Rasmussen vs. the Rest
For the data and scripts used to generate the graphs, see https://github.com/soodoku/pollbias.
Gaurav
Town Level Data on Cable Operators and Cable Channels
I am pleased to announce the release of TV and Cable Factbook Data (1997–2002; 1998 coverage is modest). Use of the data is restricted to research purposes.
Background
In 2007, Stefano DellaVigna and Ethan Kaplan published a paper that used data from Warren’s Factbook to identify the effect
Teaching Social Science
Three goals: impart information, spur deeper thinking about the topic and the social world more generally, and inculcate care in thinking. As is perhaps clear, working toward achieving any one of these goals creates positive externalities that help achieve other goals. For instance, care in exposition, which is a necessary
Stereotypical Understanding
The paucity of women in Computer Science, Math, and Engineering in the US is justly widely lamented. Sometimes, the imbalance is attributed to gender stereotypes. But only a small fraction of men study these fields. And in absolute terms, the proportion of women in these fields is not a great
The Value of Money: Learning from Experiments Offering Money for Correct Answers
Papers at hand:
Prior et al. and Bullock et al.
Two empirical points that we learn from the papers:
1. Partisan gaps are highly variable, and the mean gap is reasonably small (without money, control condition). See also: Partisan Retrospection? (and updated on 3/2025, A Gap in Our Understanding)
Sample This: Sampling Randomly from the Streets
Say you want to learn about the average number of potholes per unit paved street in a city. To estimate that quantity, the following sampling plan can be employed:
1. Get all the streets in a city from Google Maps or OSM
2. Starting from one end of the street,
Ipso Facto: Analysis of Complaints to IPSO
Independent Press Standards Agency (IPSO) handles complaints about accuracy, etc., in the media in the U.K. Against which media organization are most complaints filed? And against which organization are the complaints most often upheld? We answer these questions using data from the IPSO website. (The data and scripts behind
Clustering and then Classifying: Improving Prediction for Crudely-labeled and Mislabeled Data
Mislabeled and crudely labeled data are common problems in data science. Supervised prediction of such data is expectedly to yield poor results—coefficients are biased, and accuracy with regard to the true label is poor. One solution to the problem is to hand-code labels of an `adequate’ sample and infer
The Missing Plot
Datasets often contain missing values. And often enough—at least in social science data—values are missing systematically. So how do we visualize missing values? After all, they are missing.
Some analysts simply list-wise delete points with missing values. Others impute, replacing missing values with mean or median. Yet others
Some Facts About PolitiFact
I assessed PolitiFact on:
1. Imbalance in scrutiny: Do they vet statements by Democrats or Democratic-leaning organizations more than statements by Republicans or Republican-leaning organizations?
2.
Batting average by party: Roughly n_correct/n_checked, but instantiated here as mean Politifact rating.
To answer the questions, I scraped the data