Communicating with the Public About Marauding Terrorist Firearms Attacks: Results from a Survey Experiment on Factors Influencing Intention to “Run,Hide, Tell” in the United Kingdom and Denmark

Effective risk communication is an integral part of responding to terrorism, but until recently, there has been very little pre‐event communication in a European context to provide advice to the public on how to protect themselves during an attack. Following terrorist attacks involving mass shootings in Paris, France, in November 2015, the U.K. National Police Chiefs’ Council released a Stay Safe film and leaflet that advises the public to “run,” “hide,” and “tell” in the event of a firearms or weapons attack. However, other countries, including Denmark, do not provide preparedness information of this kind, in large part because of concern about scaring the public. In this survey experiment, 3,003 U.K. and Danish participants were randomly assigned to one of three conditions: no information, a leaflet intervention, and a film intervention to examine the impact of “Run, Hide, Tell” advice on perceptions about terrorism, the security services, and intended responses to a hypothetical terrorist firearms attack. Results demonstrate important benefits of pre‐event communication in relation to enhancing trust, encouraging protective health behaviors, and discouraging potentially dangerous actions. However, these findings also suggest that future communications should address perceived response costs and target specific problem behaviors. Cross‐national similarities in response suggest this advice is suitable for adaptation in other countries.     

Minimum spectral connectivity projection pursuit

Statistics and Computing - We study the problem of determining the optimal low-dimensional projection for maximising the separability of a binary partition of an unlabelled dataset, as measured by...     

Likelihood-free approximate Gibbs sampling

Likelihood-free methods such as approximate Bayesian computation (ABC) have extended the reach of statistical inference to problems with computationally intractable likelihoods. Such approaches perform well for small-to-moderate dimensional problems, but suffer a curse of dimensionality in the number of model parameters. We introduce a likelihood-free approximate Gibbs sampler that naturally circumvents the dimensionality issue by focusing on lower-dimensional conditional distributions. These distributions are estimated by flexible regression models either before the sampler is run, or adaptively during sampler implementation. As a result, and in comparison to Metropolis-Hastings-based approaches, we are able to fit substantially more challenging statistical models than would otherwise be possible. We demonstrate the sampler’s performance via two simulated examples, and a real analysis of Airbnb rental prices using a intractable high-dimensional multivariate nonlinear state-space model with a 36-dimensional latent state observed on 365 time points, which presents a real challenge to standard ABC techniques.     

Detecting Directionality in Time Series

Abstract

Directionality can be seen in many stationary time series from various disciplines, but it is overlooked when fitting linear models with Gaussian errors. Moreover, we cannot rely on distinguishing directionality by comparing a plot of a time series in time order with a plot in reverse time order. In general, a statistical measure is required to detect and quantify directionality. There are several quite different qualitative forms of directionality, and we distinguish: rapid rises followed by slow recessions; rapid increases and rapid decreases from the mean followed by slow recovery toward the mean; directionality above or below some threshold; and intermittent directionality. The first objective is to develop a suite of statistical measures that will detect directionality and help classify its nature. The second objective is to demonstrate the potential benefits of detecting directionality. We consider applications from business, environmental science, finance, and medicine. Time series data are collected from many processes, both natural and anthropogenic, by a wide range of organizations, and directionality can easily be monitored as part of routine analysis. We suggest that doing so may provide new insights to the processes.     

HIGH SCHOOL CHOICES AND THE GENDER GAP IN STEM

Women are less likely than men to graduate with a degree in science, technology, engineering, or math (STEM). We use detailed administrative data for a recent cohort of Ontario high school students, combined with data from the province's university admission system, to analyze the sources of this gap. We show that entry to STEM programs is mediated through an index of STEM readiness that depends on end‐of‐high school courses in math and science. Most of the gender gap in STEM entry can be traced to differences in the share of college entrants who are STEM‐ready; only a small share is attributable to differences in the choice of major conditional on readiness. We then use high school course data to decompose the gender gap in STEM readiness into two channels: one reflecting the gap in the fraction of high school students with the necessary prerequisites to enter STEM, the other arising from differences in the overall fractions of females and males who enter university. The gender gap in the fraction of males and females with STEM prerequisites is small. The primary driver of the gap in STEM readiness is the low rate of university entry by nonscience‐oriented males. (JEL I21, 28, I20)     

Finding your way into employment against all odds? Successful job search of refugees in Austria

Labour market entry poses enormous challenges for recently arrived refugees, ranging from language barriers, devaluation of human capital, unfamiliarity with customs of the job search process to outright discrimination. How can refugees overcome these challenges and quickly enter gainful employment? In this paper, we draw on interviews with 26 male and female refugees from Syria, Afghanistan, Iraq and Iran, conducted in 2017 and 2018, who came to Austria in 2015 and 2014 and who have successfully entered employment. We depict refugees’ own perspectives on and strategies for fast job entry and integration. Personal agency and a proactive approach of seeking and seizing opportunities are key for overcoming initial barriers and entering upon positive integration pathways. At the same time, refugees’ personal agency is essential for establishing social ties to the host society, which also play a crucial role in early labour market integration. Finally, institutions of the Austrian labour market (the ‘apprenticeship’-system) interact with refugees’ agency in most intricate ways, both setting up nearly insurmountable barriers but also providing specific opportunities for refugees.     

What might Normalisation Process Theory bring to policy implementation studies? Learning lessons and uncovering questions through a case study of the profound implementation failure of a new policing policy

Normalisation Process Theory (NPT), used nationally and internationally to explore implementation within health services research, is used for the first time within policing to understand profound policy implementation failure and to generate broader discussion of policy implementation theory. The policy in question (Police to Primary Care [P2PC]) was an intervention designed to notify GPs when women are assessed by police as at high risk of future domestic abuse. Designed to improve interagency communication, it took place amidst radical organisational change. Using qualitative interviews with domestic abuse specialist and frontline officers, this paper addresses how NPT helps to explain the (non)implementation of P2PC, how such an analysis differs from other policy implementation approaches, and what this means for our understandings of policy implementation more broadly. NPT proved useful in understanding mechanisms leading to (non)implementation of the intervention: fuzzy alignment with existing practice, faulty communication of purpose, and inattention to discretionary implementation spaces. It helped us understand why the intervention came to be invisible. Dwarfed by its organisational context, made institutionally hard to read by a lack of formal protocols, and given restricted view to police officers, it was compromised by a failure to instigate systems of organisational learning. More broadly, NPT helped reveal practices intersecting top‐down and bottom‐up implementation theory. The paper concludes by asking how NPT and theories of street‐level bureaucracy might be better used in tandem and, particularly, how this might help explorations of policy implementation where human actors are joined by technological actors in interpreting and making policy in vivo.