Did Australian legislators who were out of step w/ their constituents on the issue of same-sex marriage suffer electorally in the 2019 election? A new WP by me and @jillesheppard says "no, not to any substantively meaningful degree" drive.google.com/file/d/1X6m0Us…#teamprecisenulls
We tackle the question two ways. We look at individual level data, and find no sig. effect. -- but the individual level data is under-powered to detect an interaction effect of the kind we're interested in
We turn to aggregate data, and construct polling place catchment areas (black lines) using a ton of census districts (colours polygons)
We then interpolate area-level support for SSM, and use this to predict incumbent vote share in that polling place, given their stance on SSM
We find that if you're 13 percentage points (=1 SD) more "in-step" with your district, you gain a whopping 0.03 percentage points in vote share (95% CI: -0.31 to 0.38). Woot!
We then step back to the 2016 election, to see whether this was all priced in, and SSM-supportive politicians did better then in more supportive areas. Spoiler: they don't.
In response to UCU's Marking and Assessment Boycott (MAB), my employer @RoyalHolloway has decided to implement emergency regulations which in my view seriously call into question the rigour of degrees awarded (1/7)
The regulations include allowing marks for a module to be scaled proportionately (you did 50% of the coursework; that counts for 100%) (2/7)
(cont.) to permit an unlimited number of "allow" outcomes for modules (previously used where sickness or other extenuating circumstances affected students' performance) (3/7)
Everyone knows the most fun way to watch the World Cup is to support the more democratic nation in each game. So here, thanks to @vdeminstitute data, is your group-by-group rundown! (1/n)
We start in Group A, where the Netherlands is clearly in pole position, and Qatar clearly in last place (2/n)
In Group B, England and Wales are in a dead heat (until and unless V-Dem produces estimates of sub-state democracy), with Iran placing last. (3/n)
MRP works by modelling responses as a function of different demographic and political characteristics, and then making predictions for different voter types (2/15)
It works well when responses can be accurately predicted by these characteristics, or when you have a stupidly large sample size (3/15)
Jeremy Pocklington said that ministers had ignored civil service advice concerning the £3.9bn Towns Fund, and had instead applied [ahem!] "their own qualitative assessment" (3/n)
The basis for the claim is that the proportion of mask-wearers who hate, resent or think badly of non-mask wearers (58%) is greater than the proportion of Remainers who think badly of Leavers (33%) (p. 11 of report) (2/n)
First problem with this: in order for something to be divisive, it's got to divide society, and the more evenly it divides society, the more divisive it is. But the (short) report doesn't show what % of the population wear a mask. (3/n)