This Differential Emotions Scale (DES) is an objective pencil-and-paper instrument designed to measure the subjective-experience components of the fundamental emotions, based on the assumption that mood states involved a characteristic pattern. Following Boyle (Boyle, G.J. Reliability and validity of Izard's Differential Emotions Scale, Personality, 56, pp. 747-750, 1984), the present paper reports a repeated-measure multiple discriminant function analysis for individual items across raters. At least, two-thirds of the DES items are sensitive indicators of the different mood states, however, the construct (...) validity of the subscales is not clear. In particular, the profiles for the South African participants indicated that there is need for improving the construct validity and retest reliability of DES in order to be useful in applied psychological contexts in non-Western nations. (shrink)

Reporters' use of government data bases can create problems with serving justice and maintaining privacy. Although there are many advantages to the new reporting tool, problems can arise when the information is inaccurate or is misused for purposes other than originally intended. The ethical question of maintaining privacy while ful-filling the political function of the media is discussed. Suggested guidelines are given.

This article reviews the debate over electronic data bases and privacy, with an emphasis on the United States since the Privacy Act of 1974. Proposals that have value for the 1990s, both nationally and internationally, are synthesized. Some current controversies are discussed, including some of the reasons for the failure of previous privacy legislation. The way social values affect both statistical and intelligence systems is reviewed, and the debate over organizational necessity and computerization is examined. Some controversial systems (...) and programs are described, along with suggestions designed to move closer to state-of-the-art privacy oversight. (shrink)

Simulation of brain dynamics requires the use of accurate empirical data. This commentary points out major errors in some of the empirical data used in Wright & Laley's simulation. The simulation is quantitatively very different from the real cortex, and may also have important qualitative differences.

Empirical political theory has grown in importance. In empirical political theory, attention to data is part of the evaluative step. A concern was raised that being attentive to the content of political science data implies that such attentiveness would limit the normative contours of empirical political theory, and will create a status-quo bias. This concern has been called the ‘problem of critical distance’. One way to appraise the significance of this problem is to examine the work done by (...) empirical political theorists such as Anderson (on racial integration), Wenar (on international trade), and Carens (on immigration). All three scholars suggest radical policies that differ from existing institutions and rules. The likelihood that a theory will suffer from the problem of critical distance will depend on the type of usage of data by a given theorist, her/his normative standpoint, and the manner in which they coalesce or differ. (shrink)

The current behavioral consultation case demonstrates how functional behavioral assessment (FBA) data, basic and applied research, teacher preferences, and contextual variables contribute to the decision making process when developing classroom intervention procedures. A male, African-American, fifth-grade general education student was initially referred for his inappropriate vocalizations duringtime designated for independent seatwork. FBA data suggested that this behavior was being reinforced with teacher attention. Additional data showed that he was failing to complete his assignments. An intervention was implemented (...) where the student was given assignments one a time. He was instructed to solicit teacher attention and his next assignment after completing each assignment. Analysis ofteacher ratings for inappropriate vocalizations and assignment performance data suggest that the intervention was effective in increasing assignment completion and decreasing inappropriate verbalizations. Discussion focuses on how the various data playa role in the development and implementation of classroom intervention procedures. (shrink)

The current behavioral consultation case demonstrates how functional behavioral assessment (FBA) data, basic and applied research, teacher preferences, and contextual variables contribute to the decision making process when developing classroom intervention procedures. A male, African-American, fifth-grade general education student was initially referred for his inappropriate vocalizations duringtime designated for independent seatwork. FBA data suggested that this behavior was being reinforced with teacher attention. Additional data showed that he was failing to complete his assignments. An intervention was implemented (...) where the student was given assignments one a time. He was instructed to solicit teacher attention and his next assignment after completing each assignment. Analysis ofteacher ratings for inappropriate vocalizations and assignment performance data suggest that the intervention was effective in increasing assignment completion and decreasing inappropriate verbalizations. Discussion focuses on how the various data playa role in the development and implementation of classroom intervention procedures. (shrink)

Our study considers the governance, ethics and operational challenges associated with the acquisition, manipulation and commodification of ‘big data’ in the financial services sector. To the best of our knowledge, there are no published studies describing empirical research undertaken within companies in this sector to understand how they are responding to such challenges: our field-based research is a significant initial contribution in this respect. We describe the results of a micro-ethnographic study undertaken in a small-to-medium-sized company developing disruptive, technology-related (...) platforms and services in the banking and retail sectors based on big data and associated analytics: these are used to derive commercially valuable insights from personal customer data in exchange for cash back and targeted rewards. The company was found to employ a multi-level innovation governance approach, underpinned by an ethical strategy based on a principle of mutual benefit. Opt-in and informed consent for using data for specific purposes was supported by principles of data minimisation and anonymisation, with unrestricted use of secondary, anonymised and aggregated data to develop insights. Governance, which included contextual data protection legislation, payment-card industry data usage standards and internal corporate controls, presented as bespoke organisational practices relating to data security and privacy. These in total set the governance and ethics frame for big data innovation at the company within which it has had to be both adaptive and responsive under conditions of normative and regulatory uncertainty. (shrink)

Digital transformation and “artificial intelligence (AI)”—which can more adequately be called “data-based systems (DS)”—comprise ethical opportunities and risks. Therefore, it is necessary to identify precisely ethical opportunities and risks in order to be able to benefit sustainably from the opportunities and to master the risks. The UN General Assembly has recently adopted a resolution aiming for ‘safe, secure and trustworthy artificial intelligence systems’. It is now urgent to implement and build on the UN General Assembly Resolution. Allowing humans and (...) the planet to flourish sustainably in peace and guaranteeing globally that human dignity is respected not only offline but also online, in the digital sphere, and in the domain of DS, requires two policy measures: (1) human rights-based data-based systems (HRBDS): HRBDS means that human rights serve as the basis of digital transformation and DS. (2) International Data-Based Systems Agency (IDA): IDA should be established at the UN as a platform for cooperation in the field of digital transformation and DS, fostering human rights, security, and peaceful uses of DS, as well as a global supervisory institution and regulatory authority in digital transformation and DS. The establishment of IDA is realistic because humanity has already shown in its past that we are able to not always “blindly” pursue the technically possible but also to limit ourselves to what is technically feasible when humanity and the planet are at stake. For instance, humans researched the field of nuclear technology, developed the atomic bomb, and detonated it several times. Nonetheless, the same humans limited research and development in the field of nuclear technology to prevent even worse consequences by establishing the International Atomic Energy Agency (IAEA) at the UN. (shrink)

Engineering sketches and drawings are the building blocks of technological design and production. These visual representations act as the means for organizing the design to production process, hence serving as a "social glue" both between individuals and between groups. The author discusses two main capacities such visual representations serve in facilitating distributed cognition in team design work As conscription devices, they enlist and organize group participation. As boundary objects, they facilitate the reading of alternative meanings by various groups involved in (...) the design process. The introduction of computer-aided design into this visual culture of engineering restructures relationships between workers in ways that can hamper the flexibility necessary for these crucial capacities to take place. The data are drawn from a study of the daily practices of engineers engaged in redesigning a turbine engine package. The method is participant observation. (shrink)

Thirty-Five Years of Research on Neuro-Linguistic Programming. NLP Research Data Base. State of the Art or Pseudoscientific Decoration? The huge popularity of Neuro-Linguistic Programming therapies and training has not been accompanied by knowledge of the empirical underpinnings of the concept. The article presents the concept of NLP in the light of empirical research in the Neuro-Linguistic Programming Research Data Base. From among 315 articles the author selected 63 studies published in journals from the Master Journal List of ISI. (...) Out of 33 studies, 18.2% show results supporting the tenets of NLP, 54.5% - results non-supportive of the NLP tenets and 27.3% brings uncertain results. The qualitative analysis indicates the greater weight of the non-supportive studies and their greater methodological worth against the ones supporting the tenets. Results contradict the claim of an empirical basis of NLP. (shrink)

Data mining’s primary clustering method has several uses, including gene analysis. A set of unlabeled data is divided into clusters using data features in a clustering study, which is an unsupervised learning problem. Data in a cluster are more comparable to one another than to those in other groups. However, the number of clusters has a direct impact on how well the K-means algorithm performs. In order to find the best solutions for these real-world optimization issues, (...) it is necessary to use techniques that properly explore the search spaces. In this research, an enhancement of K-means clustering is proposed by applying an equilibrium optimization approach. The suggested approach adjusts the number of clusters while simultaneously choosing the best attributes to find the optimal answer. The findings establish the usefulness of the suggested method in comparison to existing algorithms in terms of intra-cluster distances and Rand index based on five datasets. Through the results shown and a comparison of the proposed method with the rest of the traditional methods, it was found that the proposal is better in terms of the internal dimension of the elements within the same cluster, as well as the Rand index. In conclusion, the suggested technique can be successfully employed for data clustering and can offer significant support. (shrink)

Contributing to a rising number of Critical Data Studies which seek to understand and critically reflect on the increasing datafication and digitalisation of governance, this paper focuses on the field of school monitoring, in particular on digital data infrastructures, flows and practices in state education agencies. Our goal is to examine selected features of the enactment of datafication and, hence, to open up what has widely remained a black box for most education researchers. Our findings are based on (...) interviews conducted in three state education agencies in two different national contexts, thus addressing the question of how the datafication and digitalisation of school governance has not only manifested within but also across educational contexts and systems. As our findings illustrate, the implementation of data-based school monitoring and leadership in state education agencies appears as a complex entanglement of very different logics, practices and problems, producing both new capabilities and powers. Nonetheless, by identifying different types of ‘doing data discrepancies’ reported by our interviewees, we suggest an analytical heuristic to better understand at least some features of the multifaceted enactment of data-based, increasingly digitalised governance, within and beyond the field of education. (shrink)

Ethical problems are related to computer data bases, containing data on individuals and groups of persons, as well as to computer knowledge bases, containing general rules and elements of expert systems.In the present essay the following conclusions are made regarding computer data bases: privacy, security, and confidentiality of medical computer data bases should be ensured. This duty should rest with physicians in hospitals. The principle of informed consent should be applied to gathering (...) information which is to be stored and processed by computers. Information stored in computer data bases should not be used for purposes for which the subjects (patients as well as personnel) have not given their consent. In order to decrease the possibility of misuses of medical data bases containing information on individuals, these registers should not be linked to other central data bases. (shrink)

The results of numerous research studies have revealed that the style in which people deliver their speech impacts on the way they are perceived by others. This is particularly so in the adversarial courtroom, where witnesses' credibility is crucial for winning a case. When witnesses do not speak the language of the courtroom, interpreters are employed to interpret the proceedings accurately. The meaning of `accuracy', however, may not be fully understood by all involved. This article presents the results of a (...) data-based study of Spanish—English court proceedings where it was found that interpreters tend to accurately interpret only the content of witnesses' answers, but constantly alter the style of testimony, either favourably or detrimentally, thus potentially changing the outcome of the case. (shrink)

Discipline and Punish analyzes the role of collecting, managing, and operationalizing data in disciplinary institutions. Foucault’s discussion is compared to contemporary forms of surveillance and security practices using algorithmic data processing. The article highlights important similarities and differences regarding the way data processing plays a part in subjectivation. This is also compared to Deleuzian accounts and Foucault’s later discussion in Security, Territory, Population. Using these results, the article argues that the prevailing focus on transparency and accountability in (...) the discussion of algorithmic applications needs to be amended with a perspective on different forms of subjectivity and ensuing power relations. (shrink)

The business environment is increasingly uncertain due to the rapid development of disruptive information technologies, the changing global economy, and the COVID-19 pandemic. This brings great uncertainties to investors to predict the performance changes and risks of companies. This research proposes a sequential data-based framework that aggregates data from multiple sources including both structured and unstructured data to predict the performance changes. It leverages data generated from the early risk warning system in China stock market to (...) measure and predict organization performance changes based on the risk warning status changes of public companies. Different from the models in existing literature that focus on the prediction of risk warning of companies, our framework predicts a portfolio of organization performance changes, including business decline and recovery, thus helping investors to not only predict public company risks, but also discover investment opportunities. By incorporating sequential data, our framework achieves 92.3% macro-F1 value on real-world data from listed companies in China, outperforming other static models. (shrink)

Computerized medical personal registers are created for administrative purposes but are frequently used in research. It can be shown that this divergence of aims deeply affects the validity of the diagnosis in register research. The diagnostic process is embedded within the process of creating the data base. This process is guided by the aims for making diagnosis.Five different aims for making diagnosis in clinical practice have been analysed and eight suggestions for validity control are proposed on the basis of (...) the study. (shrink)

The annotated dataset is an essential requirement to develop an artificial intelligence system effectively and expect the generalization of the predictive models and to avoid overfitting. Lack of the training data is a big barrier so that AI systems can broaden in several domains which have no or missing training data. Building these datasets is a tedious and expensive task and depends on the domains and languages. This is especially a big challenge for low-resource languages. In this paper, (...) we experiment and evaluate many various approaches on sentiment analysis problems so that they can still obtain high performances under limited training data. This paper uses the preprocessing techniques to clean and normalize the data and generate the new samples from the limited training dataset based on many text augmentation techniques such as lexicon substitution, sentence shuffling, back translation, syntax-tree transformation, and embedding mixup. Several experiments have been performed for both well-known machine learning-based classifiers and deep learning models. We compare, analyze, and evaluate the results to indicate the advantage and disadvantage points of the techniques for each approach. The experimental results show that the data augmentation techniques enhance the accuracy of the predictive models; this promises that smart systems can be applied widely in several domains under limited training data. (shrink)

Research on privacy practices in digital environments has oftentimes discovered a paradoxical relationship between users’ discursive appraisal of privacy and their actual practices: the “privacy paradox.” The emergence of this paradox prompts us to conduct ethnography of a health and fitness platform in order to flesh out the structural mechanisms generating this paradox. We provide an ethnographic analysis of surveillance capitalism in action that relates front-end practices empirically to the data economy’s back-end operations to show how this material-semiotic setup (...) elicits users’ desire to become self-determined subjects in a way that makes them amenable as objects of behavioral engineering. We combine different ethnographic methods and materials to specify how different types of values are produced and translated on the investigated platform. The latter offers users the values of self-mastery and social visibility. However, the data generated in this process serve to translate these values into the value of economic amenability and thereupon ultimately into economic profit. What gets lost in translation, though, is the front-end promise of self-mastery. It is these structural mechanisms that generate the privacy paradox in the first place. (shrink)

The present paper argues that neither the autophenomenological nor the heterophenomenological approach works in order to do justice to the reality of experiences, because neither approach escapes phenomenological scepticism. By regarding the potentials of neuroscience and transpersonal psychology in addition to analysing the epistemology of experiencing, it is argued that an interdisciplinary-transpersonal psychological method is preferable that covers first- second- and third-person accounts. Furthermore, it is argued that, in order to make such an approach fruitful for interdisciplinary research, a pragmatic (...) view of reality that takes experiences seriously is needed. (shrink)

We now know the structures of over 200 proteins to atomic resolution. Despite the impressive extent and quality of the results, crystal‐structure analysis has often been thought of as limited in scope, not only in its restriction to samples that can be crystallized, but in the more important respect that taking ‘snapshots’ of proteins does not directly address the complex spatio‐temporal organization of the processes in which proteins participate. It is suggested here that, as the field has matured, this second (...) limitation is gradually being overcome. As we gain increased access to structures of proteins in different conformational states – for example, in conformations produced by different states of ligation – and to families of homologous proteins, we can proceed from the statics of protein structure to the dynamics of conformational change, function, and evolution.A new scientific speciality has grown up around the solved structures: it has as its goal the elucidation of general principles of protein structure and function, to provide a theoretical framework for understanding the properties of proteins revealed by experiment. In this article we shall discuss some of the activity in this field. It will emerge clearly, I believe, that the increasing number and variety of solved structures is exerting a cumulative force. General principles are emerging from comparisons of related proteins and contrasts of dissimilar ones: the whole corpus of data is greater than the sum of the parts. (shrink)

This paper focuses on the theme of the application of deep learning in the field of basketball sports, using research methods such as literature research, video analysis, comparative research, and mathematical statistics to explore deep learning in real-time analysis of basketball sports data. The basketball posture action recognition and analysis system proposed for basketball movement is composed of two parts serially. The first part is based on the bottom-up posture estimation method to locate the joint points and is used (...) to extract the posture sequence of the target in the video. The second part is the analysis and research of the action recognition algorithm based on the convolution of the space-time graph. According to the extracted posture sequence, the basketball action of the set classification is recognized. In order to obtain more accurate and three-dimensional information, a multitraining target method can be used in training; that is, multiple indicators can be detected and feedback is provided at the same time to correct player errors in time; the other is an auxiliary method, which is compared with ordinary training. The method can actively correct technical movements, train players to form muscle memory, and improve their abilities. Through the research of this article, it provides a theoretical basis for promoting the application of deep learning in the field of basketball and also provides a theoretical reference for the wider application of deep learning in the field of sports. At the same time, the designed real-time analysis system of basketball data also provides more actual reference values for coaches and athletes. (shrink)

The laser chaos decision maker has been demonstrated to enable ultra-high-speed solutions of multiarmed bandit problems or decision-making in the GHz order. However, the underlying mechanisms are not well understood. In this paper, we analyze the chaotic dynamics inherent in experimentally observed laser chaos time series via surrogate data and further accelerate the decision-making performance via parameter optimization. We first evaluate the negative autocorrelation in a chaotic time series and its impact on decision-making detail. Then, we analyze the decision-making (...) ability using three different surrogate chaos time series to examine the underlying mechanism. We clarify that the negative autocorrelation of laser chaos improves decision-making and that the amplitude distribution of the original laser chaos time series is not optimal. Hence, we introduce a new parameter for adjusting the amplitude distribution of the laser chaos to enhance the decision-making performance. This study provides a new insight into exploiting the supremacy of chaotic dynamics in artificially constructed intelligent systems. (shrink)

First Published in 2005. Routledge is an imprint of Taylor & Francis, an informa company.

Logic-based approaches to legal problem solving model the rule-governed nature of legal argumentation, justification, and other legal discourse but suffer from two key obstacles: the absence of efficient, scalable techniques for creating authoritative representations of legal texts as logical expressions; and the difficulty of evaluating legal terms and concepts in terms of the language of ordinary discourse. Data-centric techniques can be used to finesse the challenges of formalizing legal rules and matching legal predicates with the language of ordinary parlance (...) by exploiting knowledge latent in legal corpora. However, these techniques typically are opaque and unable to support the rule-governed discourse needed for persuasive argumentation and justification. This paper distinguishes representative legal tasks to which each approach appears to be particularly well suited and proposes a hybrid model that exploits the complementarity of each. (shrink)

The use of Internet to aid research practice has become more popular in the recent years. In fact, some believe that Internet surveying and electronic data collection may revolutionize many disciplines by allowing for easier data collection, larger samples, and therefore more representative data. However, others are skeptical of its usability as well as its practical value. The paper highlights both positive and negative outcomes experienced in a number of e-research projects, focusing on several common mistakes and (...) difficulties experienced by the authors. The discussion focuses on ethics and review board issues, recruitment and sampling techniques, technological issues and errors, and data collection, cleaning, and analysis. (shrink)

Data-driven technologies have come to pervade almost every aspect of business life, extending to employee monitoring and algorithmic management. How can employee privacy be protected in the age of datafication? This article surveys the potential and shortcomings of a number of legal and technical solutions to show the advantages of human rights-based approaches in addressing corporate responsibility to respect privacy and strengthen human agency. Based on this notion, we develop a process-oriented model of Privacy Due Diligence to complement existing (...) frameworks for safeguarding employee privacy in an era of Big Data surveillance. (shrink)