My shocking political quiz score

I took a political quiz today just to see what would happen. It was one of those that puts you on a Nolan chart at the end. It said I was center-left. I’ll wait for you to finish laughing.

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Is there a War on Christmas?

A lot of people seem to scoff at the notion there’s a war on Christmas. I understand why: several of the most famous news stories about people getting in trouble for saying Merry Christmas turn out to be satirical, and you have very low odds of actually meeting anyone who’s truly offended by the phrase.

On the other hand, the phenomenon of Christmas carols being erased from school musical performances was pretty real, although not universal. And many advertisements substitute the word “holiday” when they clearly mean “Christmas,” as in electronics retailers offering “holiday” sales when basically nobody is buying expensive electronics gifts in celebration of Thanksgiving or New years. (Or Duwali or Hannukah for that matter.)

Taking Christmas down a notch by pointing out it’s mostly derived from a collection of pagan rituals is increasingly popular, especially since those kinds of factoids tend to go viral on the internet, although since they’re not subjective I’m not sure it could be called evidence of the War on Christmas.

There have indeed been cases of nativity scenes being taken down. Some of these have been on public buildings, where there is a popular misconception that no religious symbolism is allowed–but it’s an understandable misconception. I wouldn’t be surprised to learn there are cases of nativity scenes being taken down from private property, though I don’t know of any specifically off the top of my head.

What about Google doodles always saying “Happy Holidays” instead of “Merry Christmas”? I’m unconvinced by these as examples of the War on Christmas since Google serves a global user base, many of whom might not celebrate Christmas even in a secular way.

So at the end of the day I think the existence of a War on Christmas depends on how you define it. I don’t think it’s a ludicrous fallacy to say such a thing is going on, but it isn’t going on in an obvious and overbearing way either.

I also think that conservatives who live in very multicultural, liberal areas are more likely to feel like they’re living in a dystopia. Conservative culture isn’t in the drinking water the way liberal culture is, so it’s easy for those people to feel isolated and put upon. If you’re inclined to scoff at the notion of a War on Christmas, you should remember that first.

The button

Somewhere out there is a person you haven’t met yet, but who you will one day meet and care deeply for, and eventually love with all your heart.

Now imagine a button. If you press it, there is an X% chance that person will be killed right after the button is pressed, even though he or she did nothing wrong. You won’t get in any legal trouble, though a lot of people might consider you a murderer.

But there’s a further catch: if you don’t press the button, your life will become much more difficult. It will be harder to do the things you want, to achieve the things you try to achieve. You will be hampered down. You will lose sleep. You will lose money. You will experience moments of intense pain.

How large a number would X have to be before you’d refuse to press the button?

Decide on a number before reading on.

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Confirmation bias in an article about gender bias

Harvard Business Review reports on a study on gender bias in the workplace. Here’s the experimental design:

We decided to investigate whether gender differences in behavior drive gender differences in outcomes at one of our client organizations, a large multinational business strategy firm, where women were underrepresented in upper management. In this company, women made up roughly 35%–40% of the entry-level workforce but a smaller percentage at each subsequent level. Women made up only 20% of people at the fourth level (the second highest at this organization).

We collected email communication and meeting schedule data for 500 employees in one office, across all five levels of seniority, over the course of four months. We then gave 100 of these individuals sociometric badges, which allowed us to track in-person behavior. These badges, which look like large ID badges and are worn by all employees, record communication patterns using sensors that measure movement, proximity to other badges, and speech (volume and tone of voice but not content). They can tell us who talks with whom, where people communicate, and who dominates conversations.

We collected this data, anonymized it, and analyzed it. Although we were not able to see the identity of individuals, we still had data on gender, position, and tenure at the office, so we could control for these factors. To retain privacy, we did not collect the content of any communications, only the metadata (that is, who communicated with whom, at what time, and for how long).

It sounds like an interesting approach, and N=100 is respectable for what they were trying to accomplish.

A “large business strategy firm” might be representative of one type of work environment, but there are many others where women are allegedly discriminated against. I’m curious why the researchers chose this type of workplace over others, and whether they think discrimination against women happens in various types of workplaces for the same reasons.

Our analysis suggests that the difference in promotion rates between men and women in this company was due not to their behavior but to how they were treated.

I wonder if they did interviews with participants after the study was over, to generate qualitative data that would have supported the analysis. Nothing like that was reported so I guess they didn’t.

Bias, as we define it, occurs when two groups of people act identically but are treated differently.

This strikes me as a very flawed definition of bias. Bias connotes an unfair treatment, but people can be treated differently for more than just how they act, as the authors flat out admit:

Bias is not only about how behavior is perceived in the office, but also includes out-of-office expectations. At this company, women tend to leave the workforce between the third and fourth level of seniority, after having been at the company for four to 10 years. This timing presents another possible hypothesis: Perhaps women decide to leave the workplace for other reasons, such as wanting to raise a family. Our data can’t determine whether this is true or not, but we don’t think this changes the argument for reducing bias.

I agree this doesn’t change the argument for reducing bias as commonly understood, but it does change the argument for reducing bias as the authors define it.

If men and women are equal stakeholders in a family, they should presumably be leaving the workforce at the same rate. But this isn’t happening.

Here the authors confuse “equal” with “identical.” A man and woman can be equal stakeholders in a family but the husband fulfills his role by working hard to put food on the table and keep the bills paid, while the wife fulfills her role by keeping house and doing most of the day-to-day child-rearing. Their roles are not identical. The aforementioned pattern is in fact so established that it’s a cliche, and I’m puzzled why the authors feign ignorance about it. Maybe it’s because that pattern grows out of our natural sexual dimorphism, fighting against which is the essence of feminism.

Previous research has also shown that men are perceived as more responsible when they have children, while women are seen as being less committed to work.

Left unsaid is whether those perceptions are based in fact. It would be inconvenient to let facts get in the way of an agenda:

One way to [reduce bias in the workplace] is to make promotions and hiring more equal.

And there it is. Gotta love the circular logic there. In related advice, one way to be the top chess player in the world to make Magnus Carlsen knock over his king whenever the two of you play each other.

Significant research suggests that mandating a diverse slate of candidates helps companies make better decisions. A study by Iris Bohnet of Harvard Kennedy School showed that thinking about candidates in groups helped managers compare individuals by performance — but when managers evaluated candidates individually they fell back on gendered heuristics.

If you have a mixed barrel of apples and oranges, and you’re going through looking for the tastiest piece of fruit, it might be easier to systematically compare one apple to one orange rather than to just grab random pieces of fruit and evaluate their flavor one after the other. It seems like that’s what the study basically found.

Another potential problem lies in workload. In this company, we measured higher workloads as individuals advanced to higher levels of seniority. This isn’t intrinsically gendered, but many social pressures push women around this age to simultaneously balance work, family, and a disproportionate amount of housework. Companies may consider how to modify expectations and better support working parents so that they don’t force women to make a “family or work” decision.

Am I misunderstanding, or are the authors calling for companies to give women less work than men at the same seniority level? And they call this a solution to gender bias??

Companies need to approach gender inequality as they would any business problem: with hard data.

The problem is, anyone can find the hard data they need to support their argument. The important part isn’t just having the data, it’s in what data you collect, how you evaluate it, and whether you’re open to updating your initial views after you and the person arguing against you agree on the source of the data and the method of analysis.

These researchers collected data about the tone of conversations and people’s physical proximity to one another, but they didn’t cross-reference it with data from interviews that might have suggested whether the bias they thought they were seeing was really there. They also didn’t disclose whether their hypotheses changed as a result of the experiment. Just because you’re collecting data doesn’t mean you’re doing science.

Most programs created to combat gender inequality are based on anecdotal evidence or cursory surveys. But to tailor a solution to a company’s specific problems, you need to seek data to answer fundamental questions such as “When are women dropping out?” and “Are women acting differently than men in the office?” and “What about our company culture has limited women’s growth?” When organizations implement a solution, they need to measure the outcomes of both behavior and advancement in the office. Only then can they transition from the debate about the causes of gender inequality (bias versus behavior) and advance to the needed stage of a solution.

I like that these researchers have introduced another approach to measuring bias, and I like that they talk about reducing bias on an organizational rather than an institutional level. But I wish they’d have used multiple approaches together to get more reliable findings, and I wish the article had resisted the clickbaity impulse to give the impression, especially in the headline, that the findings they got were universally applicable.

By the way, can’t gender inequality be caused by bias and behavior? Pitting the two against each other as mutually exclusive seems extremely disingenuous to me. We actually can’t advance to the needed stage of a solution so long as people–including even professional researchers!–are engaging in this kind of bad-faith false-dichotomizing.

When is equality?

I don’t really understand how racial equality activists measure their results. (I’ve met some who seem like they’d at least be interested in measuring them.) The most obvious way is to use statistics, but then you run into the problem of “Whose statistics?” And “What do those statistics control for?” Am I missing something?

This is what I’m missing by not having a Twitter account

I wound up reading a post on Twitter.com by looking at my brother’s Twitter page and clicking on a twittering he replied to, and then clicking on the twittering that twitterer was replying to.

At first I didn’t get it. So what? The House prioritizes all kinds of things over other things. That’s kind of a key part of their job. Then I realized there was an invisible “Isn’t that crazy?!?! What monsters!!!” at the end of the headline, that would have been clear to me had I been part of the intended audience.

And then I read the replies, and met some representatives from that audience. Below is just a sampling:

Not much else to say about this.

I do wonder if these people genuinely feel this way, or if Twittering is just catharsis for them. On the one hand, it’s hard to imagine that none of these people have a single friend or loved one who is anti-abortion or Republican. On the other hand, bubbles can be pretty thick.

Something that doesn’t make sense to me, though, is how people can go online and, using their real names, write this kind of stuff where anyone can see it? (Employers, family members, kids, etc.) This wasn’t in some dark hidden corner of Twitter, it was a single click from the page of some D-list actor’s Twitter feed that my brother subscribes to.

Do they not care? Do they have some good reason not to fear consequences? Or are they oblivious to the tone and messages in their own writing? Has Twitter.com made it easier to be oblivious?

(P.S. Yes, all the Twitterings and the hashtags that used “white” as a put-down were written by…white people.)

Trump-bashing is boring, so why are people still doing it?

I don’t understand people who are still vocally anti-Trump. It’s been passé for 2 full years at this point, yet it remains bizarrely popular to go out of your way to bash Trump, point out his flaws, etc. Don’t the people who do that get bored with themselves?

If a skunk sprays a dog just outside your window, you don’t sit there sniffing furiously and complaining for two years. You close the window.