The Outreach Habit: 50 consecutive days of doing something I'm bad at

The Goal

Every single day for the first 50 days of 2014, I forced myself to do something outside my comfort zone. And that's how I ended up having drinks with the vice president of a powerful company.

~The Outreach Habit: Everyday, I must make contact with one person that I otherwise would not have.~

Completion rate: 100%, tracked on Lift.

This usually entailed cold e-mails to people I don’t know. I wrote to the blogger Philip Guo telling him how much his article on grant writing helped me write my predoctoral fellowship, and he got back to me immediately and posted my message on his blog. I wrote to a graduate school dean proposing a collaboration- we start Monday. I got the new President of the University of Michigan to agree to speak to the MD/PhD program within 24 hours of the announcement of his selection by the Board of Regents. I also contacted dozens of alumni and other professionals to organize a series of career panels.

The Outreach Habit also included going up to a speaker after a talk. At a conference, this led to an e-mail exchange with a professor comparing data to assess the potential for a collaboration.

I suppose you could call this the Networking Habit, but I also want to get better at keeping in touch with old friends. Therefore, I wrote up a New Year's update blurb complete with photos and sent them to my friends. Many reciprocated. On really busy days, sending a quickly-modified blurb to another friend I hadn’t seen in years was a good, easy default.
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Difficult Skills = Worthwhile Skills

Why did I choose this habit?

Answer: because it’s hard. Really hard.

Or at least it's hard for me.

First, I just spent the last year maximizing my personal productivity, cultivating my ability to focus, and cutting out distractions. I wanted to focus on my science and my work. With that mindset, other people are distractions.

Second, when I started out, I had no idea how to make these meaningful, productive exchanges. The problem was that I was not used to putting myself in others’ shoes. If I was this person, why would I want to engage with this person who just sent me a random e-mail?

Solution? I tried to make these exchanges meaningful, not worrying about how incompetent I was. Once I made the decision to reach out to a particular person, I forced myself to come up with more and more reasons to make contact. I researched the person online if I didn’t know them. I thought about my own goals and what reasons they would have for wanting to help me out. I thought about each unique person and crafted an equally unique connection. With this information in hand, I could craft a meaningful (yet short) e-mail with a meaningful outcome.

But I didn’t give up just because I sucked. I wrote e-mails that were terrible and got no reply. I’m pretty sure I offended some people. I made some embarassing mistakes during public speaking events that resulted from this outreach habit. But that is part of the process. I only stuck with it because I knew that failure is actually just feedback to help me improve. This is the “get better” mindset- all that matters is that I improve. When I hit an obstacle, that’s life asking me, “are you sure you want to change?"
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Habits Change Who You Are

A week ago, I wanted to see if I truly made Outreach into a habit. So I ended this habit plan and archived the goal on Lift. 

What happened? I began seeing outreach opportunities everywhere.

I heard that the vice president of a major company was coming to the university to give a talk on careers, and I immediately pulled up her e-mail address on LinkedIn and sent her a cold e-mail asking to meet for coffee. Within 1 hour of realizing she existed, I was on her schedule. We ended up having drinks for 3 hours and bonded over intellectual discussions and hilarious personal stories.

I now encounter very little inertia when e-mailing a random big-shot and ask for a coffee meeting. They almost always say yes. I’m meeting with a Principal at Boston Consulting Group this evening- I only e-mailed him yesterday.

Given that I used to suffer from social anxiety, it’s still a little hard to believe how comfortable I’ve become at making rapid and effective connections with complete strangers. How easy it is reach out to people who I’ve been feuding with or neglecting. And how fun it is. 

It also opens up a whole new realm of possibilities. I can only reach a certain level of productivity working alone, no matter how much I improve personal skills like focus and time management. I can’t wait to see what I can make with others, working together.

Weekly Report: Discomfort Solved

This was a very interesting week to start my experiment, because I bought a condo! That obviously took a lot of time, and I faced some other personal challenges this week as well. But my scheduled bursts still allowed me to get a lot done, and my habits have taken a lot of the stress out of my life.

If you haven't read up on my new system yet, see my last blog post.

See after the calendar for the lessons I drew this week.

Report (see calendar): I met my scheduled bursts (green) on Monday, Tuesday, Friday, and Saturday without much trouble. However, on Wednesday (yellow) I had an urgent interruption related to the condo, so I simply did my burst later in the day, under non-ideal (i.e. distracted) conditions. On Thursday (red), I was simply exhuasted from the condo closing and decided to take a nap instead. Yes, I would call that poor planning, and in the future I will avoid planning bursts on days surrounding major events.

Green = success. Yellow = urgent interruption. Red = failure. Blue = other commitments.

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My new favorite thing: discomfort

But overall, I got a lot done this week. I tackled two big experiments that I had been putting off, partially because of lack of time, and partially because I was a bit fearful and didn't know where to start. However, just 1 hour of focused concentration in each case proved sufficient to break through the barrier. At the beginning, I felt stupid and perhaps a bit guilty. After that very uncomfortable hour, I knew what I needed to do, and I was able to get started on real work. And I managed to get real (and exciting) results for both of them.

This illustrates what I've known for a while, informed by bloggers like Cal Newport and Scott Young: 

~Comfort with discomfort is one of the most important skills a person can develop. Forcing yourself to persist through discomfort is critical when starting any new project. Otherwise, it is too tempting to go back to easy work that only makes you feel productive.~

Scheduled bursts are a great way to force yourself to embrace discomfort. They are time-limited, so the task no longer seems as daunting and it's easier to get started. The process of systematically eliminating distractions also helps to psychologically prepare you for the discomfort.

To facilitate getting into "the zone," I have implemented a checklist for when I start these sessions. Checklists are obviously ubiquitous, but I'm using them for two very specific reasons:

1) Mental attention: It gives my mind one less thing to keep track of. Making deliberate changes to one's productivity system itself requires mental attention, and checklists lessen that requirement. The checklist makes it easier to fully focus on the task in front of me.

2) Ritual: This tells my brain that it's time to enter a state of "deep work."

My checklist for scheduled bursts.

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Habits are investments

I won't comment much on these this week. But I've observed two things:

1) I've already begun noticing changes in how I perceive events and how I interact with people. In particular, I make much better eye contact and feel much more confident.

2) These habits are now always running in the back of mind. Thus, I can automatically activate them when appropriate.

Lift habits.

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Next week's schedule

I also noticed last week that front-ending my bursts (e.g. scheduling more towards the beginning of the week, and beginning of the day if possible) makes good use of my abundance of early-week energy. It also eliminates feelings of guilt if I have to tend to other things later in the week. This week, I have to front-end my schedule, since I will be away for a wedding Friday-Sunday.

Scheduled bursts are in orange. Other commitments are in blue. Everything else must fit into the white space.

Friday Links: DNA + dark matter, E.O. Wilson, skeleton racing

More Friday Links! 

http://www.technologyreview.com/view/428391/revolutionary-dna-tracking-chamber-could-detect/

A really cool research venture: using DNA to detect dark matter. Deep sequencing technologies require you to compactly array DNA molecules (all of different sequences) on a solid surface, and biologists have standard techniques (PCR + sequencing) to uniquely identify a DNA molecule from any given spot in the array. Guess what? That's a great setup for detecting dark matter. The hypothesis is that the Earth should be plowing through dark matter as it revolves and/or rotates, assuming that dark matter is diffusely distributed.

Essentially, here's how the DNA dark matter detector works:

1) Earth rotates, brushing through dark matter in a predictable rhythm that varies directionally throughout the day

2) DNA molecules are arrayed on a gold sheet. Dark matter can knock gold nuclei out of the sheet and into the array of DNA molecules.

3) The gold nucleus cuts a swath through the forest of DNA molecules, severing them

4) severed DNA molecules fall from the array and are collected, then amplified by PCR and sequenced so the biologists can figure out exactly which DNA molecules were severed

5) since they know where each DNA molecule was anchored, they can put together the path that the gold nucleus took

6) Match the path with the direction from which you'd expect the dark matter to be coming from at the given time of day.

One word: awesome.

http://www.ted.com/talks/e_o_wilson_advice_to_young_scientists.html

E.O. Wilson, the famed evolutionary biologist who studies eusocial organisms, advocates the kind of cross-pollination exemplified by the above DNA-dark matter example. His message to scientists-in-training: learn broadly and collaborate broadly. Too many PhDs spend all their time doing experiments in a narrow field and never venture into other areas. But they are missing out: new discoveries are found in non-intuitive connections between different fields.

One idea I had relevant to MD/PhDs was inspired by E.O. Wilson's two strategies for doing good science:

1) Medicine shows the problems. Seek to learn all the problems (literally, ALL) then look for scientific phenomena that can explain the problems and provide a means to intervene

2) Science observes phenomena without necessarily knowing if they have consequences relevant to human well-being. Seek to learn all (literally, ALL) the phenomena then look for problems that might be linked to the phenomena and apply your knowledge to the problem

http://www.freakonomics.com/2012/06/29/how-to-make-a-better-athlete/

Every sport is a unique combination of agents (players + equipment) and rules that those agents follow (official rules + rules of physics). Fortunately, that's all you need to create a model of something, with the purpose of identifying the most important factors, and to predict and explain emergent properties.

Here, Freakonomics spotlights the Australian team in the skeleton, an Olympic sledding sport. They don't have career skeleton athletes (except one) and they don't have a chance to practice because, well, they're in Australia. You might think that the skill and practice time of the athlete are the two most important factors. In fact, that might be true in most sports. But if you carefully examine the rules of the game, you'll realize that there are two components to a race: the actual sledding, and the 30-meter sprint beforehand to get the sled going. Guess what? Australia has plenty of good sprinters. And as it turns out, using a little bit of modeling, you can show that the actual sledding is of minimal importance in terms of time. Skill might prevent you from wiping out, but as long as you stay on course you're not going to shave much time off with good sledding. So instead, they focused their efforts on finding really good sprinters and training them.

The result? An Australian qualified for the Olympics within 18 months, getting in about 1/10 as much practice time as a "career skeleton athlete." Very often, working smarter is 10x than working harder. Science knows best, and conventional wisdom fails miserably.

http://www.npr.org/blogs/thetwo-way/2012/07/05/156280450/kaboom-san-diegos-entire-fireworks-show-ignites-at-once

Haha all of San Deigo's July 4 fireworks goes off all at once:

The scale of neurology is larger than the observable universe

This week, I am happy to report that I am pretty much back on track in terms of my work routine, and productivity is once again through the roof. Spelling out and publicizing my exact strategy for not wasting time on the computer definitely motivated me to adhere to it- which is the entire point of writing a blog! But I also have another motivating factor working in my favor this week- a new undergraduate just joined the lab! When I teach, I feel like I learn more than when I'm just trying to learn. Like writing, teaching someone forces me to spell out my logic as clearly as possible, which both clarifies my thinking and uncovers hidden assumptions I had been making that may be wrong. Furthermore, the best way to teach is to ask the student questions that stimulate the student's thought and lets the student figure out the answer. That means I need to put myself in the position of a beginner, so I learn more about my own field and gain insights that I might have missed. It's true that until you can teach a subject, you haven't mastered it. But what is often overlooked is that the very act of teaching something is the METHOD by which one masters something.

Yesterday, I attended the Life Sciences Institute symposium, and this year's focus was on Neuroscience. The speakers were amazing (most were HHMI), and it reminded me why I want to go into neurology. Let's just examine some of the highly attractive intellectual aspects of neurosciences

Brain-specific systems: Molecular and cellular mechanisms that are unique to the brain and, in many cases, unique to the human brain. Non-coding DNA seems to be one of the biggest things that separates us from chimpanzees- why? A lot of it might be transposons that are specifically activated in the brain to jump around and disrupt genes, so that every brain cell has different DNA- thus creating a diversity not seen in any other organ system, other than the immune system. Another thing, which I just learned from Robert Darnell, MD, PhD (Rockefeller) is that the brain has its own splicing system (Nova proteins, etc) allowing the generation of novel isoforms not seen anywhere else in the body. 20,000 genes becomes 100 or 1000 times that number because the brain can generate far more unique proteins than the rest of the body due to novel mechanisms of splicing. Furthermore, different parts of the brain have different splicing systems, and in fact different parts of the same brain cell have different splicing machinery- possibly explaining some aspects of memory assuming these are stable states. And so it also makes sense that certain cancers would co-opt the Nova system to drastically change their gene expression profiles and give them a proliferative advantage, despite the immunological risk it puts the cancer at (spontaneous regression of Nova+ cancers have been observed due to the immune response).

Combinatorial complexity: This point can be best illustrated using one of the simplest examples in neuroscience (even though really it's not simple at all). The problem is recognizing self vs. non-self. Neurons don't want to synapse onto themselves because otherwise they inhibit themselves and become useless, or they hyper-activate themselves and end up killing themselves. But how does a highly branching neuron figure out that the neuron it has reached is another neuron or another part of itself? Larry Zipursky, PhD (UCLA) has discovered how this is accomplished in the Drosophila fruit fly. The Dscam class of molecules have alternative exons at four positions. Combinatorial complexity means that 12 x 48 x 33 x 2 = 38,000 unique Dscam molecules. Furthermore, each neuron expresses a random combination of about 50 different Dscam molecules. How many different profiles thus are possible in the brain? 

38,000^50 = 10^229. That is far greater than the number of particles in the entire universe. In fact, if every particle in the universe had an entire universe inside of it, and every particle in that universe had a entire universe inside of it, 10^229 is still far larger. Now, when a Dscam group on one neuron encounters a Dscam group on either the same or another neuron, it only binds if they match sufficiently. If it binds, they inhibit each other and cause the synapse to fail. So essentially, the likelihood that two different neurons will have profiles similar enough to inhibit each other is essentially non-existent. Thus, every neuron has a unique barcode that allows its dendrites to recognize other dendrites on itself. Even cooler, the Zipursky lab systematically deleted alternative exons until they figured out how many unique Dscam molecules are required to prevent inappropriate self-synapsing and inappropriate avoidance of non-self.

Region-specific features: Let's not forget that the brain is huge. Really huge. The human brain should not be thought of as one organ system. A single brain's complexity is more on the order of the entire rest of Earth's biosphere. So one part of the brain might act under totally differently principles than its neighboring part, even though the majority of proteins are the same. So when you treat the brain with a single simple drug, it may have really awesome effects in one part, but it's going to affect everything else too, possibly adversely. Let's take dopamine as an extremely simple example. Insufficient dopamine is a cause of some Parkinson's symptoms, so dopamine therapy can have massive benefit in terms of quality of life for Parkinson's patients. But dopamine is also inappropriately elevated in an entirely different part of the brain in schizophrenia, so a potential side effect is schizophrenic-like symptoms. Conversely, treating schizophrenic patients with dopamine antagonists can have Parkinsonian side effects. 

Another example: yesterday Luis Parada, PhD (MIT) discussed his work on SSRI anti-depressant therapy. He found that the reason why SSRIs take months to work even though they cause immediate serotonin changes is that SSRIs enhance hippocampal neurogenesis over time. New neurons need to form for SSRIs to work. More interestingly, exercise seems to have the same effect- explaining why I'm always happier after exercising consistently. Furthermore, activating hippocampal neurogenesis is sufficient to reverse depression and anxiety-like symptoms in mice, and blocking neurogenesis can block the positive effects of anti-depressants and exercise. This has major implications for depression therapy, since SSRIs currently affect serotonin all of the brain, resulting in all sorts of changes that may have all sorts of adverse effects. So if we develop a drug that specifically activates hippocampal neurogenesis, we can treat depression without the side effects. Exercise should also be incorporated as a mainstay of depression therapy. Lastly, I'd like to point out that this strategy can be used for cognitive enhancement in healthy people. Meanwhile, I'm going to keep on exercising.

One reason I want to go into neurology is that there are few good therapies for any of the major neurological disorders. But I have little doubt, based on what I've heard at research talks, that major neurological therapies will reach the clinic right around the time that I start residency. Right now there are some crazy flowcharts for figuring out which patients receive which therapies. But the brain is an entirely different animal. Figuring out which patients will benefit from neurological therapies (and cognitive enhancement) will require a fundamental understanding of these intellectually challenging topics such as combinatorial complexity. Thus neurology will provide me with intellectual challenge for my entire life. My prediction that most of the diseases of other organ systems will be cured within 100 years, and medicine will become tediously boring and trivial. I doubt that neurology will be solved for another 500.

Furious curiosity, mutagenesis screens, and prosopagnosia

And my blog returns! This is important to me because I'm trying to make writing a habit, since it stimulates thought. In the past it's been really hard to keep up new habits (even the ones I feel strongly about) but I'm slowly becoming better at it. So while this might be dangerous, I will go ahead and announce my goal: two blog posts per week for the rest of the month. No matter what.

You know what else stimulates thought? Talking to people in completely different fields than your own. I just had a really good 45 minute conversation with a fellow patron at the Espresso Royale cafe. He's a humanities grad student, so given that I'm an MD/PhD student in biogerontology, it shouldn't be surprising that it was pretty varied in terms of topic (really interesting topics, to me anyways). One might think that because neither of us knew that much about each other's fields that the conversation would be superficial. But that's not what happened. I think that because we both approached the topics as beginners, our minds were working with furious curiosity, and the ideas just started flowing. Soon enough, I was explaining the nuances of the evolutionary theory behind lifespan determination, as well as how to calculate the chances of double hits in C. elegans mutagenesis screens. He understood the intuition as well as any scientist. Meanwhile, I was also taking in ideas on the influence of postmodern thought in the humanities, the origins of musical genres, and public choice theory. I ended up sometimes sticking scientific labels on things, like emergent properties and Heisenberg's uncertainty principle, but that only goes to show that the tools and concepts of one field equips you to understand other fields (cross-pollination :) ). Conclusion? The position of a beginner may be an uncomfortable place, but it's a fantastic place to grow.

Speaking of mutagenesis screens, tomorrow I get introduced to another high-throughput method in the C. elegans roundworm. I will be trying out a BioSorter, which is capable of sending worms (or zebrafish, or fruit flies, or clusters of mammalian cells) through an analyzer that can assess size and fluorescence and count and sort them (i.e. exactly like flow cytometry and FACS). Handy tool for handling large numbers of animals and systematically searching for manipulations that impact the biological process you're studying (e.g. aging).

Finally, I'll leave you with a couple of cool facts from the last book I read, The Best American Science and Nature Writing 2011, which is a collection of essays from all scientific fields (environmental science, astronomy, physics, biology, medicine). One essay by Stephen Hawking. My goal is 20 books by the end of the year, which I'm tracking on Goodreads, a social book site where you can see what your friends are reading.

1) About ten million songbirds (warblers) are killed each year in Cyprus by poachers. They are served as a delicacy called ambelopoulia. Lots of other birds can caught in the process and are simply killed. The poaching is technically illegal, but the law is minimally enforced (even prominent politicians will eat it on camera). Most interestingly, because it is illegal, most of the poachers are armed criminals somewhat analogous to drug cartels, so police officers are wary of going after them. Another example of how banning something doesn't necessarily help a situation, but instead creates a black market that is unregulated.

2) A black bear must consume 200,000 calories per day in order to have sufficient fat stores for winter hibernation.

3) Laysan albatrosses have permanent mating pairs and together nurture an egg each year. They don't stay together throughout the year but somehow manage to find each other again when mating season arrives. About 1/3 of the "mating pairs" are actually female-female pairs, as both females are fertilized by a quick mating with a male from another pair.

4) Prosopagnosia is a specific inability to recognize faces and places (agnosia is the more generalized inability to recognize objects). Usually individuals have lesioned fusiform gyruses, either by trauma or by some sort of genetic variation (some cases run in families). People with prosopagnosia usually develop tricks to get around it, recognizing other people based on gross features or context. It is believed that this is much more common than one might think, as people don't seek medical attention if they are born with it, because "that's just the way they are."

5) Kessler syndrome is the official name for the "space junk phenomenon," where it's getting increasingly dangerous in near-Earth space because of a bunch of aging equipment we've left there. The issue is that a single collision between two objects will create thousands of smaller objects that are equally dangerous, creating a catastrophic domino effect. Because of the velocities involved, one of these tiny fragments would be like a truck bomb. A 10-cm sphere of aluminum packs the punch of 7 kg of TNT.

Blog launch; people aren't that racist

Hello! I heard it's a good idea to have a (flexible) purpose in mind when starting a new venture, so here are my reasons for starting a blog- I suspect these are common to many bloggers.

1) Share things I find interesting. Usually these involve things that defy conventional wisdom (e.g. segregation, see below)

2) Share things I'm working on to improve myself. Writing it out helps me think about it, keeps me honest, invites feedback, and maybe gives others some ideas. I have so many general goals, such as reading more, keeping a diary, getting comfortable talking to strangers, pre-defining my goals for the day/week/month, etc. But I hope that having a defined task such as a blog entry will help motivate me.

3) Improve my writing skills and stimulate my mind. Pushing myself to generate interesting blog posts will force me to look into things I'm unfamiliar with.

4) Eliminate any residual fear of having my ideas be judged by others.

So, now see below for my first real blog post!

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Intro

In my free time I've been looking into the recent explosion of startups and non-profits offering online courses, including Coursera, Udacity, and edX. These offer full-semester-long courses, given by full professors at top colleges, complete with lectures, quizzes, problem sets, and final exams, and available to everyone for free. I'd argue these are going to be a lot more effective than traditional classroom learning, where half the students are on the Internet anyways NOT learning.

So right now I'm taking Model Thinking on Coursera, and I'd have to say the interface is a lot more engaging than the majority of in-person teachers I've had. The course is a personal project of Scott Page, a professor at the University of Michigan. And it's not just a video of the courses he normally teaches- you can see him directly talking to you, his pre-prepared slides, and the stuff he writes on the slides as he talks to you in real time. And yes, you can speed it up (2X max).

I hope that Model Thinking will help me think as a scientist and an intellectual, rather than just as a worm geneticist. I also like that models can lead us to unexpected conclusions, so I will share one of the first models presented in the class: Schelling's Model of Segregation.

The model

The question behind Schelling's Model of Segregation is: We all know that many (most) cities in the US are highly segregated, along lines of race, income, etc. Blacks might on average have 80% black neighbors, while whites might on average have 80% white neighbors. Why? Is it just because they are racist and like their own kind? You might think that if people want 80% of the people near them to look like them, and people are freely moving, then on average people will have 80% of their neighbors look like them. But let's do some modeling.

We have X number of people in a hypothetical city, and a grid of X homes that they can occupy. Each person is given the choice to move or stay, based on their neighborhood percentage of people who look like them, call that P. Let's say they will move to a new home if P is lower than a threshold T. In the real world, this means a person looks at his/her own neighbors, and gets a little spooked by the number of people who don't look like them, and moves. This is applied iteratively, since as one person moves that might cause others to move as well => this is a simulation.

Let's say that T is 30%. In a city of half whites and half blacks, that in fact is very much UN-racist. In fact, they would tolerate being in the MINORITY in their neighborhood. People only need 30% of their neighbors to look like them for them to stay. If you run the simulation (use a computer program), what do you get as the end result? >75% segregation. In other words, on average each person has 75% same-race neighbors.

How can this be? We already said that people don't mind being in the minority, and they are at most minimally-racist. How did we end up with major segregation without any other factors at play?

If we think carefully about the model, there are two tipping points that bias in favor of segregation. Essentially, the effect of any one person moving gets amplified.

1. Exodus Tip: A person moves out of a neighborhood. For their original same-race neighbors that may decrease their percentage below their Threshold T. For example 3/8 > 30% becomes 2/7 < 30%.
2. Genesis Tip: That person moves into a new neighborhood. For their new different-race neighbors, that may decrease their percentage below threshold T. For example 2/6 > 30% becomes 2/7 < 30%.

These are kind of common sense, but it's hard to fully appreciate the domino effect this can have.

Once one person moves, another moves, then another moves. The end result is segregation. In fact, if we only have the requirement that people don't want to be in the minority, i.e. people only want at least 50% of their neighbors to be of the same race, what happens? The end result is that 90% of a person's neighbors ends up being of the same race.

Finally, the kicker. What happens if people ARE really racist? What if they have a requirement that 95% of the people near them have to be of the same race? Here's another thing that completely defies conventional wisdom: you DON'T GET SEGREGATION!!

This blog post is getting long, so I'll let my readers figure out why HIGH LEVELS OF RACISM leads to situations where there is NO SEGREGATION.

Anticipated rebuttal

I'm sure you have a rebuttal to all this. That there are many other factors at play that might allow racism to be the primary explanation for segregation, i.e. racist laws, rent, gentrification, etc. Fair points- it is POSSIBLE for racism to explain segregation. But it is still valid to say that just because there is segregation arising from individual behavior, we shouldn't assume that individuals are racist.

Furthermore, this highlights the importance of models. This model left things like rent and gentrification out of the equation. It made some assumptions that may not be entirely true. But all that is besides the point. The act of laying out assumptions and taking them to their logical conclusion helps us think about a problem. In the end, we may end up keeping or throwing out some of our assumptions, and deciding that we need more data on the things we left out of the model. And in the end, we're all the better for it. We made progress.

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Conclusion

I hope that the models I learn the Model Thinking class will be fertile, i.e. they will be applicable to biology and medicine even though many of them were developed for economics and social science. A PhD is a fantastic time to explore all sorts of things that interest me and develop a variety of skills, because I have control over my own time. This will be an adventure, and I hope you'll join me.