Exorcising the Ghosts In the Marital System

A heuristic model is presented for the diagnosis and treatment of families in stress. A systems approach and psychoanalytic concepts are integrated to understand and modify dysfunctional behavior transmitted across generations .     

EARLY EVIDENCE ON RECREATIONAL MARIJUANA LEGALIZATION AND TRAFFIC FATALITIES

Over the last few years, marijuana has become legally available for recreational use to roughly a quarter of Americans. Policy makers have long expressed concerns about the substantial external costs of alcohol, and similar costs could come with the liberalization of marijuana policy. Indeed, the fraction of fatal accidents in which at least one driver tested positive for tetrahydrocannabinol has increased nationwide by an average of 10% from 2013 to 2016. For Colorado and Washington, both of which legalized marijuana in 2014, these increases were 92% and 28%, respectively. However, identifying a causal effect is difficult due to the presence of significant confounding factors. We test for a causal effect of marijuana legalization on traffic fatalities in Colorado and Washington with a synthetic control approach using records on fatal traffic accidents from 2000 to 2016. We find the synthetic control groups saw similar changes in marijuana-related, alcohol-related, and overall traffic fatality rates despite not legalizing recreational marijuana. (JEL K42, I12, I18)     

CATASTROPHE AND RATIONAL POLICY: CASE OF NATIONAL SECURITY

Predicting catastrophes involves heavy‐tailed distributions with no mean, eluding proactive policy as expected cost‐benefit analysis fails. We study US government counterterrorism policy, given heightened risk of terrorism. But terrorism also involves human behavior. We synthesize the behavioral and statistical aspects in an adversary‐defender game. Calibration to extensive data shows that where a Weibull distribution is the best predictor, US counterterrorism policy is rational (and optimal). Here, we estimate the adversary's unobserved variables, e.g., difficulty of an attack. We also find cases where the best predictor is a Generalized‐Pareto with no finite mean and rational policy fails. Here, we offer “work‐arounds”. (JEL H56, D81, C46)     

After the ‘APIcalypse’: social media platforms and their fight against critical scholarly research

ABSTRACT

In the aftermath of the Cambridge Analytica controversy, social media platform providers such as Facebook and Twitter have severely restricted access to platform data via their Application Programming Interfaces (APIs). This has had a particularly critical effect on the ability of social media researchers to investigate phenomena such as abuse, hate speech, trolling, and disinformation campaigns, and to hold the platforms to account for the role that their affordances and policies might play in facilitating such dysfunction. Alternative data access frameworks, such as Facebook’s partnership with the controversial Social Science One initiative, represent an insufficient replacement for fully functional APIs, and the platform providers’ actions in responding to the Cambridge Analytica scandal raise suspicions that they have instrumentalised it to actively frustrate critical, independent, public interest scrutiny by scholars. Building on a critical review of Facebook’s public statements through its own platforms and the mainstream media, and of the scholarly responses these have drawn, this article outlines the societal implications of the ‘APIcalypse’, and reviews potential options for scholars in responding to it.     

Extended pairwise local alignment of wild card DNA/RNA sequences using dynamic programming

Optimal string alignment is used to discover evolutionary relationships or mutations in DNA/RNA or protein sequences. Errors, missing parts or uncertainty in such a sequence can be covered with wild cards, so-called wild bases. This makes an alignment possible even when the data are corrupted or incomplete. The extended pairwise local alignment of wild card DNA/RNA sequences requires additional calculations in the dynamic programming algorithm and necessitates a subsequent best- and worst-case analysis for the wild card positions. In this paper, we propose an algorithm which solves the problem of input data wild cards, offers a highly flexible set of parameters and displays a detailed alignment output and a compact representation of the mutated positions of the alignment. An implementation of the algorithm can be obtained at https://github.com/sysbio-bioinf/swat+ and http://sysbio.uni-ulm.de/?Software:Swat+.