The social sciences are at a remarkable confluence of events. Advances in computing have made it feasible to analyze data at the scale of the population of the world. How can we combine the depth of inquiry in the social sciences with the scale and robustness of statistics and computer science? Can we decompose complex questions in the social sciences into simpler, more robustly testable hypotheses? We discuss these questions and the role of machine learning in the social sciences.

We propose a rational method for addressing an important question—who deserves to be an author of a scientific article? We review various contentious issues associated with this question and recommend that the scientific community should view authorship in terms of contributions and responsibilities, rather than credits. We propose a new paradigm that conceptually divides a scientific article into four basic elements: ideas, work, writing, and stewardship. We employ these four fundamental elements to modify the well-known International Committee of Medical Journal (...) Editors (ICMJE) authorship guidelines. The modified ICMJE guidelines are then used as the basis to develop an approach to quantify individual contributions and responsibilities in multi-author articles. The outcome of the approach is an authorship matrix, which can be used to answer several nagging questions related to authorship. (shrink)

Mental time travel research emphasizes the connection between past and future thinking, whereas autobiographical memory research emphasizes the interrelationship of self and memory. This study explored the relationship between self and memory when thinking about both past and future events. Participants reported events from the near and distant past and future, for themselves, a close friend, or an acquaintance. Past events were rated higher in phenomenological quality than future events, and near self events were rated higher in quality than those (...) about friends. Although future events were more positive than past events, only valence ratings for self and close friend showed a linear increase in positivity from distant past to future. Content analysis showed that this increase in positivity could not be ascribed to choosing events from the cultural life script. These findings provide evidence for the role of personal goals in imagining the future. (shrink)

Basic income and basic capital are two common ideas for redesigning distribution. Basic income provides people with a regular income from government. Basic capital provides people with a lump-sum grant. An important part of scholarly debate concentrates on the merits of basic income versus basic capital. This paper claims that these debates are too narrow. First, current debates overlook the way that a chief inspiration for both ideas, Thomas Paine, wanted basic capital and basic income to be complements not substitutes. (...) Second, it is more instructive to compare basic capital or basic income with a wider set of alternatives than with each other. Widening the debates would benefit the discussion of a basic capital or basic income. (shrink)

Asset egalitarianism is a new agenda but an old idea. At its root is the notion that every citizen should be able to have an individual property stake, and it has recently been revived in Britain and in the U.S. in a number of proposals aimed at countering the huge and growing inequality in the distribution of assets. Such asset egalitarianism is fed from many streams; it has a long history in civic republican thought, beginning with Thomas Paine and Thomas (...) Jefferson, but has also featured in the distributist theories of G.K. Chesterton and Hilaire Belloc; the guild socialism of G.D.H. Cole and the ethical socialism of R.H. Tawney; the market liberalism of the Ordo Liberals and some of the Austrian School, particularly F.A. Hayek; and more recently the market socialism of James Meade, A.B. Atkinson and Julian Le Grand, and the market egalitarianism of Michael Sherraden, Samuel Bowles, Herbert Gintis, Richard Freeman and Bruce Ackerman. There are also important links to the proponents of a citizens' income as a different approach to the welfare state (White 2002) as well as to the ideas of stakeholding (Dowding et al. 2003). (shrink)

The vital data about the electrical activities of the brain are carried by the electroencephalography signals. The recordings of the electrical activity of brain neurons in a rhythmic and spontaneous manner from the scalp surface are measured by EEG. One of the most important aspects in the field of neuroscience and neural engineering is EEG signal analysis, as it aids significantly in dealing with the commercial applications as well. To uncover the highly useful information for neural classification activities, EEG studies (...) incorporated with machine learning provide good results. In this study, a Fusion Hybrid Model with Singular Value Decomposition Based Estimation of Robust Parameters is proposed for efficient feature extraction of the biosignals and to understand the essential information it has for analyzing the brain functionality. The essential features in terms of parameter components are extracted using the developed hybrid model, and a specialized hybrid swarm technique called Hybrid Differential Particle Artificial Bee algorithm is proposed for feature selection. To make the EEG more practical and to be used in a plethora of applications, the robust classification of these signals is necessary thereby relying less on the trained professionals. Therefore, the classification is done initially using the proposed Zero Inflated Poisson Mixture Regression Model and then it is also classified with a deep learning methodology, and the results are compared with other standard machine learning techniques. This proposed flow of methodology is validated on a few standard Biosignal datasets, and finally, a good classification accuracy of 98.79% is obtained for epileptic dataset and 98.35% is obtained for schizophrenia dataset. (shrink)

Covid-19 has sparked calls for a universal basic income as a way of coping with a demand shock caused by the pandemic. Temporary income payments have been part of the emergency response to the pandemic. This paper questions the effectiveness of temporary payments as a way to raise demand. Some observers claim that vouchers are better targeted at sectors hit hard by Covid-19 as people may have a tendency to save than spend from temporary payments. There may be a stronger (...) case for permanent rather than temporary payments if the aim is to boost demand in the economy. (shrink)

Two issues should be addressed to refine and extend the distinction between temporal updating and reasoning advocated by Hoerl & McCormack. First, do the mental representations constructed during updating differ from those used for reasoning? Second, are updating and reasoning the only two processes relevant to temporal thinking? If not, is a dual-systems framework sensible? We address both issues below.

This paper discusses the utilization of pilots' physiological indications such as electroencephalographic signals, ocular parameters, and pilot performance-based quantitative metrics to estimate cognitive workload. The study aims to derive a non-invasive technique to estimate pilot's cognitive workload and study their correlation with standard physiological parameters. Initially, we conducted a set of user trials using well-established psychometric tests for evaluating the effectiveness of pupil and gaze-based ocular metrics for estimating cognitive workload at different levels of task difficulty and lighting conditions. Later, (...) we conducted user trials with the NALSim flight simulator using a business class Learjet aircraft model. We analyzed participants' ocular parameters, power levels of different EEG frequency bands, and flight parameters for estimating variations in cognitive workload. Results indicate that introduction of secondary task increases pilot's cognitive workload significantly. The beta frequency band of EEG, nearest neighborhood index specifying distribution of gaze fixation, L1 Norm of power spectral density of pupil diameter, and the duty cycle metric indicated variations in cognitive workload. (shrink)

We extend some of the classical connections between automata and logic due to Büchi [5] and McNaughton and Papert [12] to languages of finitely varying functions or “signals”. In particular, we introduce a natural class of automata for generating finitely varying functions called ’s, and show that it coincides in terms of language definability with a natural monadic second-order logic interpreted over finitely varying functions Rabinovich [15]. We also identify a “counter-free” subclass of ’s which characterise the first-order definable languages (...) of finitely varying functions. Our proofs mainly factor through the classical results for word languages. These results have applications in automata characterisations for continuously interpreted real-time logics like Metric Temporal Logic Chevalier et al. [6] and [7]. (shrink)