How do emerging technologies affect nuclear stability? In this paper, we use a quasi-experimental cyber-nuclear wargame with 580 players to explore three hypotheses about emerging technologies and nuclear stability: (1) technological uncertainty leads to preemption and escalation; (2) technological uncertainty leads to restraint; and (3) technological certainty leads to escalation through aggressive counterforce campaigns. The wargames suggest that uncertainty and fear about cyber vulnerabilities create no immediate incentives for preemptive nuclear use. The greater danger to strategic stability lies in how overconfidence in cyber exploits incentivizes more aggressive counterforce campaigns and, secondarily, how vulnerabilities encourage predelegation or automation. Both of these effects suggest worrisome relationships between cyber exploits and inadvertent nuclear use on one hand and cyber vulnerabilities and accidental nuclear use on the other hand. Together, these findings reveal the complicated relationship between pathways to escalation and strategic stability, highlighting the role that confidence and perhaps-misplaced certainty—versus uncertainty and fear—play in strategic stability.

This paper advocates for the value of open science in many areas of research. However, after briefly reviewing the fundamental principles underlying open science practices and their use and justification, the paper identifies four incompatibilities between those principles and scientific progress through applied research. The incompatibilities concern barriers to sharing and disclosure, limitations and deficiencies of overidentifying with hypothetico-deductive methods of inference, the paradox of replication efforts resulting in less robust findings, and changes to the professional research and publication culture such that it will narrow in favor of a specific style of research. Seven recommendations are presented to maximize the value of open science while minimizing its adverse effects on the advancement of science in practice.

The paper proposes that industrial-organizational (I-O) psychology will benefit greatly from expanding our research focus from predominantly individual differences to studying organizational differences. We argue here that an increased organizational frame of reference on variables of interest to I-O psychology (e.g., selection, job design, performance management (PM), work motivation) is important because it will enhance our understanding of organizational behavior and make I-O research more effective in practice. After noting some organizational-level research already being done, several examples are provided for how an organizational mindset and methods can provide new insights into traditional areas of I-O effort. Also discussed is how methodological issues that may have constrained the study of organizational differences in the past and the potential new issues such research may yield can be addressed. We conclude that the future maintenance and enhancement of the I-O psychology brand as a science–practice profession requires enhanced attention to the organization level of analysis as our frame of reference for research.

Direct numerical simulation is used to investigate effects of turbulent flow in the confined geometry of a face-centred cubic porous unit cell on the transport, clustering and deposition of fine particles at different Stokes numbers ($St = 0.01, 0.1, 0.5, 1, 2$) and at a pore Reynolds number of 500. Particles are advanced using one-way coupling and the collision of particles with pore walls is modelled as perfectly elastic with specular reflection. Tools for studying inertial particle dynamics and clustering developed for homogeneous flows are adapted to take into account the embedded, curved geometry of the pore walls. The pattern and dynamics of clustering are investigated using the volume change of Voronoi tesselation in time to analyse the divergence and convergence of the particles. Similar to the case of homogeneous, isotropic turbulence, the cluster formation is present at large volumes, while cluster destruction is prominent at small volumes and these effects are amplified with the Stokes number. However, unlike homogeneous, isotropic turbulence, the formation of a large number of very small volumes was observed at all Stokes numbers and attributed to the collision of particles with the pore wall. Multiscale wavelet analysis of the particle number density indicates that the peak of the energy density spectrum, representative of enhanced particle clustering, shifts towards larger scales with an increase in the Stokes number. Scale-dependent skewness and flatness quantify the intermittent void and cluster distribution, with cluster formation observed at small scales for all Stokes numbers, and void regions at large scales for large Stokes numbers.

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.

I have three issues I would like to add to Rotolo et al.’s (2018) arguments for research foci and with which academics must be concerned as we move forward. We must pay attention to all of what Rotolo et al. said plus at least my three additions if we are to compete with other fields playing in the talent management (TM) space. First, I will argue we have become overly concerned in our refereed outlets with theory to the detriment of validity against important organizational outcomes. Second, I will note that industrial and organizational (I-O) psychology has become fixated on individuals and their differences to the almost literal exclusion of research on the psychology of organizational phenomena. Third, I will present an argument for research on reciprocal relationships—on organizations as real systems—in an attempt to counter the left-to-right thinking in all of our research models.

There is a lively discussion as to whether debts incurred by despotic regimes and used to the detriment of the population are legally valid. This article gives a brief introduction to the concept of so-called odious debts and argues that a legal solution is not only desirable, but feasible. Subsequently, international human rights are identified as the missing link between the behaviour of the debtor state and the assessment of individual debts. Consequently, a human rights-based mechanism for the prevention of odious agreements is developed, based on an international convention annexed to this article. The convention provides that a state is classified as odious debts-prone if it is responsible for serious and systematic violations of human rights or international humanitarian law, or if its public sector is governed by severe and systemic corruption. Agreements concluded with an odious debts-prone state are void, unless the agreement complies with principles of responsible contracting as developed in this article. Finally, the scope of application of the convention and possible state parties are specified.

We emphasize that science and practice issues are equally salient when pursuing thinking and research on employee engagement. We agree with much of what the commentaries have to say, especially that organizational competitive advantage is the relevant focus of engagement research and practice and that engagement is not a new construct but one that required clarification vis-a-vis existing constructs. We also agree that state engagement can be highly variable, that disengagement needs study, that negative situations can induce engagement behaviors, that engagement surveys should yield actionable data, and that people can be hired who are more likely to be engaged. We disagree with the idea that all employee attitudes are essentially equal and that existing conceptualizations of performance make engagement behavior a nonuseful construct.

The meaning of employee engagement is ambiguous among both academic researchers and among practitioners who use it in conversations with clients. We show that the term is used at different times to refer to psychological states, traits, and behaviors as well as their antecedents and outcomes. Drawing on diverse relevant literatures, we offer a series of propositions about (a) psychological state engagement; (b) behavioral engagement; and (c) trait engagement. In addition, we offer propositions regarding the effects of job attributes and leadership as main effects on state and behavioral engagement and as moderators of the relationships among the 3 facets of engagement. We conclude with thoughts about the measurement of the 3 facets of engagement and potential antecedents, especially measurement via employee surveys.