The Continuing Expansive Pressure to Hold Employers Strictly Liable for Supervisory Sexual Extortion: An Alternative Approach Based on Reasonableness

This Article offers a normative framework for how the current employer liability standards should be applied to sexual extortion claims. It analyzes the realist-formalist dichotomy in the supervisory sexual extortion context and concludes that the formalist approach is more consistent with the current employer liability standards and related policy considerations. The Article then explains how certain courts have incorrectly applied the second prong of the affirmative defense and inappropriately denied liability by failing to consider the avoidable consequences doctrine and related harm-avoidance principles upon which the second prong is based. The Article concludes by offering a framework for how these harm-avoidance principles apply in the supervisory sexual extortion context specifically, and the supervisory sexual harassment context more generally, such that employers are held liable for supervisory sexual extortion and sexual harassment under circumstances where it is reasonable to impose liability

Citizen forecasting 2020 : a state-by-state experiment

The leading approaches to scientific election forecasting in the United States consist of structural models, prediction markets and opinion polling. With respect to the last, by far the dominant mode relies on vote intention polling, e.g., “If the election were held tomorrow, who would you vote for?” However, there exists an abiding opinion polling strategy that shows a good deal of promise—citizen forecasting. That is, rather than query on vote intention, query on vote expectation, e.g., “Who do you think will win the upcoming election?” This approach has been pursued most extensively in the United Kingdom (Murr 2016) and the United States (LewisBeck and Tien 1999). Recent performance evaluations have shown that in the United Kingdom vote expectations clearly offer more predictive accuracy than vote intentions (Murr et al. forthcoming) and that in the United States vote expectations appear to be superior to an array of rival forecasting tools (Graefe 2014). However, the timing of the data collection has forced most of the studies using citizen forecasts to forecast elections ex post, i.e., after they occurred. Indeed, to date, there are only two ex ante citizen forecasting papers to have appeared before a national election (Lewis-Beck and Stegmaier 2011; Murr 2016). Both these efforts forecasted British General Elections, with Murr (2016) relatively most accurate among 12 academic forecasts (Fisher and Lewis-Beck 2016). With respect to the United States, the case at hand, none of the work has been ex ante and all studies have focused on the national level, with the exception of a lone study carried out at the state level (Murr, 2015). The latter point seems critical, since the final selection of the president takes place in the Electoral College. The citizen forecasting research here stands unique, being ex ante and focusing on the states. Utilizing survey questions on Amazon.com’s Mechanical Turk (MTurk), administered in July, we render forecasts for the November 2020 presidential contest. This experiment, which has been conducted before-the-fact and looks at the states, provides a strong test of the quality of citizen forecasting in this American election

Asking people in each state who they think will win suggests that the presidential election may be very close.

In new survey research, Andreas E. Murr and Michael S. Lewis-Beck asked people in each of the 50 states and Washington DC who they thought would win their state in the presidential election. Adding up their raw data, their survey suggests that President Trump will win re-election next week with 320 electoral votes to 218 for former Vice President, Democrat Joe Biden

Vote expectations versus vote intentions : rival forecasting strategies

Are ordinary citizens better at predicting election results than conventional voter intention polls? We address this question by comparing eight forecasting models for British general elections: one based on voters’ expectations of who will win and seven based on who voters themselves intend to vote for (including “uniform national swing model” and “cube rule” models). The data come from ComRes and Gallup polls as well as the Essex Continuous Monitoring Surveys, 1950 – 2017, yielding 449 months with both expectation and intention polls. The large sample size allows us to compare the models’ prediction accuracy not just in the months prior to the election, but over the years leading up to it. In predicting both the winning party and parties’ seat shares, we find that vote expectations outperform vote intent ions models. Vote expectations thus appear an excellent tool for predicting the winning party and its seat share

Using citizen forecasts we predict that with 362 electoral votes, Hillary Clinton will be the next president

Who will be the next US President? Some commentators have argued that voter intention polls are flawed because it is difficult to know who will actually turn out to vote. To get around this problem, Andreas Murr, Mary Stegmaier, and Michael S. Lewis-Beck use citizen forecasts, a “who do you think will win” survey question, to predict the election result

Citizen forecasting 2019: a big win for the Conservatives

The recent failures of voter intention polls to predict UK election results has led to public scepticism about the usefulness of polls. Andreas Murr, Mary Stegmaier, and Michael S. Lewis-Beck deploy an alternative approach, which focuses on which party opinion poll respondents expect to win the election (rather than just on their voting intentions). This ‘voter expectations’ model predicts a solid Johnson majority, with the Conservatives gaining 360 seats, and Labour only 190

On the Geometry of Surface Stress

We present a fully general derivation of the Laplace--Young formula and discuss the interplay between the intrinsic surface geometry and the extrinsic one ensuing from the immersion of the surface in the ordinary euclidean three-dimensional space. We prove that the (reversible) work done in a general surface deformation can be expressed in terms of the surface stress tensor and the variation of the intrinsic surface metric

Citizen forecasting suggests Macron will win a comfortable victory over Marine Le Pen

With the second round of the French presidential election just days away, what can election forecasts tell us about the likely result? Drawing on a citizen forecasting model, Andreas Murr, Yannick Dufresne, Justin Savoie, Bruno Jérôme and Michael S. Lewis-Beck write that Emmanuel Macron looks set to win a comfortable victory over Marine Le Pen

Evidence of Low-Temperature Superparamagnetism in Mn3O_{3}O_{4}$ Nanoparticle Ensembles

Please refer to the abstract within the main body of the paper