Informational uncertainty of measuring instruments

Recently, there has been a revival of interest in the use of the information approach in the theory of measurements. Unlike the traditional approach, information theory does not evaluate error or uncertainty, but entropy and the amount of information. This article analyzes a number of recent publications that develop ideas for the information approach. The limitations and disadvantages of both the entropy approach and the concept of uncertainty are indicated. As a compromise solution, it is proposed to use a criterion based on the Bongard’s uncertainty and useful information. The concept of information uncertainty is proposed, which is estimated by the amount of negative useful information, that is, misinformation introduced by the measuring instrument. Some methods for calculating information uncertainty are described. The problems of using the uncertainty approach are noted. This approach does not imply the use of such a generalized characteristic of measuring instruments as an accuracy class. The article proposes an analogue of the accuracy class in the form of relative informational uncertainty, expressed as a percentage. This will make it possible to evaluate the quality of the measuring instrument by a single parameter, the calculation of which requires a minimum of computational operations.

Neuromarketing as interdisciplinary area: Theoretical and methodological analysis

Modern neuromarketing is a synthesis of behavioral economics theoretical and methodological foundations in close connection with the tools of neurophysiology which are successfully used in the practice of sensory marketing. At the same time, the basic methodological principle of neuromarketing is limited rationality in the context of behavioral and informational uncertainty. Purpose of publication – сarrying out theoretical and methodological analysis of neuromarketing as a complex interdisciplinary and innovative area; disclosure of methodological principles and theoretical provisions of behavioral economics in the context of their applications in touch marketing. Such methods as analysis, comparison, generalization, systemic and logical ones were used in the research. It is argued that consumer decision-making in choice situations is influenced by emotions based on subconscious perception. It is proved that visual, sound and aromarketing are the main “nudging” factors of R. Thaler’s theory in the context of neuromarketing. For the first time in the scientific discourse, the elements of the sensory component of neuromarketing are considered as stimulating factors for the implicit “nudging” of R. Thaler's behavioral economics theory. The theoretical and methodological foundations of neuromarketing research, which based on more realistic postulates of limited rationality, influence of emotions and information incompleteness in contrast to “homo economicus” neoclassical paradigm are improved. It is shown that a necessary condition for further successful development of neuromarketing is a combined interaction of psychology behavioral direction, neurophysiological technologies and empirical experience of marketers due to possible achievement of synergistic effect. The results of experimental studies, based on the empirical experience of a number of well-known scientists using neurophysiological methods, have proved the verification of the basic theoretical and methodological positions and individual effects of behavioral economics, which are actively used by Ukrainian marketers and marketers of other countries.

What Surrogates Understand (and Don’t Understand) About Patients’ Wishes After Engaging Advance Care Planning: A Qualitative Analysis

Background: The goal of advance care planning (ACP) is to improve end-of-life decision-making for patients and their spokespersons, but multiple studies have failed to show substantial or consistent benefit from ACP. Understanding how and why ACP under-performs in the setting of complex medical decision-making is key to optimizing current, or designing new, ACP interventions. Aim: To explore how ACP did or did not contribute to a spokespersons’ understanding of patient wishes after engaging in ACP. Design: Thematic analysis of 200 purposively sampled interviews from a randomized control trial of an ACP decision aid. Setting/Participants: 200 dyads consisting of patients 18 years or older with advanced serious illness and their spokesperson at 2 tertiary care centers in Hershey, PA and Boston, MA. Participants were interviewed 1 month after completing ACP. Results: ACP helped participants: 1) express clear end-of-life wishes, 2) clarify values, and 3) recognize challenges associated with applying those wishes in complex situations. Shortcomings of ACP included 1) unknown prognostic information or quality-of-life outcomes to inform decision-making, 2) skepticism about patients’ wishes, and 3) complicated emotions impacting end-of-life discussions. Conclusions: Helping patients and their spokespersons better anticipate decision-making in the face of prognostic and informational uncertainty as well as the emotional complexities of making medical decisions may improve the efficacy of ACP interventions.

Hybrid Media and Hybrid Politics: Contesting Informational Uncertainty in Lebanon and Tunisia

This paper investigates the dynamic relationship between hybrid media and hybrid politics in Lebanon and Tunisia. While previous research on the media in hybrid regimes has mainly focused on regime strategies of restricting and manipulating public debate, our analysis moves beyond repression. We argue that the ambiguities of hybrid politics, which combines democratic and authoritarian elements, not only constrain independent and critical reporting but also open up opportunities for journalistic agencies. We draw on Schedler's concept of informational uncertainty to capture the epistemological instability of hybrid regimes and the strategies of political actors to control public knowledge. Distinguishing between three dimensions of media hybridity - economic, cultural and technological - we show how the new hybrid media environment significantly increases the volatility of hybrid politics and informational uncertainty for political actors. Our empirical analysis is based on seventy-one semistructured interviews with journalists in Lebanon and Tunisia conducted between 2016 and 2019. The material reveals a broad range of strategies used by journalists who employ the internal contradictions of hybrid politics to pursue their own agenda. The comparison between Lebanon and Tunisia also highlights contextual conditions that enable, or limit, journalistic agency, such as clientelistic dependencies, economic resources, and civil society alliances.

Application of Models of Probabilistic Situations regarding Railways

The article describes application of models of information probabilistic situations for solving problems of traffic control on the railway. The content of situational control is revealed. The difference between a visual and a «blind» situation during vehicle’s movement is shown.The information situation around a moving object can be deterministic and stochastic. The concept of a stochastic information control situation is introduced. The choice of alternatives in stochastic control situations is characterized by organizational, technological, and informational uncertainties.This motivates development of control methods and algorithms that consider uncertainty and multicriteria in control of moving objects in such situations. Situational control can be used in automated, cyber-physical and intelligent control.The article proposes a model for controlling mobile objects based on a probabilistic approach in a stochastic situation and on the consideration of a number of stochastic factors. The model is based on calculating the probability of existence of an obstacle in the path of a vehicle. Such a model can be used under the conditions of poor visibility and a probability of receiving erroneous information from sensors. The article gives a systematics of the probabilistic characteristics of a stochastic information situation accompanying a moving object. The application of dichotomous and oppositional analysis in studying obstacles on the route has been substantiated. The model for detecting a foreign object on a traffic route is based on the assumption of the presence of reliable and erroneous information. The analysis is based on Dempster–Schafer theory. The stochastic information situation model uses the probabilistic characteristics of the presence of an obstacle on the track. The probability of an object’s existence is estimated using Bayes’ theorem. The proposed model considers three factors of the stochastic situation: informational uncertainty in the signal; false signals, sensor measurement error. The field of application of this situational model comprises digital railway, intelligent transport systems, transport cyber-physical systems.

The Logic of Vulnerability and Civilian Victimization

ABSTRACTWhat causes civilian victimization in conventional civil wars and in conventional wars that experience insurgencies? The authors argue that a key driver of civilian victimization is the vulnerability of the incumbent forces, specifically when the conflict’s front line is shifting. Vulnerability is a function of informational and logistical challenges: when the front line is moving, incumbents face increased informational uncertainty and unstable supply chains that augment their vulnerability. Thus, incumbents will increase the use of civilian victimization in response to a scarcity of high-quality information on the location and identity of insurgents, to limit possible information leaks, and to contain supply disruption and logistics support to adversaries. The authors support their argument using matched difference-in-differences analyses of original subnational data on Nazi-Fascist violence in World War II Italy (1943–1945) and qualitative evidence.

Prospection does not imply predictive processing

Predictive processing models of psychopathologies are not explanatorily consistent with the present account of abstract thought. These models are based on latent variables probabilistically mapping the structure of the world. As such, they cannot be informed by representational ontology based on mental objects and states. What actually is the case is merely some terminological affinity between subjective and informational uncertainty.

State anxiety biases estimates of uncertainty during reward learning in volatile environments

Previous research established that clinical anxiety impairs decision making and that high trait anxiety interferes with learning rates. Less understood are the effects of temporary anxious states on learning and decision making in healthy populations. Here we follow proposals that anxious states in healthy individuals elicit a pattern of aberrant behavioural, neural, and physiological responses comparable with those found in anxiety disorders, particularly when processing uncertainty in unstable environments. In our study, both a state anxious and a control group learned probabilistic stimulus-outcome mappings in a volatile task environment while we recorded their electrophysiological (EEG) signals. By using a hierarchical Bayesian model, we assessed the effect of state anxiety on Bayesian belief updating with a focus on uncertainty estimates. State anxiety was associated with an underestimation of environmental and informational uncertainty, and an increase in uncertainty about volatility estimates. Anxious individuals deemed their beliefs about reward contingencies to be more precise and to require less updating, ultimately leading to impaired reward-based learning. We interpret this pattern as evidence that state anxious individuals are less tolerant to informational uncertainty about the contingencies governing their environment and more uncertain about the level of stability of the world itself. Further, we tracked the neural representation of belief update signals in the trial-by-trial EEG amplitudes. In control participants, both lower-level precision-weighted prediction errors (pwPEs) about the reward outcomes and higher-level volatility-pwPEs were represented in the ERP signals with an anterior distribution. A different pattern emerged under state anxiety, where a neural representation of pwPEs was only found for updates about volatility. Expanding previous computational work on trait anxiety, our findings establish that temporary anxious states in healthy individuals impair reward-based learning in volatile environments, primarily through changes in uncertainty estimates and potentially a degradation of the neuronal representation of hierarchically-related pwPEs, considered to play a central role in current Bayesian accounts of perceptual inference and learning.