Les Carter writes points to the article, Coming apart? Cultural distances in the United States over time, Marianne Bertrand and Emir Kamenica, which states: There is a perception that cultural distances are growing, with a particular emphasis on increasing political polarization. . . . Carter writes: I am troubled by the inferences in the paper. […]

# Category: Sociology

## The bullshit asymmetry principle

Jordan Anaya writes, “We talk about this concept a lot, I didn’t realize there was a name for it.” From the wikipedia entry: Publicly formulated the first time in January 2013 by Alberto Brandolini, an Italian programmer, the bullshit asymmetry principle (also known as Brandolini’s law) states that: The amount of energy needed to refute […]

## One more reason to remove letters of recommendation when evaluating candidates for jobs or scholarships.

This is just one more sexual harassment story, newsworthy only in the man-bites-dog sense. But it reminded me of something that gets discussed from time to time, which is that we should stop using letters of recommendation to evaluate candidates for jobs or scholarships. Here’s a list of hoops that people recommend you jump through. […]

## Science as an intellectual “safe space”? How to do it right.

I don’t recall hearing the term “safe space” until recently, but now it seems to be used all the time, by both the left and the right, to describe an environment where people can feel free to express opinions that might be unpopular in a larger community, without fear of criticism or contradiction. Sometimes a […]

## A ladder of responses to criticism, from the most responsible to the most destructive

In a recent discussion thread, I mentioned how I’m feeling charitable toward David Brooks, Michael Barone, and various others whose work I’ve criticized over the years, because their responses have been so civilized and moderate. Consider the following range of responses to an outsider pointing out an error in your published work: 1. Look into […]

## Storytelling: What’s it good for?

A story can be an effective way to send a message. Anna Clemens explains: Why are stories so powerful? To answer this, we have to go back at least 100,000 years. This is when humans started to speak. For the following roughly 94,000 years, we could only use spoken words to communicate. Stories helped us […]

## “The Book of Why” by Pearl and Mackenzie

Judea Pearl and Dana Mackenzie sent me a copy of their new book, “The book of why: The new science of cause and effect.” There are some things I don’t like about their book, and I’ll get to that, but I want to start with a central point of theirs with which I agree strongly. […]

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## “The Book of Why” by Pearl and Mackenzie

Judea Pearl and Dana Mackenzie sent me a copy of their new book, “The book of why: The new science of cause and effect.” There are some things I don’t like about their book, and I’ll get to that, but I want to start with a central point of theirs with which I agree strongly. […]

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## Did she really live 122 years?

Even more famous than “the Japanese dude who won the hot dog eating contest” is “the French lady who lived to be 122 years old.” But did she really? Paul Campos points us to this post, where he writes: Here’s a statistical series, laying out various points along the 100 longest known durations of a […]

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## Did she really live 122 years?

Even more famous than “the Japanese dude who won the hot dog eating contest” is “the French lady who lived to be 122 years old.” But did she really? Paul Campos writes: Here’s a statistical series, laying out various points along the 100 longest known durations of a particular event, of which there are billions […]

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## What to do when you read a paper and it’s full of errors and the author won’t share the data or be open about the analysis?

Someone writes: I would like to ask you for an advice regarding obtaining data for reanalysis purposes from an author who has multiple papers with statistical errors and doesn’t want to share the data. Recently, I reviewed a paper that included numbers that had some of the reported statistics that were mathematically impossible. As the […]

The post What to do when you read a paper and it’s full of errors and the author won’t share the data or be open about the analysis? appeared first on Statistical Modeling, Causal Inference, and Social Science.

## What to do when you read a paper and it’s full of errors and the author won’t share the data or be open about the analysis?

Someone writes: I would like to ask you for an advice regarding obtaining data for reanalysis purposes from an author who has multiple papers with statistical errors and doesn’t want to share the data. Recently, I reviewed a paper that included numbers that had some of the reported statistics that were mathematically impossible. As the […]

The post What to do when you read a paper and it’s full of errors and the author won’t share the data or be open about the analysis? appeared first on Statistical Modeling, Causal Inference, and Social Science.

## Combining apparently contradictory evidence

I want to write a more formal article about this, but in the meantime here’s a placeholder. The topic is the combination of apparently contradictory evidence. Let’s start with a simple example: you have some ratings on a 1-10 scale. These could be, for example, research proposals being rated by a funding committee, or, umm, […]

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## Combining apparently contradictory evidence

I want to write a more formal article about this, but in the meantime here’s a placeholder. The topic is the combination of apparently contradictory evidence. Let’s start with a simple example: you have some ratings on a 1-10 scale. These could be, for example, research proposals being rated by a funding committee, or, umm, […]

The post Combining apparently contradictory evidence appeared first on Statistical Modeling, Causal Inference, and Social Science.

## Combining apparently contradictory evidence

I want to write a more formal article about this, but in the meantime here’s a placeholder. The topic is the combination of apparently contradictory evidence. Let’s start with a simple example: you have some ratings on a 1-10 scale. These could be, for example, research proposals being rated by a funding committee, or, umm, […]

The post Combining apparently contradictory evidence appeared first on Statistical Modeling, Causal Inference, and Social Science.

## Back to the Wall

Jim Windle writes: Funny you should blog about Jaynes. Just a couple of days ago I was looking for something in his book’s References/Bibliography (it along with “Godel, Escher, Bach” and “Darwin’s Dangerous Idea” have bibliographies which I find not just useful but entertaining), and ran across something I wanted to send you but I […]

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## Back to the Wall

Jim Windle writes: Funny you should blog about Jaynes. Just a couple of days ago I was looking for something in his book’s References/Bibliography (it along with “Godel, Escher, Bach” and “Darwin’s Dangerous Idea” have bibliographies which I find not just useful but entertaining), and ran across something I wanted to send you but I […]

The post Back to the Wall appeared first on Statistical Modeling, Causal Inference, and Social Science.

## “Thus, a loss aversion principle is rendered superfluous to an account of the phenomena it was introduced to explain.”

What better day than Christmas, that day of gift-giving, to discuss “loss aversion,” the purported asymmetry in utility, whereby losses are systematically more painful than gains are pleasant? Loss aversion is a core principle of the heuristics and biases paradigm of psychology and behavioral economics. But it’s been controversial for a long time. For example, […]

The post “Thus, a loss aversion principle is rendered superfluous to an account of the phenomena it was introduced to explain.” appeared first on Statistical Modeling, Causal Inference, and Social Science.

## “Thus, a loss aversion principle is rendered superfluous to an account of the phenomena it was introduced to explain.”

What better day than Christmas, that day of gift-giving, to discuss “loss aversion,” the purported asymmetry in utility, whereby losses are systematically more painful than gains are pleasant? Loss aversion is a core principle of the heuristics and biases paradigm of psychology and behavioral economics. But it’s been controversial for a long time. For example, […]

The post “Thus, a loss aversion principle is rendered superfluous to an account of the phenomena it was introduced to explain.” appeared first on Statistical Modeling, Causal Inference, and Social Science.

## Carol Nickerson explains what those mysterious diagrams were saying

A few years ago, James Coyne asked, “Can you make sense of this diagram?” and I responded, No, I can’t. At the time, Carol Nickerson wrote up explanations for two of the figures in the article in question. So if anyone’s interested, here they are: Carol Nickerson’s explanation of Figure 2 in Kok et al. […]

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