously unmarked, yet essential material scaffolding constituting the ‘material conditions of possibility’ for pious life in the lifeworld of late modernity. Halalness is conceptualised not as an inherent quality of a clearly defined set of things, but as a (sometimes complicated) relationship between humans, ethical intentionality, and infrastructurally organised habitats. Pointing beyond the case of halal, this article syncretises theories of self-cultivation, material religion, ethical consumption, and infrastructure to address current lacunas and explore fresh theoretical and methodological ground. This ‘ethical infrastructure’ framework enables us to conceptualise the embeddedness of contemporary ethicists in complex environments and the process by which processes of inner self-fashioning change and are changed by material worlds.

scholarly journals Stability Analysis of R&D Cooperation in a Supply Chain

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Luyun Xu ◽  
Dong Liang ◽  
Zhenjie Duan ◽  
Xu Xiao
Keyword(s):  
Game Theory ◽  
Stability Analysis ◽  
Knowledge Spillovers ◽  
Opportunistic Behavior ◽  
Collaborative Process ◽  
Level Of Knowledge ◽  
The Stability ◽  
The Cost ◽  
Inherent Quality

R&D outsourcing becomes the often-adopted strategy for firms to innovate. However, R&D cooperation often ends up with failure because of its inherent quality of instability. One of the main reasons for cooperation failure is the opportunistic behavior. As the R&D contract between firms is inherently incomplete, opportunistic behavior always cannot be avoided in the collaborative process. R&D cooperation has been divided into horizontal and vertical types. This paper utilizes game theory to study opportunistic behavior in the vertical R&D cooperation and analyzes the equilibrium of the cooperation. Based on the equilibrium and numerical results, it is found that the vertical R&D cooperation is inherently unstable, and the downstream firm is more likely to break the agreement. The level of knowledge spillovers and the cost of R&D efforts have different effects on firms’ payoffs. When the level of knowledge spillover is low or the cost of R&D efforts is high, mechanisms such as punishment for opportunism may be more effective to guarantee the stability of cooperation.

scholarly journals The Public Employee Facing Unconstitutional Policies: Organization, State, Power, Stability and Social Control

2019 ◽  
Author(s):  
Helder Gusso
Keyword(s):  
Public Sector ◽  
Social Control ◽  
Government Policy ◽  
Power Relations ◽  
Control Agency ◽  
Public Employee ◽  
Organizational Analysis ◽  
The Public ◽  
And Control

This article highlights the duty of the public employee to oppose any government policy that goes against constitutional principles and objectives. The defence of this position is made from an organizational analysis of the State. Theoretical contributions such as the understanding of State and Domination in M. Weber, Organization in D. Katz and R.L. Khan, and Control Agency in B.F. Skinner have been used. The analysis of contingencies that control the behavior of the public employee and the understanding of the notions of State and Organizations enable greater clarity about what constitutes the role of workers in the public sector. It also highlights the importance of existing mechanisms to reduce the imbalance in power relations between governors, servants and the population.

scholarly journals Measuring outcomes in healthcare economics using Artificial Intelligence: With application to resource management

Data & Policy ◽  
2021 ◽  
Vol 3 ◽  
Author(s):  
Chih-Hao Huang ◽  
Feras A. Batarseh ◽  
Adel Boueiz ◽  
Ajay Kulkarni ◽  
Po-Hsuan Su ◽  
...  
Keyword(s):  
Decision Making ◽  
Traveling Salesman ◽  
Data Driven ◽  
Resources Allocation ◽  
Healthcare Economics ◽  
Economic Aspects ◽  
Internal Factors ◽  
Measuring Outcomes ◽  
Optimum Plan

Abstract The quality of service in healthcare is constantly challenged by outlier events such as pandemics (i.e., Covid-19) and natural disasters (such as hurricanes and earthquakes). In most cases, such events lead to critical uncertainties in decision-making, as well as in multiple medical and economic aspects at a hospital. External (geographic) or internal factors (medical and managerial) lead to shifts in planning and budgeting, but most importantly, reduce confidence in conventional processes. In some cases, support from other hospitals proves necessary, which exacerbates the planning aspect. This paper presents three data-driven methods that provide data-driven indicators to help healthcare managers organize their economics and identify the most optimum plan for resources allocation and sharing. Conventional decision-making methods fall short in recommending validated policies for managers. Using reinforcement learning, genetic algorithms, traveling salesman, and clustering, we experimented with different healthcare variables and presented tools and outcomes that could be applied at health institutes. Experiments are performed; the results are recorded, evaluated, and presented.

scholarly journals Handling Uncertainty in Collaborative Embedded Systems Engineering

2020 ◽  
pp. 147-170
Author(s):  
Torsten Bandyszak ◽  
Lisa Jöckel ◽  
Michael Kläs ◽  
Sebastian Törsleff ◽  
Thorsten Weyer ◽  
...  
Keyword(s):  
Embedded Systems ◽  
Systems Engineering ◽  
Heterogeneous Systems ◽  
Data Driven ◽  
Collaborative Group ◽  
System Behavior ◽  
Learning Capability ◽  
Context Knowledge ◽  
The One

AbstractAs collaborative embedded systems operate autonomously in highly dynamic contexts, they must be able to handle uncertainties that can occur during operation. On the one hand, they must be able to handle uncertainties due to the imprecision of sensors and the behavior of data-driven components for perceiving and interpreting the context to enable decisions to be made during operation. On the other hand, uncertainties can emerge from the collaboration in a collaborative group, related to the exchange of information (e.g., context knowledge) between collaborative systems. This chapter presents methods for modeling uncertainty early in development and analyzing uncertainty during both design and operation. These methods allow for the identification of epistemic uncertainties that can occur when various, potentially heterogeneous systems are required to collaborate. The methods also enable graphical and formal modeling of uncertainties and their impact on system behavior (e.g., in the course of dynamic traffic scenarios). Furthermore, this chapter investigates the quality of outputs issued by data-driven models used to equip collaborative embedded systems with uncertainty-resilient machine learning capability.

Connecting Teacher-Made Assessments to Course Learning Outcomes Through Learning Analytics

2019 ◽  
pp. 101-125
Author(s):  
Julia Chen ◽  
Dennis Foung
Keyword(s):  
Learning Outcomes ◽  
Learning Analytics ◽  
Structural Equation ◽  
Data Driven ◽  
Equation Modeling ◽  
Curriculum Alignment ◽  
Outcome Based Education ◽  
Data Driven Approach ◽  
The Subject

This chapter explores the possibility of adopting a data-driven approach to connecting teacher-made assessments with course learning outcomes. The authors begin by describing several key concepts, such as outcome-based education, curriculum alignment, and teacher-made assessments. Then, the context of the research site and the subject in question are described and the use of structural equation modeling (SEM) in this curriculum alignment study is explained. After that, the results of these SEM analyses are presented, and the various models derived from the analyses are discussed. In particular, the authors highlight how a data-driven curriculum model can benefit from input by curriculum leaders and how SEM provides insights into course development and enhancement. The chapter concludes with recommendations for curriculum leaders and front-line teachers to improve the quality of teacher-made assessments.

Building an Analytics Culture to Boost a Data-Driven Entrepreneur's Business Model

2019 ◽  
pp. 260-291
Author(s):  
Soraya Sedkaoui ◽  
Mounia Khelfaoui
Keyword(s):  
Big Data ◽  
Small Business ◽  
Business Model ◽  
Business Process ◽  
Data Analytics ◽  
Data Driven ◽  
Business And Society ◽  
Crucial Importance

This chapter treats the movement that marks, affects, and transforms any part of business and society. It is about big data that is creating, and the value generating that companies, startups, and entrepreneurs have to derive through sophisticated methods and advanced tools. This chapter suggests that analytics can be of crucial importance for business and entrepreneurial practices if correctly aligned with business process needs and can also lead to significant improvement of their performance and quality of the decisions they make. So, the main purpose of this chapter are exploring why small business, entrepreneur, and startups have to use data analytics and how they can integrate, operationally, analytics methods to extract value and create new opportunities.

Conclusion

2020 ◽  
pp. 212-224
Author(s):  
Phillip Brown
Keyword(s):  
Human Capital ◽  
Social Life ◽  
Power Relations ◽  
Research Evidence ◽  
Future Prospects ◽  
Distributional Conflict ◽  
Way Of Thinking

This concluding chapter provides arguments based on mounting research evidence showing that, for many, learning is not earning. It also rests on the contention that historical possibilities exist to improve the quality of individual and social life through the transformation of economic means—in other words, by developing a new way of thinking about human capital. The chapter goes on to confront future prospects for the new human capital, even as these prospects depend on rebalancing the power relations between capital and labor. To conclude, the chapter calls for a different narrative that connects with the disconnections in people’s lives—their sense of disappointment, alienation, and unfairness. However, the distributional conflict revealed at the very heart of capitalism, which is central to the crisis of human capital, remains to be resolved.

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