You know how it’s better to have a discussion with someone when you’re calm and they haven’t just done something that drives you absolutely nuts? Well I’m going to generalize to the parenting advice realm: best time to give parenting advice is not when you’ve just seen a kid get poorly parented or a parent stress out about stupid stuff. Best time is when you’re alone in your pajamas, nowhere near other people’s kids. That way those of you who have kids won’t feel defensive.
Also, here’s another rule about parenting advice: never take parenting advice from anyone, because the people who are actually eager to give it are usually super weird. Look at Tiger Mom as Exhibit A.
In spite of that very wise second rule, I’ma go ahead and give some advice that’s pretty good, if I do say so myself in my own weird way.
- Before having kids, think of all the reasons not to. They’re loud, expensive, and they weigh you down immensely. You will never be able to stay up with friends after 10pm again if you do it. So don’t do it.
- Unless… unless you just absolutely cannot help it because of all those freaking hormones and how cute they look in summer dresses (boys included, yes, they don’t care, they’re babies). Then do it, but think hard and plan well for the noise, the expense, and the inconvenience.
- In terms of how you parent a baby: think long-term about stuff. Are you gonna want to get up a million times every night for the rest of your life? No, you’re not. So figure out how to get the damn baby to sleep through the night. This cannot be forced until the kid is 6 months or so, and the moment you can manipulate their sleep is characterized by the moment they can try to manipulate their sleep and stay awake to hang out with you. That’s when you start the 6pm bedtime ritual, including songs and books and 6:30 lights out. They will cry for like 10 minutes three nights in a row and after that you will be golden. Long term thinking, remember. Even if they cry for an hour, it’s an investment for a lifetime, namely yours.
- In terms of how you parent a little kid: think super long-term about stuff. Don’t raise your voice unless they are doing something actually dangerous, like walking into traffic or sticking a fork into an outlet. Make sure you let them get really dirty and try to eat weird things, too – their tongues are like extra hands at this age, it helps them explore the world. The only thing a little kid really needs is regular meals and a 6 or maybe 7pm bedtime ritual. They can spend 2 hours ripping up a newspaper for entertainment. Once a week baths would be good.
- In terms of how you parent a school age kid: think super duper long-term about stuff. If you do their homework for them, they will never do it themselves. So let them figure that out, but do remind them to do it if they’re forgetful. If you structure all their time, they will never figure out what they love to do, so make sure they get bored sometimes. Keep lots of good books and nerdy puzzles and interesting people around the house but don’t make them “do math” with you unless they ask for it. Don’t make them take music lessons. Instead, wait for them to beg for music lessons, and then say no for a while until you’re really sure they want them. Don’t just tell them to be nice, exhibit nice behavior to them and to others in front of them. Reward them for pointing out your hypocrisies, and make them watch Star Trek: The Next Generation (or equivalent) with you for its moral education and for the popcorn, and have fun listening to them pointing out the bad physics. And the most important of all: enjoy them and have fun with them, because that’s the best kind of way to role model for your kids, plus it’s fun, and they’re people who will move away pretty soon and you’ll miss them.
- In terms of how you parent an older kid, I have no idea because my oldest kid is 14. But so far we’re having a blast. I’m pretty sure they’re already mostly raised in terms of my role anyway by the time they’re 12.
One last, general thing for today’s anxious parents: don’t feel guilty, you’re doing your best. Guilt is a waste of time and gets in the way of enjoying the popcorn.
A tiny article in The Cap Times was recently published (hat tip Jordan Ellenberg) which describes the existence of a big data model which claims to help filter and rank school teachers based on their ability to raise student test scores. I guess it’s a kind of pre-VAM filtering system, and if it was hard to imagine a more vile model than the VAM, here you go. The article mentioned that the Madison School Board was deliberating on whether to spend $273K on this model.
One of the teachers in the district wrote her concerns about this model in her blog and then there was a debate at the school board meeting, and a journalist covered the meeting, so we know about it. But it was a close call, and this one could have easily slipped under the radar, or at least my radar.
Even so, now I know about it, and once I looked at the website of the company promoting this model, I found links to an article where they name a customer, for example in the Charlotte-Mecklenburg School District of North Carolina. They claim they only filter applications using their tool, they don’t make hiring decisions. Cold comfort for people who got removed by some random black box algorithm.
I wonder how many of the teachers applying to that district knew their application was being filtered through such a model? I’m going to guess none. For that matter, there are all sorts of application screening algorithms being regularly used of which applicants are generally unaware.
It’s just one example of the dark matter of big data. And by that I mean the enormous and growing clusters of big data models that are only inadvertently detectable by random small-town or small-city budget meeting journalism, or word-of-mouth reports coming out of conferences or late-night drinking parties with VC’s.
The vast majority of big data dark matter is still there in the shadows. You can only guess at its existence and its usage. Since the models themselves are proprietary, and are generally deployed secretly, there’s no reason for the public to be informed.
Let me give you another example, this time speculative, but not at all unlikely.
Namely, big data health models arising from the quantified self movement data. This recent Wall Street Journal article entitled Can Data From Your Fitbit Transform Medicine? articulated the issue nicely:
Consumer wearables fall into a regulatory gray area. Health-privacy laws that prevent the commercial use of patient data without consent don’t apply to the makers of consumer devices. “There are no specific rules about how those vendors can use and share data,” said Deven McGraw, a partner in the health-care practice at Manatt, Phelps, and Phillips LLP.
The key is that phrase “regulatory gray area”; it should make you think “big data dark matter lives here”.
When you have unprotected data that can be used as a proxy of HIPAA-protected medical data, there’s no reason it won’t be. So anyone who wants stands to benefit from knowing health-related information about you – think future employers who might help pay for future insurance claims – will be interested in using big data dark matter models gleaned from this kind of unregulated data.
To be sure, most people nowadays who wear fitbits are athletic, trying to improve their 5K run times. But the article explained that the medical profession is on the verge of suggesting a much larger population of patients use such devices. So it could get ugly real fast.
Secret big data models aren’t new, of course. I remember a friend of mine working for a credit card company a few decades ago. Her job was to model which customers to offer subprime credit cards to, and she was specifically told to target those customers who would end up paying the most in fees. But it’s become much much easier to do this kind of thing with the proliferation of so much personal data, including social media data.
I’m interested in the dark matter, partly as research for my book, and I’d appreciate help from my readers in trying to spot it when it pops up. For example, I remember begin told that a certain kind of online credit score is used to keep people on hold for customer service longer, but now I can’t find a reference to it anywhere. We should really compile a list at the boundaries of this dark matter. Please help! And if you don’t feel comfortable commenting, my email address is on the About page.
I’m going to write one of those posts where many of you will already understand my point. In fact it might be old hat for a majority of my readers, yet it’s still important enough for me to mention just in case there are a few people out there who don’t know how the modern business model is set up.
Namely, like this. As a gmail and Google Search user, you are not a customer of Google. You are the product. The customers of Google are the ones who advertise to you. Your interaction with Google is, from the perspective of the business operation, that you give them information which they harvest so they can advertise to you in a more targeted way, thus increasing the likelihood of you clicking. The fact that you get a service from these interactions is great, because it means you’ll come back to give Google and its customers more information about you soon.
This misunderstanding, once you see it as such, can be clarifying. For example, when people talk about anti-trust and Google, they should talk about whether the customers of Google have any other serious choice. And since the customers of Google are advertisers, not gmailers or searchers, the alternatives aren’t hotmail or Bing. Rather they are other advertising outlets. And a very good case can be made that Google does violate anti-trust laws in that sense, just ask Nathan Newman.
It also explains why something like the recent European “right to be forgotten” law seems so strange and unreasonable to the powers that be at Google. It’d be like a meat farm where the cows go on strike and demand better food. Cows are the product, and they aren’t supposed to complain. They’re not even supposed to be heard. At worst we treat them better when our customers demand it, not when the cows do.
I was reminded about this ubiquitous business model yesterday, and newly enraged by its consequences, when reading this article entitled Held Captive by Flawed Credit Reports (hat tip Linda Brown) about the credit score agency Experian and how they utterly disregard the laws trying to protect consumers from mistakes in their credit reports. The problem here is that, to the giant company Experian, its customers are giant companies like Verizon which send credit score requests millions of times a day and pay for each score. Mere people, whose mortgage application is being denied because of mistakes, are the product, not the customer, and they are almost by definition unimportant.
And it seems that the law which is supposed to protect these people, namely the Fair Credit Reporting Act, first passed in 1970, doesn’t have enough teeth behind it to make the big credit scoring agencies sit up and pay attention. It’s all about the scale of the fines compare to the scale of the business. This is well explained in the article (emphasis mine):
Last year, the Federal Trade Commission found that 5 percent of consumers — or an estimated 10 million people — had an error on one of their credit reports that could have resulted in higher borrowing costs.
The F.T.C., which oversees the industry along with the Consumer Financial Protection Bureau, has been busy bringing cases in this arena. Since 2000, it has filed 18 enforcement actions against reporting bureaus; 13 were district court actions that generated $25.7 million in penalties.
Consumers have also won in the courts, on occasion. Last year, an Oregon consumer was awarded $18.4 million in punitive damages by a jury after she sued Equifax for inserting errors into her credit report. But the fines, settlements and judgments paid by the larger companies are not even close to a rounding error. Experian generated $4.8 billion in revenue for the year ended March 2014, and its after-tax profit of $747 million in the period was more than twice its 2013 figure.
Million versus billion. It seems like the cows don’t have much leverage.
This is a guest post by Nathan, who recently finished graduate school in math, and will begin a post-doc in the fall. He loves teaching young kids, but is still figuring out how to motivate undergraduates.
Like most mathematicians in academia, I’m teaching calculus in the fall. I taught in grad school, but the syllabus and assignments were already set. This time I’ll be in charge, so I need to make some design decisions, like the following:
- Are calculators/computers/notes allowed on the exams?
- Which purely technical skills must students master (by a technical skill I mean something like expanding rational functions into partial fractions: a task which is deterministic but possibly intricate)?
- Will students need to write explanations and/or proofs?
I have some angst about decisions like these, because it seems like each one can go in very different directions depending on what I hope the students are supposed to get from the course. If I’m listing the pros and cons of permitting calculators, I need some yardstick to measure these pros and cons.
My question is: what is the goal of a college calculus course?
I’d love to have an answer that is specific enough that I can use it to make concrete decisions like the ones above. Part of my angst is that I’ve asked many people this question, including people I respect enormously for their teaching, but often end up with a muddled answer. And there are a couple stock answers that come to mind, but each one doesn’t satisfy me for one reason or another. Here’s what I have so far.
To teach specific tasks that are necessary for other subjects.
These tasks would include computing integrals and derivatives, converting functions to power series or Fourier series, and so forth.
Intuitive understanding of functions and their behavior.
This is vague, so here’s an example: a couple years ago, a friend in medical school showed me a page from his textbook. The page concerned whether a certain drug would affect heart function in one way or in the opposite way (it caused two opposite effects), and it showed a curve relating two involved parameters. It turned out that the essential feature was that this curve was concave down. The book did not use the phrase “concave down,” though, and had a rather wordy explanation of the behavior. In this situation, a student who has a good grasp of what concavity is and what its implications are is better equipped to understand the effect described in the book. So if a student has really learned how to think about concavity of functions and its implications, then she can more quickly grasp the essential parts of this medical situation.
To practice communicating with precision.
I’m taking “communication” in a very wide sense here: carefully showing the steps in an integral calculation would count.
I have issues with each of these as written. I don’t buy number 1, because the bread and butter of calculus class, like computing integrals, isn’t something most doctors or scientists will ever do again. Number 2 is a noble goal, but it’s overly idealistic; if this is the goal, then our success rate is less than 10%. Number 3 also seems like a great goal, relevant for most of the students, but I think we’d have to write very different sorts of assignments than we currently do if we really want to aim for it.
I would love to have a clear and realistic answer to this question. What do you think?
After recording my weekly Slate Money podcast this morning I will be off to the Clearwater Festival in Croton-on-Hudson. The weather’s supposed to be gorgeous all weekend, which is good because I’m camping in a tent, and the last few times I went to bluegrass or folk festivals and camped in a tent it rained and I ended up sleeping in puddles. If you’ve never done that, let me tell you that there’s something gross and creepy about wet pillows.
My bandmate Jamie, who plays the mandolin and washboard, convinced me not only to go but to be a volunteer at this festival, which as it turns out means I’ll be preparing food in the kitchen. There are 1,000 volunteers at this festival, so who knows how many people go; I’m preparing for a lot of diced carrots and onions no matter what. Or maybe I’ll be doing dishes. I love doing dishes for some reason.
So this Clearwater Festival was Pete Seeger’s baby, he came every year, and since he passed away this past winter, the entire weekend will be a tribute to his life and his work. Some incredible musicians are going to be there to honor Pete, and I am hoping my kitchen duties don’t conflict with my old favorite, Marty Sexton (Sunday at 4pm), as well as my new favorite, John Fullbright (Saturday at 2:30).
Stuff I’ve packed for the trip: tent, sleeping bag, pillow (dry so far), bluegrass juice (of the Jack Daniels variety), my fiddle, my banjo, a wooden bowl and utensils, and some metal coffee cups and shot glasses. Oh, and some clothes.
You should totally come by for either day or for the whole weekend if you’re nearby and in the mood for some really old hippy reminiscences! And really, who isn’t.
No time for a post this morning but go read this post by Scott Aaronson on using a PageRank-like algorithm to understand human morality and decision making. The post is funny, clever, very thoughtful, and pretty long.
My friend Chris Wiggins just sent me this recent letter by Alex “Al3x” Payne in response to this recent post by Marc Andreessen. Andreessen’s original post is entitled This is Probably a Good Time to Say That I Don’t Believe Robots Will Eat All the Jobs… and the rebuttal is entitled simply Dear Marc Andreessen.
To get a flavor of the exchange, we’ll start with this from Andreessen:
What never gets discussed in all of this robot fear-mongering is that the current technology revolution has put the means of production within everyone’s grasp. It comes in the form of the smartphone (and tablet and PC) with a mobile broadband connection to the Internet. Practically everyone on the planet will be equipped with that minimum spec by 2020.
versus this from Payne:
If we’re gonna throw around Marxist terminology, though, can we at least keep Karl’s ideas intact? Workers prosper when they own the means of production. The factory owner gets rich. The line worker, not so much.
Owning a smartphone is not the equivalent of owning a factory. I paid for my iPhone in full, but Apple owns the software that runs on it, the patents on the hardware inside it, and the exclusive right to the marketplace of applications for it.
You spent a lot of paragraphs on back-of-the-napkin economics describing the coming Awesome Robot Future, addressing the hypotheticals. What you left out was the essential question: who owns the robots?
Please read both the original post and the rebuttal in their entireties. At it’s heart, their conversation strikes me as a somewhat more contentious version of the argument I’ve had with myself about the utopia envisioned in Star Trek.
Namely, at some point we’ll have all these robots doing stuff for us, but how are we going to spread that wealth around? Who owns the robots and when are they going to learn to share? In this vision of the distant future, that critical “singularity of moral enlightenment” (SME) is never explained. I wish I could ask Captain Picard how it all went down.
It’s one thing to lack an explanation for the SME, and to consider it an aspirational quasi-religious utopian goal, but it’s another thing entirely to fail to acknowledge it.
That someone as powerful and famous as Mark Andreessen, who is personally involved in the development and nurturing of so many technology platforms, has trouble seeing the logical inconsistency of his own rhetoric can only be explained by the fact that, as the controller of such platforms, it is he who reaps their benefits. It’s yet another case of someone thinking “this system works for me therefore it is super awesome for everyone and everything, amen.”
I’m hoping Al3x’s fine response will get Marc to consider how SME is gonna happen, and when.
One of the reasons I enjoy my blog is that I get to try out an argument and then see if readers can 1) poke holes in my arguement, or 2) if they misunderstand my argument, or 3) if they misunderstand something tangential to my argument.
Today I’m going to write about an issue of the third kind. Yesterday I talked about how I’d like to see the VAM scores for teachers directly compared to other qualitative scores or other VAM scores so we could see how reliably they regenerate various definitions of “good teaching.”
The idea is this. Many mathematical models are meant to replace a human-made model that is deemed too expensive to work out at scale. Credit scores were like that; take the work out of the individual bankers’ hands and create a mathematical model that does the job consistently well. The VAM was originally intended as such – in-depth qualitative assessments of teachers is expensive, so let’s replace them with a much cheaper option.
So all I’m asking is, how good a replacement is the VAM? Does it generate the same scores as a trusted, in-depth qualitative assessment?
When I made the point yesterday that I haven’t seen anything like that, a few people mentioned studies that show positive correlations between the VAM scores and principal scores.
But here’s the key point: positive correlation does not imply equality.
Of course sometimes positive correlation is good enough, but sometimes it isn’t. It depends on the context. If you’re a trader that makes thousands of bets a day and your bets are positively correlated with the truth, you make good money.
But on the other side, if I told you that there’s a ride at a carnival that has a positive correlation with not killing children, that wouldn’t be good enough. You’d want the ride to be safe. It’s a higher standard.
I’m asking that we make sure we are using that second, higher standard when we score teachers, because their jobs are increasingly on the line, so it matters that we get things right. Instead we have a machine that nobody understand that is positively correlated with things we do understand. I claim that’s not sufficient.
Let me put it this way. Say your “true value” as a teacher is a number between 1 and 100, and the VAM gives you a noisy approximation of your value, which is 24% correlated with your true value. And say I plot your value against the approximation according to VAM, and I do that for a bunch of teachers, and it looks like this:
So maybe your “true value” as a teacher is 58 but the VAM gave you a zero. That would not just be frustrating to you, since it’s taken as an important part of your assessment. You might even lose your job. And you might get a score of zero many years in a row, even if your true score stays at 58. It’s increasingly unlikely, to be sure, but given enough teachers it is bound to happen to a handful of people, just by statistical reasoning, and if it happens to you, you will not think it’s unlikely at all.
In fact, if you’re a teacher, you should demand a scoring system that is consistently the same as a system you understand rather than positively correlated with one. If you’re working for a teachers’ union, feel free to contact me about this.
One last thing. I took the above graph from this post. These are actual VAM scores for the same teacher in the same year but for two different class in the same subject – think 7th grade math and 8th grade math. So neither score represented above is “ground truth” like I mentioned in my thought experiment. But that makes it even more clear that the VAM is an insufficient tool, because it is only 24% correlated with itself.
Every now and then when I complain about the Value-Added Model (VAM), people send me links to recent papers written Raj Chetty, John Friedman, and Jonah Rockoff like this one entitled Measuring the Impacts of Teachers II: Teacher Value-Added and Student Outcomes in Adulthood or its predecessor Measuring the Impacts of Teachers I: Evaluating Bias in Teacher Value-Added Estimates.
I think I’m supposed to come away impressed, but that’s not what happens. Let me explain.
Their data set for students scores start in 1989, well before the current value-added teaching climate began. That means teachers weren’t teaching to the test like they are now. Therefore saying that the current VAM works because an retrograded VAM worked in 1989 and the 1990′s is like saying I must like blueberry pie now because I used to like pumpkin pie. It’s comparing apples to oranges, or blueberries to pumpkins.
I’m surprised by the fact that the authors don’t seem to make any note of the difference in data quality between pre-VAM and current conditions. They should know all about feedback loops; any modeler should. And there’s nothing like telling teachers they might lose their job to create a mighty strong feedback loop. For that matter, just consider all the cheating scandals in the D.C. area where the stakes were the highest. Now that’s a feedback loop. And by the way, I’ve never said the VAM scores are totally meaningless, but just that they are not precise enough to hold individual teachers accountable. I don’t think Chetty et al address that question.
So we can’t trust old VAM data. But what about recent VAM data? Where’s the evidence that, in this climate of high-stakes testing, this model is anything but random?
If it were a good model, we’d presumably be seeing a comparison of current VAM scores and current other measures of teacher success and how they agree. But we aren’t seeing anything like that. Tell me if I’m wrong, I’ve been looking around and I haven’t seen such comparisons. And I’m sure they’ve been tried, it’s not rocket science to compare VAM scores with other scores.
The lack of such studies reminds me of how we never hear about scientific studies on the results of Weight Watchers. There’s a reason such studies never see the light of day, namely because whenever they do those studies, they decide they’re better off not revealing the results.
And if you’re thinking that it would be hard to know exactly how to rate a teacher’s teaching in a qualitative, trustworthy way, then yes, that’s the point! It’s actually not obvious how to do this, which is the real reason we should never trust a so-called “objective mathematical model” when we can’t even decide on a definition of success. We should have the conversation of what comprises good teaching, and we should involve the teachers in that, and stop relying on old data and mysterious college graduation results 10 years hence. What are current 6th grade teachers even supposed to do about studies like that?
Note I do think educators and education researchers should be talking about these questions. I just don’t think we should punish teachers arbitrarily to have that conversation. We should have a notion of best practices that slowly evolve as we figure out what works in the long-term.
So here’s what I’d love to see, and what would be convincing to me as a statistician. If we see all sorts of qualitative ways of measuring teachers, and see their VAM scores as well, and we could compare them, and make sure they agree with each other and themselves over time. In other words, at the very least we should demand an explanation of how some teachers get totally ridiculous and inconsistent scores from one year to the next and from one VAM to the next, even in the same year.
We need some ground truth, people, and some common sense as well. Instead we’re seeing retired education professors pull statistics out of thin air, and it’s an all-out war of supposed mathematical objectivity against the civil servant.
There’s been a movement to make primary and secondary education run more like a business. Just this week in California, a lawsuit funded by Silicon Valley entrepreneur David Welch led to a judge finding that student’s constitutional rights were being compromised by the tenure system for teachers in California.
The thinking is that tenure removes the possibility of getting rid of bad teachers, and that bad teachers are what is causing the achievement gap between poor kids and well-off kids. So if we get rid of bad teachers, which is easier after removing tenure, then no child will be “left behind.”
The problem is, there’s little evidence for this very real achievement gap problem as being caused by tenure, or even by teachers. So this is a huge waste of time.
As a thought experiment, let’s say we did away with tenure. This basically means that teachers could be fired at will, say through a bad teacher evaluation score.
An immediate consequence of this would be that many of the best teachers would get other jobs. You see, one of the appeals of teaching is getting a comfortable pension at retirement, but if you have no idea when you’re being dismissed, then it makes no sense to put in the 25 or 30 years to get that pension. Plus, what with all the crazy and random value-added teacher models out there, there’s no telling when your score will look accidentally bad one year and you’ll be summarily dismissed.
People with options and skills will seek other opportunities. After all, we wanted to make it more like a business, and that’s what happens when you remove incentives in business!
The problem is you’d still need teachers. So one possibility is to have teachers with middling salaries and no job security. That means lots of turnover among the better teachers as they get better offers. Another option is to pay teachers way more to offset the lack of security. Remember, the only reason teacher salaries have been low historically is that uber competent women like Laura Ingalls Wilder had no other options than being a teacher. I’m pretty sure I’d have been a teacher if I’d been born 150 years ago.
So we either have worse teachers or education doubles in price, both bad options. And, sadly, either way we aren’t actually addressing the underlying issue, which is that pesky achievement gap.
People who want to make schools more like businesses also enjoy measuring things, and one way they like measuring things is through standardized tests like achievement scores. They blame teachers for bad scores and they claim they’re being data-driven.
Here’s the thing though, if we want to be data-driven, let’s start to maybe blame poverty for bad scores instead:
I’m tempted to conclude that we should just go ahead and get rid of teacher tenure so we can wait a few years and still see no movement in the achievement gap. The problem with that approach is that we’ll see great teachers leave the profession and no progress on the actual root cause, which is very likely to be poverty and inequality, hopelessness and despair. Not sure we want to sacrifice a generation of students just to prove a point about causation.
On the other hand, given that David Welch has a lot of money and seems to be really excited by this fight, it looks like we might have no choice but to blame the teachers, get rid of their tenure, see a bunch of them leave, have a surprise teacher shortage, respond either by paying way more or reinstating tenure, and then only then finally gather the data that none of this has helped and very possibly made things worse.
This is a great book. It’s well written, clear, and it focuses on important issues. I did not check all of the claims made by the data but, assuming they hold up, the book makes two hugely important points which hopefully everyone can understand and debate, even if we don’t all agree on what to do about them.
First, the authors explain the insufficiency of monetary policy to get the country out of recession. Second, they suggest a new way to structure debt.
To explain these points, the authors do something familiar to statisticians: they think about distributions rather than averages. So rather than talking about how much debt there was, or how much the average price of houses fell, they talked about who was in debt, and where they lived, and which houses lost value. And they make each point carefully, with the natural experiments inherent in our cities due to things like available land and income, to try to tease out causation.
Their first main point is this: the financial system works against poor people (“borrowers”) much more than rich people (“lenders”) in times of crisis, and the response to the financial crisis exacerbated this discrepancy.
The crisis fell on poor people much more heavily: they were wiped out by the plummeting housing prices, whereas rich people just lost a bit of their wealth. Then the government stepped in and protected creditors and shareholders but didn’t renegotiate debt, which protected lenders but not borrowers. This is a large reason we are seeing so much increasing inequality and why our economy is stagnant. They make the case that we should have bailed out homeowners not only because it would have been fair but because it would have been helpful economically.
The authors looked into what actually caused the Great Recession, and they come to a startling conclusion: that the banking crisis was an effect, rather than a cause, of enormous household debt and consumer pull-back. Their narrative goes like this: people ran up debt, then started to pull back, and and as a result the banking system collapsed, as it was utterly dependent on ever-increasing debt. Moreover, the financial system did a very poor job of figuring out how to allocate capital and the people who made those loans were not adequately punished, whereas the people who got those loans were more than reasonably punished.
About half of the run-up of household debt was explained by home equity extraction, where people took out money from their home to spend on stuff. This is partly due to the fact that, in the meantime, wages were stagnant and home equity was a big thing and was hugely available.
But the authors also made the case that, even so, the bubble wasn’t directly caused by rising home valuations but rather to securitization and the creation of “financial innovation” which made investors believe they were buying safe products which were in fact toxic. In their words, securities are invented to exploit “neglected risks” (my experience working in a financial risk firm absolutely agrees to this; whenever you hear the phrase “financial innovation,” please interpret it to mean “an instrument whose risk hides somewhere in the creases that investors are not yet aware of”).
They make the case that debt access by itself elevates prices and build bubbles. In other words, it was the sausage factory itself, producing AAA-rated ABS CDO’s that grew the bubble.
Next, they talked about what works and what doesn’t, given this distributional way of looking at the household debt crisis. Specifically, monetary policy is insufficient, since it works through the banks, who are unwilling to lend to the poor who are already underwater, and only rich people benefit from cheap money and inflated markets. Even at its most extreme, the Fed can at most avoid deflation but it not really help create inflation, which is what debtors need.
Fiscal policy, which is to say things like helicopter money drops or added government jobs, paid by taxpayers, is better but it makes the wrong people pay – high income earners vs. high wealth owners – and isn’t as directly useful as debt restructuring, where poor people get a break and it comes directly from rich people who own the debt.
There are obstacles to debt restructuring, which are mostly political. Politicians are impotent in times of crisis, as we’ve seen, so instead of waiting forever for that to happen, we need a new kind of debt contract that automatically gets restructured in times of crisis. Such a new-fangled contract would make the financial system actually spread out risk better. What would that look like?
The authors give two examples, for mortgages and student debt. The student debt example is pretty simple: how quickly you need to pay back your loans depends in part on how many jobs there are when you graduate. The idea is to cushion the borrower somewhat from macro-economic factors beyond their control.
Next, for mortgages, they propose something the called the shared-responsibility mortgage. The idea here is to have, say, a 30-year mortgage as usual, but if houses in your area lost value, your principal and monthly payments would go down in a commensurate way. So if there’s a 30% drop, your payments go down 30%. To compensate the lenders for this loss-share, the borrowers also share the upside: 5% of capital gains are given to the lenders in the case of a refinancing.
In the case of a recession, the creditors take losses but the overall losses are smaller because we avoid the foreclosure feedback loops. It also acts as a form of stimulus to the borrowers, who are more likely to spend money anyway.
If we had had such mortgage contracts in the Great Recession, the authors estimate that it would have been worth a stimulus of $200 billion, which would have in turn meant fewer jobs lost and many fewer foreclosures and a smaller decline of housing prices. They also claim that shared-responsibility mortgages would prevent bubbles from forming in the first place, because of the fear of creditors that they would be sharing in the losses.
A few comments. First, as a modeler, I am absolutely sure that once my monthly mortgage payment is directly dependent on a price index, that index is going to be manipulated. Similarly as a college graduate trying to figure out how quickly I need to pay back my loans. And depending on how well that manipulation works, it could be a disaster.
Second, it is interesting to me that the authors make no mention of the fact that, for many forms of debt, restructuring is already a typical response. Certainly for commercial mortgages, people renegotiate their principal all the time. We can address the issue of how easy it is to negotiate principal directly by talking about standards in contracts.
Having said that I like the idea of having a contract that makes restructuring automatic and doesn’t rely on bypassing the very real organizational and political frictions that we see today.
Let me put it this way. If we saw debt contracts being written like this, where borrowers really did have down-side protection, then the people of our country might start actually feeling like the financial system was working for them rather than against them. I’m not holding my breath for this to actually happen.
My schedule nowadays is to go to the Lede Program classes every morning from 10am until 1pm, then office hours, when I can, from 2-4pm. The students are awesome and are learning a huge amount in a super short time.
So for instance, last time I mentioned we set up iPython notebooks on the cloud, on Amazon EC2 servers. After getting used to the various kinds of data structures in python like integers and strings and lists and dictionaries, and some simple for loops and list comprehensions, we started examining regular expressions and we played around with the old enron emails for things like social security numbers and words that had four or more vowels in a row (turns out that always means you’re really happy as in “woooooohooooooo!!!” or really sad as in “aaaaaaarghghgh”).
Then this week we installed git and started working in an editor and using the command line, which is exciting, and then we imported pandas and started to understand dataframes and series and boolean indexes. At some point we also plotted something in matplotlib. We had a nice discussion about unsupervised learning and how such techniques relate to surveillance.
My overall conclusion so far is that when you have a class of 20 people installing git, everything that can go wrong does (versus if you do it yourself, then just anything that could go wrong might), and also that there really should be a better viz tool than matplotlib. Plus my Lede students are awesome.
We moved to our apartment in New York almost exactly 9 years ago. I know that in part because I remember the date we moved in – June 4th, 2005 – but also because that first weekend we lived here, when we decided to try to buy some furniture for our nearly empty living room, we had to cross the Puerto Rican parade to get to Crate & Barrel on the east side of 5th Avenue. It was one of the most characteristic New York moments of my existence, and it made me feel like a real New Yorker.
About two days after moving in I figured out with my friend Michael Thaddeus (who has guest blogged hugely successfuly before) that his apartment was within direct sight of mine. We could wave to each other from our windows across both 116th and Claremont! For a suburban girl like me this was a hoot. We decided to build a string telephone at some point.
Well, we finally got around to doing it yesterday.
I live on the 9th floor, and Thads lives on the 5th floor of his apartment, so there was no chance we could throw anything up to the window on the outside. Instead Thads came over with two balls of string and two cans. For each window we lowered the string to the street with the help of someone on the street who could guide the person in the window. I actually only saw the first half of this procedure because I was tasked with holding the string after the first window and waiting for the second string to be lowered. Then the idea was we’d tie the two strings together.
So here I am, outside my building, holding a string in my hand that goes all the way up to a 9th floor building across the street. I’m also wearing my cowboy hat because it’s sunny outside, but for some reason the combination made everyone walking by stop and ask me what the hell I’m doing.
You see, there aren’t many things that can make New Yorkers talk to each other on the street, but I’ve found that holding on to very very long strings whilst wearing a ridiculous hat does the trick.
My favorite was when this middle aged Greek guy comes up to me and asks me what I’m doing, but he’s clearly hoping it’s mischievous, so I asked him to guess, and he says “You’re pulling someone’s tooth!!”.
After a while my neighbors noticed the string outside their window and got involved. And I noticed the security guard on the corner paying close attention, especially when we had both strings on the street and we were trying to tie them together, which took a while because they barely reached.
There was even a cop car silently observing that part of the experiment, but it disappeared as soon as we got it connected and Johan pulled the string taut so it was above the tree line.
After poking the strings into the cans, we tried our our string telephone. It was incredibly fun.
Aunt Pythia is super glad to be here. It’s a gorgeous day, Aunt Pythia has super fun plans that involve this place in Morristown, New Jersey, and the world is looking bright and colorful and happy. Aunt Pythia’s usual skeptical gloom has given way to rainbows and puppies (Aunt Pythia is a dog person).
Are you with me peoples?! Give it up for life! Give it up for humanity!!
Having said that, Aunt Pythia has more than her usual number of slapdowns to administer today, as you will soon see below.
Don’t be intimidated, though, folks! After watching the abuse, do your best to
think of something to ask Aunt Pythia at the bottom of the page!
Dear Aunt Pythia,
Have you seen this, combining two blog interests?
So yeah, shortest Aunt Pythia question ever. Turns out “this” is an article about yet another person who “hacked” OKCupid to find the love of their life. A male mathematician who dove headlong into the data mining of love. Ho hum.
Please also see [another earlier article], where it was a woman instead of a man. I can’t find it now because this article became so popular that it’s cockblocking my google searches. Wait, I think she gave a TED talk as well. Oh yeah here she is! And she reverse-engineered the algorithm, too. And honestly she’s telling her own story which is way more engaging than that article.
Anyhoo, here’s the thing. First of all, ew. He went on way too many dates too quickly. I’m glad he found love eventually, but let’s face it, he was making himself less receptive, not more receptive, by going on all those dates. Plus he was posing artificially based on his “mathematical research,” which came down to a clustering algorithm. Plus the woman he eventually proposed to FOUND HIM. Plus ew.
I think this reaction post said it best:
“…the idea that math (or, more broadly, “formulas”) can be used as a dating tactic is a surprisingly popular belief based on a number of very flawed premises, many of which reveal pickup artist-flavor misogynist attitudes among the nerdy white guys who champion them.”
Now given that I also have an example of a woman doing this, I’m not gonna claim it’s all about sexism (although there’s more than a veneer of nerdiness!). Rather, it’s all about the weird non-human mindset. Here’s another stab at what I’m talking about:
“But much of the language used in the story reflects a weird mathematician-pickup artist-hybrid view of women as mere data points anyway, often quite literally: McKinlay refers to identity markers like ethnicity and religious beliefs as “all that crap”; his “survey data” is organized into a “single, solid gob”; unforeseen traits like tattoos and dog ownership are called “latent variables.” By viewing himself as a developer, and the women on OkCupid as subjects to be organized and “mined,” McKinlay places himself in a perceived greater place of power. Women are accessories he’s entitled to. Pickup artists do this too, calling women “targets” and places where they live and hang out “marketplaces.” It’s a spectrum, to be sure, but McKinlay’s worldview and the PUA worldview are two stops along it. Both seem to regard women as abstract prizes for clever wordplay or, as it may be, skilled coding. Neither seems particularly aware of, or concerned with, what happens after simply getting a woman to say yes.”
So, again, it’s not just men who do this. Women who are ABSOLUTELY OBSESSED WITH FINDING MR. RIGHT also do this. They stop thinking about men as people and start thinking of them as bundles of attributes. You have to be tall! And weigh more than me! And culturally Jewish!
If you want to think about this more, and how deeply damaging it is to society and our concepts of ourselves and our expectations of the future, not to mention how we perceive children, then take a look at the book Why Love Hurts: A Sociological Explanation. It’s super fascinating.
So there you go, a long answer to a short question.
One last thing: I’m not saying that you should give up on your own algorithms and trust OKCupid’s algorithms. Far from it! I just think that the key thing is to stay human. Plus all online dating sites are asking the wrong questions, as I mentioned here.
Dear Aunt Pythia,
I’m about to start a PhD in Math at a top-ranked place. I’m pretty sure I won’t end up in academia for a variety of personal reasons (mostly that my partner is a non-academic with a job that needs to be in New York, SF, or DC). What should I be doing my first year/summer to make sure I’m in a reasonably good place for a non-academic job hunt 5 or 6 years from now?
(And to make matters more complicated, both finance and government creep me out morally, but I really want to end up somewhere with some fun, interesting mathematics.)
Higher Education, Less Professionalism
Make sure you know how to code, make sure you know how it feels to work in a company, make sure you keep your eye on what makes you feel moral and useful and interested. Oh, and read my book! I wrote it for people like you.
By the way, I’m hoping that, by the time you finish your Ph.D., there are better non-academic jobs out there for morally centered people with math skills. I’m just feeling optimistic today, I can’t explain it.
Dear Aunt Pythia,
With data science hype at an all-time high (and rising), I’ve been hearing of more and more people who are deciding to make a career change to data science. These acquaintances are smart, science-minded people, but without any background in advanced math, statistics, or computer science. An example background would be a bachelors degree in Chemistry. They are planning to take a few online courses, or a semester-long course or two, and then enter the job market.
My question is, do you think there’s a place for “data scientists” like these? Who’ve learned all the programming/machine learning/statistics they can in 3 months part-time but nothing beyond that? As someone with a strong technical background, I am skeptical that data scientists can be successfully churned out so quickly. Then again, if the hype is all it’s hyped up to be, maybe they’ll all get great jobs. Wondering what your take is.
Some Kooky Elitist Person Trying to Intuit Climate
Niiiiice sign-off! I am super proud.
Two things. First, I certainly believe that anyone who has a high general level of intelligence and works hard can learn a new field diligently. So I don’t doubt the intentions or efforts of our chemist friends.
On the other hand, do data science jobs allow for follow-up training and – even more importantly – thinking? I’m guessing some do but most don’t. So yes, I agree that for many of these people, it’s a disappointment waiting to happen. And yes, certainly 3 months training does very little. At best you can start thinking a new way, but it’s up to you to actually make things happen with that new mindset.
They might find out their job is really nothing like the job they thought they had. They might end up being excel or SQL database monkeys, or they might find out their job is a front so that the company can claim to be doing “data science.” Worst case they’re asked to audit and approve models they don’t understand which are being used in a predatory manner so they’re on the hook when shit gets real.
On the other hand, what are the options really? It’s a new field and there’s no major for it (UPDATE: there are post-bacc programs popping up everywhere, for example here and here). This is what new fields look like, a bunch of amateurs coming together trying to figure out what they’re doing. Sometimes it works brilliantly and sometimes it produces frauds who ride the hype wave because they’re good at that.
In short, stay skeptical but don’t presume that your friends and acquaintances have bad intent. Ask them probing questions, when you see them, about which above scenario they’re in, it might help them figure it out for themselves. Unless that’s creepy and/or obnoxious.
Dear Aunt Pythia,
How useful do you think “generate-and-test” results are? I am searching for good parameter settings using recent history from the last twelve days. For example, I just checked the report that is being generated and saw successful results eight times out of twelve. I actually could run a check against history, not including the last result and see how often the next result is good. Is this crazy or what?
Sleepless in Mesquite
I have never heard of “generate and test” so I googled it and found this, which honestly seems ridiculous for the following reason: how will you ever know your “solution” works?
So there is an example where it will work that illustrates my overall point. If you know that you have a line (“the solution”) and you know two (different) points that are on that line, then once you find a line with those points you know you’ve found the solution, because it’s unique.
Similarly, if you know your solution is a quadratic equation, then all you need to do is test it on three (different) points and you know you’re good.
But in general, how do you “test” a solution? Unless you are given, a priori, the form of the solution, to test your solution in general you’d need to try it on every point in the universe where you care about the solution working. That doesn’t sound like a useful approach.
I know I’m talking abstractly here, but you gave me very little to work with. In any case 8 out of 12 doesn’t sound very convincing, and 12 doesn’t sound big enough for much of anything. That is, even if you got 12 out of 12 I still wouldn’t be convinced you’re done unless I know more information.
I hope that was helpful!
One more thing which didn’t come up in my questions but I wanted to mention (hat tip David Opela): this article, entitled There’s No Such Thing As A Slut, which I also posted recently on mathbabe. Most important excerpt, as noted by a commenter, is this:
Armstrong notes that midway through their college experience, none of the women had made any friendships across the income divide.
Take a look!
Please submit your well-specified, fun-loving, cleverly-abbreviated question to Aunt Pythia!
I’m too busy this morning for a real post but I thought I’d share a few things I’m reading today.
- Matt Stoller just came out with a long review of Timmy Geithner’s book: The Con Artist Wing of the Democratic Party. I like this because it explains some of the weird politics around, for example, the Mexican currency crisis that I only vaguely knew about.
- New York Magazine has a long profile of Stevie Cohen of SAC Capital insider trading fame: The Taming of the Trading Monster.
- The power of Google’s algorithms can make or break smaller websites: On the Future of Metafilter. See also How Google Is Killing The Best Site On The Internet.
- There is no such thing as a slut.
This coming Sunday my friend Adam Reich is coming to Alternative Banking to talk about his work as the faculty director of a collaborative project this summer between Columbia’s INCITE and the OUR Walmart campaign.
The plan involves twenty students to scatter across the country, organizing and conducting oral history interviews alongside Walmart workers in five regions.
It is also, not coincidentally, the 50th anniversary of the Freedom Summer of 1964, when a bunch of volunteers including students helped register black Mississippians to vote.
Adam is an activist and a sociologist professor at Columbia. He is also an author of three books including Selling Our Souls: The Commodification of Hospital Care in the United States.
Details are as follows, and I hope you can come:
Where: Room 409 of the International Affairs Building at 118th and Amsterdam.
When: Sunday, June 8th, 2-3pm.
I am now part of the administrative bloat over at Columbia. I am non-faculty administration, tasked with directing a data journalism program. The program is great, and I’m not complaining about my job. But I will be honest, it makes me uneasy.
Although I’m in the Journalism School, which is in many ways separated from the larger university, I now have a view into how things got so bloated. And how they might stay that way, as well: it’s not clear that, at the end of my 6-month gig, on September 16th, I could hand my job over to any existing person at the J-School. They might have to replace me, or keep me on, with a real live full-time person in charge of this program.
There are good and less good reasons for that, but overall I think there exists a pretty sound argument for such a person to run such a program and to keep it good and intellectually vibrant. That’s another thing that makes me uneasy, although many administrative positions have less of an easy sell attached to them.
I was reminded of this fact of my current existence when I read this recent New York Times article about the administrative bloat in hospitals. From the article:
And studies suggest that administrative costs make up 20 to 30 percent of the United States health care bill, far higher than in any other country. American insurers, meanwhile, spent $606 per person on administrative costs, more than twice as much as in any other developed country and more than three times as much as many, according to a study by the Commonwealth Fund.
A comprehensive study published by the Delta Cost Project in 2010 reported that between 1998 and 2008, America’s private colleges increased spending on instruction by 22 percent while increasing spending on administration and staff support by 36 percent. Parents who wonder why college tuition is so high and why it increases so much each year may be less than pleased to learn that their sons and daughters will have an opportunity to interact with more administrators and staffers— but not more professors.
There are similarities and there are differences between the university and the medical situations.
A similarity is that people really want to be educated, and people really need to be cared for, and administrations have grown up around these basic facts, and at each stage they seem to be adding something either seemingly productive or vitally needed to contain the complexity of the existing machine, but in the end you have enormous behemoths of organizations that are much too complex and much too expensive. And as a reality check on whether that’s necessary, take a look at hospitals in Europe, or take a look at our own university system a few decades ago.
And that also points out a critical difference: the health care system is ridiculously complicated in this country, and in some sense you need all these people just to navigate it for a hospital. And ObamaCare made that worse, not better, even though it also has good aspects in terms of coverage.
Whereas the university system made itself complicated, it wasn’t externally forced into complexity, except if you count the US News & World Reports gaming that seems inescapable.
You might have heard about the recent study entitled Higher social class predicts increased unethical behavior. In it, the authors figure out seven ways to measure the extent to which rich people are bigger assholes than poor people, a plan that works brilliantly every time.
What they term “unethical behavior” comes down to stuff like cutting off people and cars in an intersection, cheating in a game, and even stealing candy from a baby.
The authors also show that rich people are more likely to think of greed as good, and that attitude is sufficient to explain their feelings of entitlement. Another way of saying this it that, once you “account for greed feelings,” being rich doesn’t make you more likely to cheat.
I’d like to go one step further and ask, why do rich people think greed is good? A couple of things come to mind.
First, rich people rarely get arrested, and even when they are arrested, their experiences are very different and much less likely to end up with a serious sentence. Specifically, the fees are not onerous for the rich, and fancier lawyers do better jobs for the rich (by the way, in Finland, speeding tickets are on a sliding scale depending on the income of the perpetrator). It’s easy to think greed is good if you never get punished for cheating.
Second, rich people are examples of current or legacy winners in the current system, and that feeling that they have won leaks onto other feelings of entitlement. They have faith in the system to keep them from having to deal with consequences because so far so good.
Finally, some people deliberately judge that they can afford to be assholes. They are insulated from depending on other people because they have money. Who needs friends when you have resources?
Of course, not all rich people are greed-is-good obsessed assholes. But there are some that specialize in it. They call themselves Libertarians. Paypal founder Peter Thiel is one of their heroes.
Here’s some good news: some of those people intend to sail off on a floating country. Thiel is helping fund this concept. The only problem is, they all are so individualistic it’s hard for them to agree on ground rules and, you know, a process by which to decide things (don’t say government!).
This isn’t a new idea, but for some reason it makes me very happy. I mean, wouldn’t you love it if a good fraction of the people who cut you off in traffic got together and decided to leave town? I’m thinking of donating to that cause. Do they have a Kickstarter yet?
You might notice that Aunt Pythia’s advice is getting posted later than usual. That’s because Aunt Pythia is a wee bit slow on the uptake this morning due to a mighty exciting and exhausting week followed by celebrations of said week. Please bear with her as she gives groggy, possibly irrelevant suggestions to your lovely, deeply and heartfelt questions.
And please, after reading her worse-than-usual advice this morning/ afternoon,
think of something to ask Aunt Pythia at the bottom of the page!
Dear Aunt Pythia,
I seriously consider the “Ask Aunt Pythia” series on mathbabe.org as the greatest and bloggiest thing on the blogging planet (granted, I explored only a part of it, and this is only an individual opinion).
Is this the right place to say it?
Mount Trouillet With Love
Why yes, yes it is. Thank you darling.
Dear Aunt Pythia,
As a grad student, I feel guilty constantly. Guilty that I am probably not spending enough time on my research, guilty that I don’t spend enough time on teaching, guilty that I sleep too much… You get the idea.
To have a successful academic career, how much should one be working, assuming average intelligence? Also, how should one avoid feeling guilty all the time?
A Grad Student Who Loves To Sleep
Sleep sounds like a gooooooood idea right about now, I think I will.
One of the things I don’t miss about being an academic is the constant guilt I imposed upon myself. It was all me, and I can’t blame anyone else. I can blame nothing except possibly the intense and competitive environment, which again, I chose to live in.
It was, I guess, the internal drive to write papers and stay abreast of my field, and without it I might never have done those things, but it sucked. I don’t even think I could summon up guilt feelings like that if I tried nowadays. Instead I do things out of sheer excitement about the ideas. I guess sometimes I feel frustrated that I haven’t had time to do the stuff I want to, but that frustration is definitely preferable to the old guilt. And come to think of it, a much more efficient way to work too.
My advice to you is to give yourself one day a week to do stuff that you just totally love, and banish guilt from your life. You might end up getting more done that way, and then you could expand it to two days a week, who knows. Tell me how that works for you!
p.s. Please work on your sign-offs. “AGSWLTS” means nothing to me.
p.p.s. Never skimp on sleep. Skimp on reading Aunt Pythia, but never skimp on sleep.
Dear Aunt Pythia,
I have lived in a different country in each decade of my life and currently use three different languages on an every day basis. No language do I master well, especially in speaking and listening. The doctor says that I am healthy, and I try to study and practice as much as possible. But, I have communication difficulties in any language. Should a more drastic action be taken? For example, find a job that requires more oral communication. Or, move back to my mother tongue country and try to reactivate my native language ability?
Smurf, or Schtroumpf
I just wanna start this out by saying how very much I enjoyed the smurfs as a child. It was weird, the show was never very good but I always ascribed to those little blue creatures much more interesting lives than they seemed to have. At the end of each episode I remember thinking, “and now they’ll go back to even more interesting things they do in their village in the woods with mushroom houses.”
I think that was their magic, in fact, to seem more interesting than they are. Smallish confession for Aunt Pythia readers: I have been doing my best to summon up a similar more-interesting-than-she-seems cachet pretty much all my life. That’s right, everything I’ve ever done or ever will do goes back to my fascination with the smurfs, and especially papa smurf, who always seemed wiser than even Alan Greenspan back in the day (“NOT LONG NOW!”).
As for your question, I’m of the opinion that people get good at what they focus on and what they are patient for. If you really want to focus on getting good at a given language, then you’ll need to stop moving countries and just forgive yourself for not already knowing stuff you don’t know, it will come with time. My husband, who is not particularly good with languages, has gotten really good at English since I met him 20 years ago.
Dear Aunt Pythia,
Your thoughts on the mathematical community being possibly less empathetic than average really hit home for me, because my experiences of being trans and attempting to do math have been really pretty miserable.
So with that said, let’s confront some cissexism:
Plenty of human females have penises. Trans women are female.
Plenty of human males have vaginas. Trans men are male.
(and of course such porn exists)
Talking about sexism in science is interesting. But we can (and should!) do it without erasing the experiences and existence of trans people, whose gender and sex are valid and real.
Further reading here.
Cisnormativity Is Silly
Thanks for the corrections, CIS! You are totally correct that I ignored trans women in my recent piece about female penes.
And although I strive to be empathetic, ignoring someone is a common way to be the opposite. And so I apologize, and I’ll try to be more thoughtful in the future. Thanks for writing!
Please submit your well-specified, fun-loving, cleverly-abbreviated question to Aunt Pythia!
I have been doing some reading about the Amazon/ Hachette battle and I have come to the conclusion that Amazon has become a huge bully. I also wasn’t impressed by how they treat employees, how they monitor and surveil them, and a host of other problems. For that reason I’m boycotting Amazon for my shopping as well as my blogging habits, so no more direct links.
Update: I’m actually still going to use their EC2 services as part of the Lede Program. Not sure how to avoid that actually, and I’d welcome suggestions.