Inflated statistics, spring admission, and the University of Southern California

A significant number of USC students do not enter as freshmen in the fall. The university offers alternative enrollment options to inflate incoming freshmen statistics and make their student-body appear higher-quality than it actually is.

Something about USC doesn’t add up.

Every fall approximately 3,200 wide-eyed freshmen matriculate. They were admitted from a pool of more than 60,000 applicants and are among the best of what high schools in the 21st-century have to offer. In 2019, the middle 50% range of their SAT scores was 1360-1530. The same stat for GPAs was 3.72 – 3.99. Roughly 20% of enrollees have rèsumès good enough to warrant merit scholarships.

This is impressive. For most of its history, USC was academically underpowered. It was better known for its football team and fraternities than serious study until the university launched a status-raising campaign in the 2000s. Now, some of the brightest high-schoolers in the country become Trojans.

But look closer. For the 2019-2020 academic year, USC claims to have around 20,500 undergraduates enrolled. If approximately 3,200 freshmen enroll every year, and that has been the case for the last 4 years, then USC should only have 3,200 * 4 = 12,800 students. In fact, if you sum the actual number of freshmen that USC reports matriculated in fall 2016, 2017, 2018, and 2019, you only get 3,068 + 3,358 + 3,401 + 3,168 = 12,995 students.

Where is everybody? If we grant that the 20,500 figure is correct, then there are roughly 7,000 students at USC who are unaccounted for on this naive model. In other words, it’s not obvious how almost 35% of the student body got into USC, or how they compare academically to their peers.

In the next section, I want to establish that the freshmen/total enrollment discrepancy at USC is real and significant compared to similar institutions. Afterward, we will discuss possible explanations for the gap.

1. The discrepancy

1.1 Methodology

The guiding thought is we should be able to get reasonably close to a university’s reported undergraduate population by counting all the students they say enroll. For instance, if a university says they enroll 250 freshmen each year, we might expect their total number of undergrads to be around 1,000. Students should graduate in 4 years, so the only people on campus should be those who enrolled 1, 2, 3, or 4 years ago.

If only college was that simple. There are good reasons why the simple calculation I just described will be inaccurate. Not everybody finishes their degree in 4 years, so students who enrolled 5 or 6 years ago might still be on campus. Matriculating class sizes might vary dramatically over that period as well. Adding a couple of numbers together also can’t account for people like dropouts and transfers who might affect the size of a student body.

We can account for all of these concerns. Many universities (including USC) publish their matriculating class sizes on their websites, either part of the Common Data Set or other statistics they distribute. The same schools also frequently publish the number of transfers they receive. As a result, we can get an exact sense of student inflow over the past 4 years.

We can also roughly approximate the number of students who take more than 4 years to graduate. Universities publish 6 and 4 year graduation rates as part of the Student Right-to-Know Act. From these figures, we can estimate the number of students in a freshmen cohort who graduate on time. We assume the rest of the students in the cohort graduate in 5 or 6 years, getting an idea of how many people who enrolled more than 4 years ago contribute to the student population.

(I acknowledge this is an overcount since some students who don’t graduate in 4 years drop out. Yet, note that overcounts are in USC’s favor. Our naive calculations show there are 7,000 missing students, so any fudgery that accounts for more undergrads helps them).

Handling dropouts who enrolled in the past 4 years is tricky but doable. Universities don’t publish the exact number of students who drop out and when, so making any kind of exact calculation is difficult. For instance, a freshman enrolling in 2015 might count towards undergrad enrollment in 2015, 2016, and 2017, but then drop out. If we knew what percent of a freshmen cohort dropped out every year, we could just “thin” their class accordingly and be done with it.

Our strategy is to perform two sets of calculations. The first assumes everybody that enrolls eventually finishes their degree. This is a “best-case scenario” and will give us an upper bound on the student body. Imagine the student who enrolls in 2015 but drops out in 2017. If we’re trying to calculate undergraduate population in 2018 under the assumption of no dropouts, she’s going to be counted even though she’s no longer enrolled. As a result, if we pretend every freshman sticks around and eventually graduates, we’re going to overshoot the number of people actually on campus by tallying people that have already left school.

The second set of calculations gives us a “worst-case scenario.” We assume everyone who will drop out does so the moment they set foot on campus. The proportion of a freshmen cohort that drops out can be approximated via published graduation rates. In our minds, those who will drop out are counted as enrolled freshmen and then disappear. If we’re doing these calculations for 2018, they will not count our hypothetical student who drops out in 2017. In fact, they wouldn’t count her in 2015, 2016, or 2017, even though she was enrolled then. Under this assumption, we get a lower bound on the student body by ignoring attendees who will eventually drop out, even if they are still enrolled.

With rough upper and lower bounds, we can be reasonably confident the number of students we can trace back to freshmen enrolled in the fall or transfers lies somewhere between the two figures. Roughly, the bounds will be computed as follows:

Upper bound = (number of freshmen enrolled over last 4 years) + (transfers from last 2 years) + (students who take 5-6 years to graduate from freshmen cohorts 5 and 6 years ago)

Lower bound = (number of freshmen expected to graduate who enrolled over the last 4 years) + (transfers from last 2 years) + (students who take 5-6 years to graduate from freshmen cohorts 5 and 6 years ago)

What’s left is to compile the data, run the numbers, and see if the bounds on the number of students we can trace back differ significantly from the number of undergrads a university says it has.

1.2  Numbers

By looking through a combination of Common Data Sets, enrollment reports, and university fact pages, I was able to gather the necessary data and compute lower and upper bounds for 8 schools, including USC. In an effort to compare apples to apples, I tried to include schools that are private and similarly sized. Data for those institutions aren’t always available, so the sample also includes public schools of similar size, and smaller, private ones (with UCLA thrown in for good measure).

Below is a table with the 8 schools and their respective reported undergraduate enrollments.

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Table 0

Using the ideas outlined in the previous section, we calculate the number of students traceable to either freshmen or transfer enrollment. The next table displays the upper and lower bounds as a percentage of the undergraduate population.

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Table 1. For details on how upper and lower bounds were calculated, consult Appendix A.

Let’s look at the University of Virginia (UVA) to start. If we add up all the students the University says have enrolled as freshmen in the past 4 years, adjust for students that enrolled 5 and 6 years ago who are taking extended time, and assume nobody drops out, we can account for 102.38% of the students on campus. If we assume all the freshmen that are going to drop out do so immediately, we can account for 97.91% of the students on campus. In this case, our upper and lower bounds contain the number of reported students. This is a sign as our method does a decent job of predicting how many undergrads a university should have given the numbers they publish.

However, this does not always happen. A percentage greater than 100 indicates an overshoot. For instance, if we assumed all the students we expected were going to drop out of Baylor did so immediately, we should expect their undergraduate population to be 114% of their current one.

As Table 1 suggests, our method does not yield pinpoint accuracy. We don’t hit actual undergraduate population numbers exactly, but two things are notable. First, our new model tends to overshoot. Half of the schools in the sample have lower bounds that are greater than stated enrollment, and the lower bounds of two more come within 8% of the actual figure. The upper bounds of 6 schools are well over 100%, or very close. This suggests there may be outflows of students I haven’t considered, leading to systemic overcounts.

The second feature is BU and USC are outliers. BU comes reasonably close in the upper bound, but its lower bound is nearly 15% below stated enrollment. USC is even worse. Its upper bound is 83.99%, which is even lower than BU’s lower bound. Remember, 83.99% as an upper bound means we can only account for that percentage of students if we make the rosy assumption nobody drops out. USC’s lower bound also dips into the 70s, which is far worse than any other school considered.

USC, and to a lesser extent, BU, have notable discrepancies between their published freshmen/transfer numbers and total enrollments. Their published student inflows do not come close to accounting for the students they have. The fact USC and BU’s freshmen/transfer enrollment numbers under predict student population — when the model overshoots considerably for other schools — suggests something is afoot.

2. Explanations

There are two general ways to account for USC and BU’s enrollment discrepancies. The first is to claim they’ve made a mistake. For one reason or another, the reasoning goes, both universities don’t have a grip on either their total enrollment or the number of freshmen/transfers that enroll every year. This could be caused by problems with their internal systems, apathy, or communication issues.

I don’t think this is plausible. For one thing, knowing how many freshmen enroll is crucial to universities. Tuition is a large source of revenue, so institutions invest a lot in ensuring incoming cohorts have the correct size and socioeconomic makeup. Unexpected freshmen yields can also lead universities to rescind acceptances, which is bad for students and administrators alike. Along the same lines, it seems unlikely a university also doesn’t know how many total undergraduates they have. Every student is a paying customer, so I’d imagine schools would know the size of a major income source.

Deceit is also a possibility, but if schools are lying about their enrollments, we have a much larger problem than can be discussed in this blog post. For that reason, I will not consider it.

The second general explanation is USC and BU have additional student inflows that aren’t matriculating freshmen or transfers. This sounds strange: doesn’t everyone enroll as either a fall freshman or a transfer? How else are you admitted to a school?

It turns out there’s a third way. USC and BU both admit applicants for the spring semester. This means a high school senior submits their application like everyone else, but instead of being invited to campus in August, the earliest they can enroll is the following January. In USC’s case, we know spring admits aren’t tallied in the freshmen numbers I used to compute the upper and lower bounds. In their matriculating freshmen reports, they are strangely specific in talking about fall admits and fall enrolls.

We can test if spring admits account for the missing students at USC. According to their admissions blog, USC enrolls between 500 and 600 spring freshmen every year. Let’s be conservative and assume the number is 500 while supposing the practice has been active for the last 4 years. We can account for this in our model by adding 500 to every fall matriculating class going back to 2016.

Table 2 demonstrates the new upper and lower bounds with this assumption. Consult Appendix A for details on how the bounds were computed.

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Table 2

There’s improvement. 93.74% as an upper bound approaches respectability, but 87.89% as a lower one is still concerning.

At this point in my investigation, I thought there has to be a table where spring admits show up in USC’s Common Data Set. It records everything from Pell Grant recipients to the number of philosophy degrees conferred, so spring admits need to be recorded somewhere, if not under the name.

That’s when the “Other first-year, degree-seeking” row in Section B of USC’s Common Data Set caught my eye. According to the definitions table in the back of the document, “Other first-year, degree-seeking” undergraduates are students that have completed fewer than 30 semester hours (units) and are seeking to graduate at the university in question. These are contrasted with “Degree-seeking, first-time, freshmen” who are undergraduates in their first year that have not attended a prior postsecondary institution. In other words, “Degree-seeking, first-time, freshmen” are traditional freshmen. “Other first-year, degree-seeking” students are freshmen that have attended a prior institution.

Two pieces of evidence that suggest this row in the Common Data Set counts spring admits. First, USC recommends spring admits to go to community college or study abroad during the fall semester. On their website, they say “most first-year spring admits choose to enroll in community college during the fall.” For the cosmopolitans (or those that can afford it), they even have fall-semester programs in places like Rome and Prague at partner universities exclusively for USC spring admits.

The second piece is the actual values in the “Other first-year, degree-seeking” row. As mentioned, USC says between 500 and 600 spring admits enroll every year. It turns out, for the last 3 years, the number of “Other’s” has been around 600, with a spike 4 years ago. If we update our upper and lower bounds by adding the number of “Other’s” to the freshmen enrollment numbers for the last 4 years, we get the following:

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Table 3

We’re much closer. Our upper bound is nearly 100%, and the lower one is a respectable 93.63%. For USC, I’m more confident than not the “Others” row approximates their spring admits. As a result, I believe USC’s policy of offering spring admission more or less explains the apparent discrepancy between matriculating freshmen numbers and total undergraduate enrollment.

If what I’m saying is correct, we can follow an identical process with BU and create better upper and lower bounds. Yet, there are slight differences that prevent this. BU’s “Other” rows are often in the low teens. This means very few freshmen have attended a prior institution before landing at BU. However, I attribute this to the nature of their spring admission policy. It appears almost all delayed admits arrive at BU as part of the College of General Studies (CGS). This is a 2-year program where students arrive in the winter, take classes, and then study abroad for the summer after their freshman year. On the CGS FAQ, they recommend students spend their gap semester volunteering, working, traveling, or taking a class. The next entry in the FAQ explicitly prohibits CGS students from enrolling in another institution for the fall semester. If students want to take non-degree courses during the fall, BU advises them to consult their CGS academic advisor.

In other words, BU does not present taking classes during fall as an attractive option. For this reason, I am not surprised the “Other” row in their Common Data Set is so low. Yet, we can still update our bounds by taking into account the number of first-year CGS students. From their website, they claim to enroll approximately 600 students annually. If we add 600 to every freshmen class going back 4 years, our new bounds are:

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Table 4

These look similar to bounds created for other institutions. Taking delayed admissions into account, we can resolve BU’s apparent discrepancy between freshmen enrollment and total undergraduate population. As mentioned, I believe the same is true of USC. Every year, both schools enroll around 600 freshmen during the second semester.

3. Motives

I believe USC and BU do this to inflate the statistics of their freshmen classes. The thought is if they can exclude academically weaker students from matriculating in the fall, their student-body will appear better and more selective than it actually is. After all, spring admits aren’t included in the fancy documents USC spins up for their “Class of 202X” promotions, and I doubt CGS statistics are included in BU materials. Based on my calculations, USC could have inflated their admit rate by ~1.3% in 2018. Consult Appendix B for the exact methodology.

Colleges have another incentive to delay admission for weaker students. US News and World Report uses the test scores and high school GPAs of first-time, first-year students who enter in the fall to calculate their rankings. If students are admitted in the spring, their statistics are irrelevant from US News’ perspective. This means spring admission is a way for schools to shield weaker students from prying eyes. Every year, the high-school performance of around 600 USC and BU freshmen is not considered when calculating college rankings. Put differently, 15% of their entering class is invisible to those who want to discern the academic quality of the average Trojan or Terrier. I would be surprised if including that 15% helped USC or BU’s cause.

Deirdre Fernandes, reporting in the Boston Globe, describes the phenomena.

Many of the students targeted for delayed admissions would have traditionally been wait listed or rejected because their test scores or grades may not have been as strong as other applicants. But since these students aren’t counted as part of the entering fall class, their academic histories don’t weigh down the school’s overall average for that particular year.

There is also a wealth dimension.

The freshmen who come in likely wouldn’t have been accepted for the traditional freshman class because their grades weren’t as strong, but they are usually wealthier and can afford to pay for a spot without relying on financial aid from the school.

Put bluntly,

“The college banks on the fact that the student wants to go there,” said Todd Weaver, a vice president with Strategies for College Inc., a Norwood-based private counseling firm. “This student might not be a best fit, but their bank account is.”

In addition to being academically weaker than traditional admits, it appears colleges also target the students that can afford to pay full freight. Observational evidence stands in favor of this point for USC. To be clear, I do not have data on USC spring admit income. Yet, of the three students who gave testimonials about their spring admit experience on USC’s delayed admission page, two went to $40,000 a year college prep high schools. This is far from damning evidence, but it is suggestive.

I acknowledge there are non-deceitful reasons why a university might offer spring admission. For instance, staggering the arrival of students allows institutions to enroll more people. Spring freshmen can replace upperclassmen that are studying abroad for the semester, which leads to efficient use of dormitory space. Personally, I believe more students should take time off between high school and college, and we can see delayed admissions as an embrace of the idea.

Perhaps university administrators have these thoughts, but the consequences for ranking and status are just too convenient. Universities live off their reputations and, notwithstanding the coronavirus, are finding it more difficult to fund themselves; we should be skeptical of professed altruistic motives. Anyone should have a hard time believing colleges engage in policies that hide low-quality admits and allow them to enroll more wealthy students for reasons other than their own advancement.

4. Normative claims

I’m going to pick on USC because it was the original subject of my investigation, though I believe everything below also applies to BU.

There’s an equality argument against USC’s spring admission policy. As described, they advantage rich, under-qualified applicants who otherwise would have little chance of being accepted. We believe wealth should have no role in allocating educational opportunity, so our ideals about merit and social mobility are violated. Hence, spring admissions policies are inconsistent with our values and should be abolished or altered. I believe this is an effective and important argument but will not pursue it at length. We all know its steps and understand how much of an issue social mobility is.

A more interesting argument concerns honesty.

Suppose you don’t mind whether private institutions lower academic standards for wealthy students. You might not believe these universities deserve tax breaks, but in principle, there’s nothing wrong with private actors imposing an income qualification on applicants. In the same way only the wealthy can buy birken bags, only the rich can get a degree from USC.

In light of this, you can still think spring admission is problematic because it functions to misrepresent the institution. Perhaps it’s within USC’s right to compromise rigor in admitting some students, but their statistics should reflect that. It’s disingenuous to tout 96th percentile SAT scores and falling acceptance rates when 15% of freshmen are not included in those figures. It’s deceptive to submit unrepresentative data to college rankings for status and prestige while slipping in hundreds of students that might be under-qualified.

I think it’s admirable USC is on such a deliberate campaign to improve itself. It’s clearly a much better institution than it was in the past, but only substantive growth should be rewarded. Its spring admissions policies are evidence it wants all the benefits of a high-powered student body while still reserving the right to lower standards for the wealthy. It cannot pick both and remain honest. If USC wants to remain a playground for the rich, so be it, though it should not pretend otherwise.

5. Conclusion

I could be wrong. It’s possible all spring admits are highly qualified, even more so than regular admits. In fact, some of them probably are [1]. It’s also possible most spring admits are low-income first-generation students, on their way up the socioeconomic ladder. Given the evidence, though, I think this is unlikely. The consequences for universities are just too convenient. I invite USC, BU, and all other universities to release statistics on spring admits. Until then, I stand by my critique.

My criticisms are also directed entirely towards institutions, not individuals. Being accepted to any college, during any semester, is a reason to celebrate. When confronted with opportunity, individuals are obliged to take it. Yet, this does not prevent debate at the institutional level about how some opportunities are allocated, or if organizations are being dishonest about who receives them.


[1] Let F(1): (1) is a spring admit and G(1): (1) is academically underqualified.

My position is not:


But rather:

∀x[P(Gx|Fx) > P(Gx)]

(with a little abuse of notation)



Appendix A: Calculations

Let’s begin with an example. Here is the excel sheet I used to calculate UVA’s figures.

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Table A1

The calculations start with the same intuition we had in the introduction: adding up freshmen enrollment numbers over the last 4 years, should reasonably approximate total undergraduate population. This happens in the “Fall matriculating class size” column. The total of 4 years of freshmen enrollment is tallied at the bottom.

The figures in the “students expected to graduate” column are calculated by multiplying the corresponding fall matriculating class size with the university’s 6-year graduation rate. UVA’s 6-year graduation rate is 95%. This means the “students expected to graduate” figure for 2017 is 3788*(.95) = 3598.6.

Transfers per year are often obtained from the latest edition of a university’s Common Data Set. Occasionally, transfer numbers aren’t available for the year 2019-2020, so in that case I assume they took in the same number of transfers as in 2018-2019. Recall that I’m assuming all transfers stay on campus for only 2 years. This means the only transfers on campus are those who arrived this year or the one prior.

I also attempt to approximate the number of students who enrolled as freshmen more than 4 years ago but are still on campus. These are the “students taking non-standard time.” To approximate the number of students from the freshmen class of 2014 that are still at UVA, I multiplied the total freshmen class by (1-[4-year graduation rate]). The rough thought is if you don’t graduate in 4 years, you will in 5 or 6. UVA’s 2014 freshmen enrollment is 3672 and their 4-year graduation rate is 89%. Hence, the number of freshmen from 2014 who are still around is 3672*(1-.89) = 403.92.

The upper bound of accounted-for students is calculated by summing the totals of “fall matriculating class size,” “transfers per year,” and “students taking non-standard time.” This assumes that every freshmen in the 4 prior classes is still around. The lower bound is calculated similarly, but the total of “fall matriculating class size” is replaced by that of “students expecting to graduate.” This calculation assumes all the students that are expected to drop out will immediately, and don’t contribute to the current undergraduate population.

The following table results:

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“Students accounted for (no dropouts)” is the upper bound, and “Students accounted for (all dropout immediately)” is the lower bound.

The full excel sheet I used can be found here. It includes additional notes on where I found enrollment data and graduation rates, and the assumptions I made when those weren’t available.


Appendix B: admit rate

Approximating how much USC inflates their admission rate is straightforward. Let’s use their published data from 2018 as an example, as this is the latest year where good data are available.

In 2018, USC admitted 8,339 students for the fall from a pool of 64,352 applicants. This translates into a 8,339/64,362 = 12.9% acceptance rate. However, in order to get a better sense of their total acceptance rate, we must factor in those they rejected for fall but admitted for spring. To my knowledge, you can’t directly apply for spring admission to USC, so the spring admits must have come from fall applications.

If what I mentioned about the “Other first-year, degree-seeking” row in the Common Data set is correct, USC had 642 spring admits enroll in 2018. Note that fewer students enroll than are admitted. Hence, the total number of spring admits is likely higher than the 642 recorded in the “Other” row. If we knew the “yield rate,” or percentage of students offered spring enrollment who took it, we could divide 642 by the rate and get the number of students accepted for the spring. To my knowledge, USC doesn’t publish that figure.

Yet, we can estimate a yield rate. Suppose it’s true the students offered spring admission to USC are academically under-whelming relative to fall admits. This means they probably would not have been accepted to USC, or schools of similar quality, under regular circumstances. As a result, even though USC offered them a spring position, it’s likely the best option they have. In other words, the choice could be between attending a #22 ranked college in the spring, or a #32 ranked college in the fall. I imagine most students opt for the former, leading to a higher yield rate.

Other factors can also influence the rate. Even though USC might be the best option for many students, it could still be unattractive to start in the spring. Students might want the entire “freshmen experience” that comes with arriving in the fall with other freshmen. Starting in the spring jeopardizes that.

It’s clear USC realizes the concern and took pains to alleviate it. As mentioned, it offers numerous foreign programs with other USC students to make spring admits feel they are not missing out. This increases the appeal of a spring enrollment.

How do we balance these competing concerns? USC’s fall 2018 yield rate was 41%. Harvard’s 2018 yield rate was 82%. I propose we think of a spring admission from USC as more attractive than a fall offer (given the spring admits’ poorer alternatives) but less attractive than Harvard (given the need to delay enrollment on campus). I think a fair figure is 75%. After all, spring admission programs are popular. In 2019, Babson College offered spring admission to 100 students and 86 took the offer. Babson is a small, specialized school, though, so I’m unwilling to read too much into their 86% yield. Still, it indicates rates should be higher rather than lower.


Using admit and application data, we can estimate USC’s actual 2018 admit rate given a 75% spring enrollment yield.

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Our assumptions entail USC is inflating their admit rate by around 1.3%. This might look paltry, but every percentage point counts in the prestige arms race.




Probability and God

Occasionally, rare things happen to us.

You might land a competitive job (3/100), appear on the big screen at a sporting event (1/70,00), or win the lottery (1/12,271,512). It’s also possible for you to get a US green card (1/126), be struck by lightning (1/700,000), or have an idea so good it’s “like getting struck by lightning” (1/???).

Whether it’s good or bad when the improbable becomes actual, there’s always a question lurking in the background: is this evidence of anything? If what seemed impossible is staring us in the face, what can we say about it?

This question is fascinating with respect to life in the universe and God. “God” in this post will not refer to the God of the new testament, the God of the old testament, Allah,  Shiva, Mahavira, Zeus, Ra, Spinoza’s God of substance, or any other popular deity. Formal religion aside, we will be interested in the quite general question of whether a being designed the universe to support life. This designer, whether s/he exists, will be referenced as “God.” I repeat, there is nothing Judeo-Christian, Muslim, Hindu, Wiccan, etc… about my invocation of “God.” I chose the capital-g for ease of reference and because I knew it would grab your attention.


Our existence is an anomaly.  We can get an intuitive feel for this by gazing at the night sky. Billions of stars, millions of planets, and somehow, we’re alone (so far). We have yet to find evidence of even microbes in the vast expanse of the universe, so the fact beings as sophisticated as humans came about represents something uncommon and significant.

The improbability goes deeper. As it turns out, even the laws of the universe that allow life to exist are rare and unlikely to come about by chance. If we were to slightly change the basic rules of force and gravity, for instance, the resulting universe would be hostile to life. Philip Goff has examples. The following three bullets are his words.

  • The strong nuclear force has a value of 0.007. If that value had been 0.006 or less,
    the Universe would have contained nothing but hydrogen. If it had been
    0.008 or higher, the hydrogen would have fused to make heavier elements. In
    either case, any kind of chemical complexity would have been physically
    impossible. And without chemical complexity there can be no life.
  • The physical possibility of chemical complexity is also dependent on the
    masses of the basic components of matter: electrons and quarks. If the mass
    of a down quark had been greater by a factor of 3, the Universe would have
    contained only hydrogen. If the mass of an electron had been greater by a
    factor of 2.5, the Universe would have contained only neutrons: no atoms at
    all, and certainly no chemical reactions.
  • Gravity seems a momentous force but it is actually much weaker than the
    other forces that affect atoms, by about 10^36 . If gravity had been only slightly
    stronger, stars would have formed from smaller amounts of material, and
    consequently would have been smaller, with much shorter lives. A typical
    sun would have lasted around 10,000 years rather than 10 billion years, not
    allowing enough time for the evolutionary processes that produce complex
    life. Conversely, if gravity had been only slightly weaker, stars would have
    been much colder and hence would not have exploded into supernovae. This
    also would have rendered life impossible, as supernovae are the main source
    of many of the heavy elements that form the ingredients of life.

This is the cosmological equivalent of tweaking the rules of your favorite game and then finding out it is unplayable. If the laws of physics differed slightly from what they are now, life as we know it wouldn’t stand a chance. It appears every law was formulated to lie just inside the narrow range that allows complex organisms like us to exist.

When we consider the fact life is highly uncommon in our current universe, and the second-order fact that it was incredibly unlikely the fundamental structure of said universe could be compatible with even the potential for life, our existence looks even more astounding. Roger Penrose —winner of a Nobel prize in physics with Stephen Hawking— calculated the odds of a universe such as ours being created by chance as one in 10^1,200. Lee Smolin, another physicist, calculates the probability of life arising in the universe as 10^229. These estimates differ by about a thousand orders of magnitude, but their point is clear. If left to chance, nature conspires against us.

It’s natural to find these odds unsettling. “But,” someone might say, “we exist! The odds say it’s nearly impossible for us to be around, yet here we are. If something so improbable happens there has to be some explanation for it that doesn’t appeal to pure chance.” Here, we reach for God. If the universe wasn’t the result of a random process but the product of a creator with life in mind, it’s much easier to believe we exist despite the astronomical odds against us. God is a much more satisfying, and, in a certain sense, more simple, explanation than blind luck. As the reasoning goes, a low probability of life existing in the universe, coupled with the fact life actually exists, constitutes evidence of a creator.


There’s an alternative perspective to probability and God. Life being necessary, in some sense, should be evidence of a creator. If God exists, we assume she wants life to come about and will not tolerate the possibility it could be otherwise. Such a God would make it impossible for a universe to exist that cannot support life, like us.

For instance, if we discovered there was a 99.99% chance any given universe could support life, wouldn’t this mean that possible universes were optimized for our presence? What better evidence of God could there be than odds stacked in our favor? If anything, a low probability of life originating in the universe might be an indication our existence was somehow left to chance. It’s possible we would not have existed, and that is incompatible with there being a God.

These two camps, those that stress the improbability of life, and those that stress its necessity, are at odds. One claims a low probability of life arising in the universe is evidence of God, while the other asserts high probabilities are. In other words, they use opposite premises to draw identical. At first pass, one of the camps has to be wrong. After all, how can low and high probabilities both be evidence for God? Does this mean we get the evidence either way? Did I just prove the existence of God? Definitely not. Probabilistic inference appears to have gone awry, and we’re going to get to the bottom of it.

Interpreting probability (can skip if frequency-type/objective and belief-type/subjective probabilities are familiar)

There are two ways to interpret probability. The first is characterized by statements like:

“There is a 60% chance you draw a red marble out of the urn.”

“The odds of getting pocket aces is 6/1326.”

“You will only win the lottery 1 out of 12 million times.”

Here, we use probability to talk about the outcomes of repeatable chance events. In this sense, a probability tells you, on average, how frequently an outcome occurs per some number of events. “60%” in the first sentence tells us, on average, if we draw 10 marbles out of the urn 6 of them will be red. Likewise, “6/1326” in the second sentence tells us that if we play 1326 hands of poker we should expect 6 pocket aces. In each case, the probability tells us about the distribution of a certain occurrence over a number of trials. We learn something about how often a chance event yields a specific outcome. This is the frequency-type interpretation of probability.

The second interpretation of probability is characterized by statements like:

“I am 90% sure I left my keys at home.”

“The odds of getting Thai food tonight are 1/10.”

“What’s the probability Trump wins the election? I say 28.6%”

These statements are similar to the others in that they use fractions and percents to express probabilities. The similarities end there. Rather than describe the outcomes of chance events, they express subjective levels of confidence in a belief. This is called the belief-type interpretation of probability. Higher probabilities correspond to more certainty in a belief, while lower ones express doubt. For instance, saying there is a “1/10” chance of getting Thai food means you are very unsure it will happen. Saying there’s a “90%” chance you left your keys elsewhere means you’re very confident you don’t have your keys.

It’s important to note that the frequency and belief-type interpretations apply to different things. We formulate frequency-type probabilities about the outcomes of chance events, like poker hands and lottery-drawings. Belief-type probabilities do not apply to chance events. They’re used to describe our subjective degree of confidence in statements about the world, like who is going to win an election or what we are going to eat tonight.

Reconciling the two camps

In the arguments given for God, which interpretation of probability is operative?

Frequency-type looks unlikely. The creation of a universe does not appear to be the outcome of a repeatable chance event, like drawing a marble from an urn. By most scientific accounts, there was a single “Big Bang” that yielded our universe, and there will never be a similar moment of creation. Because the event is unique, it makes no sense to talk about the frequency of a certain occurrence over a number of trials. We cannot say whether a universe containing life will arise 1 out of 10^10 times as it’s impossible to create 10^10 universes and observe what happens.

Belief-type probabilities don’t run into these difficulties. It’s coherent to say you have more or less confidence God created the universe, though a bit unnatural to express the sentiment as a probability. However, philosophers wrestle with how to further interpret belief-type probabilities and discover complications. Many take belief-type probabilities as the odds an individual would set for an event to avoid being dutch-booked. This view has the advantages of being intuitive and mathematical, but the betting analogy breaks under select circumstances. Individuals might refrain from setting odds (and if we compelled them, would those odds be accurate?), and it’s not clear there’s a single, precise number that we would set the odds at to express our confidence in a proposition.

While belief-type probabilities appear to be the best choice, I’m going to ignore them. This is because my “solution” to this issue relies on a frequency-type interpretation of probability so I’m going to shamelessly ignore the alternative. We will assume the creation of our universe is the outcome of a repeatable chance event. It’s also true belief-type probabilities have been critiqued in the context of reasoning about religious hypotheses, but I will not discuss such objections.

Using frequency-type probabilities can also be somewhat legitimate. We can circumvent the objections to using it in reference to the creation of the universe with a multiverse theory. If you believe multiple universes have been created — perhaps there are 10^10 parallel universes, for example — it’s perfectly acceptable to use a frequency-type probability to describe the odds of life arising. Your statement simply expresses the odds of picking a universe with life at random out of all the created universes. Personally, I have no idea whether multiverse theories are actually plausible, but this is a potential way to justify a frequency-type interpretation.

Given the above, I don’t think the two camps are incompatible with each other. It’s possible for low and high probabilities of life to serve as evidence for God. Both parties are making valid inferences from the probabilistic evidence they have. The caveat is that I believe each can only argue for a certain type of God.

Consistent with our assumption the creation of the universe is the outcome of a repeatable chance event, imagine it is determined by the spin of a roulette wheel. Each slot in the wheel represents a possible universe, and wherever the ball lands, the universe corresponding to that slot is created. One slot might represent a universe with physical laws like our own, and compatible with life. Another slot might represent a universe so different from ours that life could never originate.

Those who think low probabilities of life are evidence of God might imagine the roulette wheel of possible universes to be enormous. There are trillions of possible slots, and only a handful of them will correspond to universes that contain life. The probability the ball lands in a slot that creates a universe containing life will be minuscule. Yet, our universe exists and contains life. Since it defied nearly-impossible odds, the reasoning goes, it must have had some assistance beyond pure chance. The “assistance” in roulette wheel terms might be thought of as God picking up the ball and deliberately placing it in a slot corresponding to life. God intervenes in the chance event, making the highly improbable, actual.

The high-probability camp’s perspective can also be thought of in terms of the roulette wheel. In this case, a high probability of life would translate into every slot in the wheel corresponding to a universe where life exists. No matter where the ball lands, a hospitable universe will be created. Chance can select any slot it desires, but the outcome will be the same. God enters the picture when we ask ourselves who made the roulette wheel and dictated the nature of possible universes. The wheel being as it is constitutes evidence of an intention to bring life about. In this instance, God creates living things by stacking the odds in our favor.

When we consider how both camps might imagine God, the tensions between them fade. High and low probabilities of life can both constitute evidence of a creator because they support different versions of her. Low probabilities imply the existence of a God that chose our universe out of innumerable alternatives. High probabilities suggest a God that creates life by making a desolate universe metaphysically impossible.

This doesn’t guarantee either type of God exists, though. Individuals may use high or low probabilities of life arising in the universe as evidence for certain types of Gods, but how effective these arguments are is an open question. At any rate, neither line of reasoning abuses probability.



A dialogue in defense of business majors

Sophia Booth and Taylor Hutchins are both freshmen in college. Sophia has just told Taylor she wants to switch her major to business.

Taylor: Why would you do that? How can you learn anything about business in the classroom? They’re only going to teach you theory, and we all know that’s worse than useless when you go out into the real world.

Sophia: What makes you qualified to piss on business majors like that? Just because you’re mechanical engineering doesn’t give you a license to demean an entire subject you haven’t even studied.

Taylor: Are you kidding me? The business model canvas? The Boston matrix? You’re going to spend your undergraduate years filling out forms and pointing out farm animals as opposed to learning anything useful. Even if that stuff was the cutting edge of business knowledge at one point it’s surely going to be outdated by the time you graduate. You think you’re learning something applicable but it’s all empty theory.

Sophia: Woah, Taylor, you have it all wrong. I can see how you think we’re at college to learn eternal truths about how things operate and then apply them, but that’s just not how higher education works.

Taylor: What do you mean? Are you saying my education is as worthless as a SWOT analysis?

Sophia: No. You’re probably going to apply much of what you learn here in the future, but you need to understand you’re in a minority. The rest of us come to college to signal.

Taylor: You’re making less and less sense. What the hell is a “signal?” We’re all here to learn. That’s why our university exists in the first place.

Sophia: The people that are here to learn things for their jobs are future engineers, programmers, scientists, doctors, professors, and researchers. If I work outside any of those fields I will most likely never draw upon anything I learned in undergrad. Firms like Deloitte hire junior consultants from any major and train them on the job. The way most people get employed is not by learning whatever skills might be necessary to actually do their job, but by sending strong signals to the labor market.

Employers want to know I’m sharp, have a good work ethic, and am enthusiastic about working for their company. It’s possible for me to demonstrate these things by acing my classes, maxing out on credit-hours, and radiating excitement during my job interview. These are the signals I’m talking about, and I’ll get employed by sending them.

Taylor: Wait, so you’re on my side now? I hear you saying that what most people learn in college is useless. That gives you a much stronger reason to do mechanical engineering or computer science rather than business.

Sophia: My point is that even if you’re right and nothing in my business degree is applicable to my career, it doesn’t matter. A business degree sends a strong signal to the job market so getting one is not a total waste of time. I can still show employers I’m sharp, (by acing my classes) hard-working, (by taking a lot of credits) and enthusiastic about being their employee. Remembering any of the stuff in class just doesn’t matter.

Taylor: So you only care about your signals, right? The actual substance of what you learn doesn’t matter, yes? That sounds pretty cynical.

Sophia: I’m just not willing to delude myself into thinking everyone learns applicable things, including in business. It could be the case what I’m learning is useful, but it really doesn’t matter. Academically, college is only a big obstacle course with employers waiting at the other end to see who gets through first.

Taylor: You said employers want to know you’re sharp, right?

Sophia: Yeah.

Taylor: So you should still switch to computer science. It’s much harder than business, so if you do well you’ll be sending a much stronger “signal” to the job market, as you say. Straight A’s in computer science say much more about your ability than A’s in business, and employers know that. There is no reason to get a business degree.

Sophia: Sure, you’re right that computer science sends a better signal in the “sharpness” category, but there are still two other types of signals I’m trying to send. If I do business, I can still take a lot of credits and show employers I’m hard-working. We’ll say business and computer science are approximately equal on that front. Yet, business sends a much better enthusiasm signal. A business degree tells employers I’ve been thinking about business-related things for four years. Who cares if those things are applicable. My willingness to do that demonstrates a deep commitment to private industry that doesn’t come across in a computer science degree. Employers understand I wanted a job in business when I was 18-19 and had enough conviction to stick with it. Sure, doing well in computer science would show I’m sharp, but business says something deeper about my attitude and commitment, two vital things about any potential employee. Plus, I can still ace my management classes and check the sharpness box.

Taylor: You know you still won’t learn anything about doing business.

Sophia: Maybe I will, maybe I won’t, but who cares? I’m sending a good signal and will be able to get a job in business in the end. Still, we both know I’ll probably learn at least one applicable thing. I might have to take accounting or finance, and everybody agrees those are useful.

Taylor: I still think you’re making a mistake. You can send a good signal in a different major. Just switch to engineering and we can do problem sets together.

Sophia: Too late — I have a meeting with my academic counselor now. See you later!


Is Sophia convincing? I think so. She has given a strong argument as to why you should pursue a business degree, but it’s crucial to distinguish between what she is and is not saying.

Sophia is not arguing everything people learn in a business major is unapplicable.

Her argument is agnostic on this point. Maybe she’ll learn applicable things, and maybe she won’t, but it does not matter. To her, there’s no use arguing about applicability. Education is signaling, and all she’s claiming is that doing business sends a good signal regardless of whether applicable learning happens.

This is a strong and important point. It allows someone to say something like this:

“Ok business major skeptic. Let’s assume I learn nothing applicable in the business major for the sake of argument. I’m still making a good decision because my signal to the labour market will be strong and I will be hired.”

That’s it. You don’t need to say anything about how management 101 is highly applicable or how accounting is useful. Signaling will justify your decision regardless.

A business major can certainly strengthen her case by saying, “oh by the way, management 101 is great and finance is applicable,” but these are independent points. What Sophia has shown is that you can theoretically concede a lot of ground and have a strong position.


Jewish occupational selection

I came across this paper while researching a forthcoming post on Medieval Jews and the Black Death. The abstract:

This paper documents the major features of Jewish economic history in the first millennium to explain the distinctive occupational selection of the Jewish people into urban, skilled occupations. We show that many Jews entered urban occupations in the eighth-ninth centuries in the Muslim Empire when there were no restrictions on their economic activities, most of them were farmers, and they were a minority in all locations. Therefore, arguments based on restrictions or minority status cannot explain the occupational transition of the Jews at that time. Our thesis is that the occupational selection of the Jews was the outcome of the widespread literacy prompted by a religious and educational reform in the first century ce, which was implemented in the third to the eighth century. We present detailed information on the implementation of this religious and educational reform in Judaism based on the Talmud, archeological evidence on synagogues, the Cairo Geniza documents, and the Responsa literature. We also provide evidence of the economic returns to Jewish religious literacy.

This reminds me of Protestant advantages that accrued due to increased literacy. What would the 21st century equivalent of this be? A religion that mandated all adults teach their children algebra? C++?

Questions to ask people

I like to have a couple of these in my pocket so when I meet someone new I can ask something that hopefully yields an interesting answer. My go-to for years has been “what’s the worst advice you’ve ever received?”


-What’s a story your parents like to tell about you? (credit to Anshul Aggarwal for this. I have only heard this one in a formal interview setting, though).

-What’s the best book you’ve read that you disagree entirely with?

-Who did you worship when you were younger?

-Do you think the rate of technological progress has slowed over the last 50 years? (then you proceed to convince them that it has).

-What’s the worst decision you made that turned out well? (and vice-versa: best decision that went terribly)

-Do you know of any fun online blogs?

-What do you do to remain weird?

-What’s something only people from your hometown do?

-Why do you think people buy expensive things they don’t need?

-What’s something you take seriously?

-What’s your opinion of Los Angeles? (works in any locale)

-What’s the taboo thing to do in [insert person’s hobby]?

-What’s the weirdest joke you find funny?

-What do you think is the most underrated personality trait?

-I don’t think computer science is really a science. Do you? (only works for CS people).

-If you could write an op-ed for the NYTimes, what would it be about?

-Do you trust economists?

-What’s the best city that’s not your hometown?

Educational Signaling

I recently finished Bryan Caplan’s “The Case Against Education” which is a rollercoaster of a book. Caplan basically makes two claims: education is much more effective at signaling worker productivity than imparting practical/employable skills, and as a result of this we should cut state and federal funding for it entirely.

It’s natural to approach these assertions with a healthy dose of skepticism. I’ll withhold judgment on the second claim for now, but I admit I am moved by his arguments for educational signaling. In short, he demonstrates we learn nothing in school beyond basic literacy and numeracy. Take science. Caplan supplies the following table with data from the General Social Survey and his own corrections for guessing. IMG_0057He has similar tables for basic political and historical knowledge. Clearly, we retain very little in the form of pure information.

What about the old adage that education is supposed to “teach you how to think”? Caplan has an answer for that as well. He cites studies demonstrating that the entirety of one’s undergraduate education increases general reasoning ability marginally, and only specific areas depending on the choice of major. “Learning transfer,” or the ability to apply principles learned in one situation to another, is also rare, especially when the initial principles were learned in a formal context. Self-reflection confirms this. How many times have you explicitly used information/a pattern of reasoning developed in class to solve a problem outside of a test?

In fact, my own decision to study philosophy, and expect employment post-graduation, presupposes a signaling theory of education. I do not plan on becoming a philosophy professor, but that is the only occupation where what I learn in class will be relevant. Nobody uses Kant on the job, and I knew that ex-ante. Instead, I have to rely on the fact choosing philosophy signals something about me that employers value. In Caplan’s terms, I’m hoping it demonstrates my ability, conscientiousness, and/or conformity, as these are the primary signals a college degree functions to send.

I’m a convert. Signaling explains why students cheer when class is canceled, but are reluctant to skip, why MOOCs can provide an objectively better educational experience than many brick and mortar institutions but pose no threat to the establishment, why STEM graduates do not work STEM jobs, and why the years of college that see the most payoff are graduation years. The personal and academic evidence for signaling is gigantic. Why ignore it?

The individual implications for this conclusion are Excellent Sheepy. Because your degree + extracurriculars are the only measurements employers have of your productivity, maximize those. Do the minimum amount of work for each class. Cheat on tests. Join as many clubs as possible and try to get a leadership position in each. You’re not going to remember course material, and it’s surely not going to be relevant to your job, so who cares? Even if you’re overcredentialed for your ability and turn out to be a poor employee, you’ll stick around as long as your incompetence isn’t egregious. Firms will keep a marginal employee for years to delay finding a replacement and upsetting other employees.

The societal implications are also gigantic. If education is just signaling, should there be less of it? (Yes, but I’m not a full Caplanian). If education is just signaling, should it not be a human right? If education is just signaling, should this be an indicator e-learning companies should create better, more informative credentials rather than trying to improve content delivery?


I didn’t check my grades for two years

By the time college rolled around, I had made the decision not to check my grades at all. They had, quite literally, ruled my life during high school, and I was intent on making sure the future was different. This was not (fully) an irresponsible retreat from reality, but the consequence of some positions I began to hold about schools and learning. As a result, up until the end of my sophomore year, I never knew what letter grade I had received in a class or even what my GPA was. I never even got around to learning how to check my grades.

I knew how I did on tests and essays and the like. My policy was that, if the assessment is handed back to me, I’m allowed to know the score. In fact, knowing those types of scores was of the utmost importance to me.

To explain how I arrived at this strange and perhaps irresponsible decision, I am going to outline the general reasoning I used to get there. It will help to define some terms at the start. I’m going to use “marks” to refer to the individual scores one receives on specific assignments. 87/110 is a mark that one might receive on a test. “Grades” refer to numbers that are usually composed of the weighted averages of all of your marks. 88.4% is an example of a grade. “A,” “B,” “C,” etc. are also examples of grades because they are assigned by calculating the weighted average of your marks.

Here’s the reasoning:

  1. The objective of school is to learn.
    1. You should do things that contribute to this objective.
  2. Learning, roughly, consists of knowing things you did not know before.
    1. This is a two-part process. First, you must identify the things you do not know. Next, you learn those things.
  3. Knowing the marks you receive on individual assignments helps identify the things you do not know. Example: if you receive poor marks on a quiz that covers the binomial theorem, this is a good indicator you don’t understand the binomial theorem.
  4. Knowing marks on assignments contributes to the first part of learning. (2.1, 3)
  5. You should know your marks. (4, 1.1)

As the example in (3) suggests, marks are helpful because they give you feedback at a low level. What you receive on a single essay or test can often tell you what you know or don’t know with a fair amount of specification. This, I admit, mostly happens if you get the actual assignment handed back to you with a certain level of feedback. If you only know the “true mark,” or what percentage of points you received, it can sometimes be difficult to figure out the exact extent of your knowledge. Luckily, individual assignments often cover only a handful of topics, so it can be easier to infer what you missed.

So far, we’ve only established that you should know your marks. Great. How did I arrive at the idea these are the only things you should check?

This conclusion was established negatively. I couldn’t find any argument that appealed to learning that says I should check my grades. Let’s try to start from the first two premises of the prior argument, incorporate grades, and arrive at the conclusion we should check them.

  1. The objective of school is to learn.
    1. You should do things that contribute to this objective.
  2. Learning, roughly, consists of knowing things you did not know before.
    1. This is a two-part process. First, you must identify the things you do not know. Next, you learn those things.

We can’t use the same move as last time. Grades, because they are a weighted average of many individual assignments, can’t carry information about what specifically you don’t know. If you get a C in a Shakespeare class, you can convincingly say “I don’t know Shakespeare,” but how helpful is that? You’ve identified what you don’t know on a superficial level, but that statement doesn’t provide a useful direction towards actually learning the stuff. Are you shaky with Othello? Does the play format give you fits? Can you even penetrate Shakespearean English? A poor grade only says you need to do work. It does a horrible job of specifying exactly what needs to be done.

We’ve seen that grades are ineffective at identifying the things you do not know. The only remaining way to relate them to learning, and establish that you should pay attention to them, is to claim they somehow help you learn those things.

Now, how can grades help you in the act of learning? This is unclear. In what way does knowing the weighted average of your marks allow you to understand academic material better? A certain type of knowledge about the points you’ve earned doesn’t seem related to your ability to comprehend unrelated concepts.

I can see a skeptic coming up with a counterargument. They might say that knowing grades can give someone motivation to study and learn. They might want a better grade rather than a worse one, so knowing where they stand pushes them to spend time with the material. An attitude like this violates the first premise, though. A student who is motivated by grades supplants learning with credentialism as the goal of school. The student would have to reject premise 1 and commit themselves to a school experience that makes learning an afterthought. No good.

This is reasoning, in some inchoate form, was what was floating around my head when I decided not to check my grades after my first quarter of college, and the second, and the third, and the fourth, etc… I had a faint idea of what my GPA was since I saw the marks on the tests I got back, but it was very vague. Basically, I knew I wasn’t going to be on academic probation anytime soon.

I must also emphasize this is the literal truth. I didn’t peek here and there or do some back of the napkin math to get an approximate sense of my grades. I was in complete and utter ignorance of my official GPA.

And it was wonderful. For the first in my life, I felt a deep sense of academic freedom. I understood that I was at university to learn, and my behavior was fully consistent with this fact. I did close readings of texts when I could have skimmed them. I revised essays two, three times when I knew the first draft would do. I read more books in my free time than I had since middle school. I felt comfortable talking candidly with my professors and TAs because I wanted to learn, not grovel.

This doesn’t mean my college experience was/is faultless. An unambiguous focus on learning was somewhat of a compensatory mechanism meant to address the many faults I found in my institution. Nonetheless, the experiment was a success.

Readers at this point are perhaps left with several questions. “Riley,” they ask, “do you still not know your grades? Why submit yourself to such paralyzing uncertainty? Don’t you understand your GPA determines a significant part of your adult life, playing an instrumental role in considerations like, but not limited to, your attainment of internships, full-time jobs, graduate school admissions, scholarships, loans, and other professional opportunities? Are you out of your mind?!?”

In response to the first question, I currently know my GPA. This experiment concluded at the end of my sophomore year, but the effects are, hopefully, permanent. I understand what it’s like to put learning first, and, though it takes much effort, I intend to keep it this way.

An explanation of why the experiment ended addresses the remaining questions. I began to pay attention to my grades again because I realized the argument I gave above is wrong. Premise 1 is faulty. Ask anyone who isn’t a philosophy major what the purpose of school is and they will say anything but learning. Formal education can be about creating a workforce, increasing social mobility, instilling civic knowledge, cultural assimilation, personal maturation, landing a job, proving something to society, or proving something to yourself. All of these are valid ends of the enterprise. Surely, you can find an argument that appeals to one of them and concludes you should check your grades. Instead of reading “the objective of school is to learn,” premise 1 should say “an objective of school is to learn.”

Do I regret this decision? Absolutely not. I acted in full accordance with my values. Were my values those of an educational idealist, dismissive of the many social, cultural, and economic objectives of formal schooling? Sure. Should you ignore values arrived at via ample reflection because you’re unsure if they will change in the future? Almost never.

I’ll maintain that learning should be the principal objective of school, or at least near the top of the list. However, as soon as you introduce other grade-influenced ends into the mix, saying you should not check your grades is indefensible. That’s why I know my GPA now. I don’t obsess over it. I don’t stake my emotional health on whether it twitches in one direction or another. It is a metric that, for one reason or another, people care about. If I want to convince these people I deserve to study with them, work with them, or use their money, I shouldn’t neglect it entirely.

Yet, I remain committed to learning. I’ve seen what wonderful academic experiences are possible if I let it motivate my decision making. I recommend you take this idea seriously. If you do, this doesn’t mean you should ignore your grades. Just check them a little less often.


What I’ve Learned at 21 (with brief justifications/explanations)

It’s almost obligatory at this point. Around your birthday, you write a post/article detailing what you’ve learned thus far and some thoughts going forward. Yet, just because the “what I’ve learned at x” post is common doesn’t mean it’s without value.

Hopefully, this blog post is the first step of what will become a lifelong project. I already journal every day and record some of what I’ve learned there, but making a public list helps me clarify my thoughts and allows friends to challenge them. In the future, it can also afford me an opportunity to publicly affirm or refute something I said in previous years. It’s certain some things I mention below will turn out to be false. Other things might take on additional significance with the passage of time.

Instances of the “what I’ve learned at x” genre typically proceed as follows: a brief introduction, a flurry of aphorisms, and an optimistic conclusion drawing attention to the next 365 days. I’m keeping the beginning and end, but modifying the middle. Instead of dispensing with the things I’ve learned in bullet-point format with bullet-point brevity, I aim to provide some additional justification/explanation for each one. Where I can provide an adequate argument for why something is true, I hope to do that. If not, the least I can do is outline why I think it’s plausible.

Three things matter a lot to me

(1) Having intimate relationships with wonderful people (2) Being interesting to myself (3) contributing to progress.

Explanation of (1): My friendships are my most prized possessions. To have people with whom you can speak candidly, who will push you in unexpected ways is invaluable beyond expression. Some of our most basic human powers can only be fully exercised in friendships like these. For this reason, I consider them essential for making a life go right, and count myself fortunate beyond belief to have already experienced several of these relationships in my short life thus far.

Justification for (2): A thought experiment: you must wear a secret service style earpiece for the rest of your life that relays you the real-time mental activity of another human being. Every thought they have, every idea that flashes through their mind enjoys the same force inside of your own head. What type of person would you hope to be connected to? Beyond wanting them to be kind and generally nice, chances are, you would also want them to be interesting. You would like them to have varied thoughts about varied things and play with ideas you might not have encountered otherwise. Under these circumstances, this freaky mind-reading scenario might actually be enriching, and you wouldn’t mind having another person occupy your head.

This might be even more convincing when you consider the alternative: having the same bland thoughts piped into your mind every day. I can imagine being neutral towards this possibility in the short run. After all, boring thoughts are inescapable. Yet, years of this might erode you until you are just as uninspired as your mental companion. This is, as it were, death by dullness.

If the possibility of mental poverty caused by foreign thoughts is unacceptable, then the same possibility caused by endogenous ones should be equally terrifying. Thankfully, our thoughts are controllable to a large extent. We can choose who we’re “hooked up to.” As a result, we can aspire to have our heads be exciting places to live rather than arenas of tedium and routine.

Explanation of (3): I don’t have an argument here (at least not yet) but this value stems from something intuitively compelling about the idea of progress. The world today is much better than the world prior to the industrial revolution, and that world was still superior to the world during the middle ages. Doing my part to make sure the future is still better than the past just seems like a reasonable thing to do.

Additionally, I can thank Lincoln High School and the entire city of Portland for instilling in me a desire to be normative. I spent my formative years in a community that publicly valued righting historical wrongs and securing our future from existential threats like climate change. I learned that it’s not only possible to shape the future into a just and prosperous society, but that we’re morally obligated to do so.

Wonderful people are rare and cannot be taken for granted. Do everything possible to maintain close ties even though time and circumstances may pull you and them apart.

Explanation: Whether there actually are few wonderful people out there or the conditions under which we interact make it difficult to recognize the wonderful-ness of others is an open question. Yet, it’s clear their company is not guaranteed. I’ve been fortunate enough to meet wonderful people who, though they no longer belong to the same institutions as me I’ve managed to keep in touch with. Our relationships have been rich and deeply fulfilling, and life would be much harder without them. The benefits of being around wonderful people need not decrease with distance, though ensuring this requires deliberate effort.

Everything worth doing is difficult, but not everything difficult is with doing.

Justification: This is best illustrated by an example. Curing cancer is incredibly difficult, but the suffering endured in pursuit of this goal is justified by your service to humankind and the pure pleasure of solving a seemingly impossible problem. Attempting to run up Mt. Everest is also hard, but it’s much more difficult to get a convincing answer as to why it’s worth doing. Even if you find a plausible reason (I must prove something to myself, I enjoy setting absurd goals and achieving them, etc.) it cannot have the same gravity that the reason behind curing cancer has.

Interrogate your goals. They may be ambitious and difficult, but this does not mean they are worth your time.

You are the average of the 5 people you spend the most time with, but this doesn’t give you an excuse to be an asshole.

Justification: The first part is almost a cliché, and I take it most people can recognize the immense power of your immediate social circle on your thoughts and attitudes. Exercising personal aspiration by controlling your company, however, carries a hint of snobbery that’s difficult to dismiss. Pick your friends wisely, but having high standards is also compatible with being kind and open-minded.

Good roommates are incredibly valuable

Justification: This is intuitive, though it’s tough to know how much more valuable until you’ve gone from having a poor roommate to a fantastic one.

The majority of your interestingness is determined by how much you read.

Justification: I’ll claim that your level of interestingness is related to the volume and quality of ideas that go through your head. It’s possible to have a lot of interesting thoughts on your own, but we’re all limited by our experience and expertise. The solution is to maximize exposure to ideas, and this comes either through reading or interacting with interesting people. However, the people you can interact with are also limited by their experiences, and all of you are limited by time and place. The fact you can interface with them and speak the same language means you all live in the same era, within roughly the same culture, and mentally developed with respect to the same dominant ideas.

Reading faces these problems to a minimal extent. Translators alleviate the language barrier, and our compulsion to write and record has given us the opportunity to hear the major ideas of every civilization up to the present, provided the relevant texts survive. The volume of potential ideas you can be exposed to expands dramatically with reading. I’ll also claim reading exposes you to higher quality ideas. Poor thinking is less likely to have survived millennia, or be published in collected essays or anthologies. It’s possible to get your fix of ideas via oral exchange, but reading is generally superior.

Live music is wonderful

Explanation: I always forget this until I see a live performance with someone really good. There’s nothing quite like feeling the bass in your chest or getting chills from a vocalist. We all need a little more of this in our lives.

Girardian Terror is real

Explanation: Very roughly, Girardian terror refers to the idea that our desires are mimetic. We want things that we see other people want, and competition between us and others similar to us who desire the same thing leads to anxiety, conformity, and terror. For a lengthier discussion, see Girard’s wikipedia page, or his IEP entry. To see how Girard’s theories apply in a business context, check out Zero to One.

The intuitive appeal of this idea is easy to see. If everyone in your community (school/friend group) wants to be a doctor/lawyer/engineer, it takes a substantial amount of awareness and willpower to resist finding yourself aspiring to the same careers. Once desires are standardized, then competition between you and your peers for the limited number of med school/law school slots is fierce. So little differentiates you from the others. Every triumph over them represents a step towards distinction. Every failure is a slide backwards into obscurity.

Dan Wang has an excellent post on how American colleges and universities are perfect incubators of Girardian terror. I highly recommend reading it.

Alcohol is overrated

Justification: Who are you more likely to have a good conversation with, a drunk person or a sober person? Is this more likely to happen when you’re drunk, or when you’re sober?

Always have several uncommon/interesting questions on hand.

Justification: Unless it’s the case you and another person happen to have much in common, meeting someone new can be painful. Bypassing small talk with pointed, interesting questions can be the first step towards making a mundane interaction interesting, or performing conversational triage. Two of my favorite examples include: what’s the worst advice you have ever received? What’s something true but unpopular? Lama Al Rajih has a fantastic list of such questions here.

I want to die in Portland

Justification: circularity.

I do not want to raise children in Los Angeles or the Bay Area.

Justification: I have a clear bias towards my non-Californian upbringing. Yet, I still think both locales fail in several major areas that are, in my opinion, crucial for healthy development.

Los Angeles is devoid of natural beauty. It’s a great place to be if you’re into highways and overpasses, but I have not once looked around and thought to myself “this is a really beautiful place to be.” Malibu and Pacific Palisades suffer from this problem less, but let’s be real. It is unlikely I will live in either location.

For the Bay Area, if half of what I’ve heard about their high schools is half true, the entire educational experience is psychologically damaging for the average student.

Air quality is also a concern for both locations. The Bay Area less so, but if we continue to discover that air pollution is really bad for you, this would become more of a factor.

Both also suffer from housing and transportation woes that may only increase in severity. Being wealthy solves these problems to a certain extent, but I do not my children to grow up thinking they need to make at least $117,000 to enjoy a decent life.

Human reason can solve any problem

Explanation: This is a big claim that I can’t defend well. To do so requires an incredible understanding of history and philosophy that I do not have.

What brings me to this view is an intuition. Humanity has solved countless, seemingly intractable problems, and there is nothing to say we will not continue to do so. A skeptic mentions the problems we haven’t quite solved yet. P=NP,  the Goldbach conjecture, the existence of God, etc.. My naïve reply is that these problems are really hard, but solvable given enough time. Perhaps we eventually get there on our own. Perhaps we “solve” these problems indirectly by cooking up an AI that can handle them for us. Who knows? I think it’s a lack of imagination that causes people to think that just because we cannot solve something now means we will never be able to do it.

Ask and ye shall receive

Justification: This is all anecdotal, but cold emails work wonders when you’re a student. When I was running the Stumptown Speaker Series in high school, we booked free event space, got advertising, and brought in fantastic speakers like Kim Malek of Salt and Straw, all pretty much by asking. The strategy worked the same in college. While I was in charge of bringing in speakers for Bruin Entrepreneurs, we booked local entrepreneurs and members of Forbes 30 under 30 all via cold email.

The trick is to never copy/paste the same email template. Every message I sent was “handwritten” and included something specific to the receiver. I wanted them to come in, as opposed to someone else, and the emails demonstrated that I had done my homework. This is why to book three speakers I only had to send four emails.

People aren’t comfortable asking strange/intrusive questions but are perfectly fine answering them.

Explanation: I actually learned this from some social science research that came my way, but I can’t find the exact paper at the moment. The takeaway is that you should ask more questions, regardless of whether you think they go a bit too far. Obviously, there’s a boundary, but it’s not where we think.

Become friends with the strange people you meet. They’re much more interesting.

Explanation: Self-explanatory. A corollary is that if there are no strange people around, you are not in for a good time.

Sexy things are almost always overvalued

Justification: Here’s an example. The global professional sports industry took in revenues of $91 billion in 2017. The global cardboard box industry recorded revenues of $500 billion in 2014.

People like to be applauded for what they do. They like to feel their industry is “hot” or “sexy.” Some industries certainly deserve the hype they generate to a certain extent, but many of the products and services that are absolutely integral to our daily lives and current standard of living are very “unsexy” by mainstream standards. Think public infrastructure and the like.

I’m willing to generalize this beyond the economic sphere, too. Sexy restaurants, institutions, or ideas are probably so because there’s at least one thing extraordinary about them. Yet, what they offer is probably small in comparison to the price we pay for them.

Take more risks.

Justification: I’ve noticed people tend to regret the risks they didn’t take more than the consequences of a risk that didn’t work out well. Obviously, this only goes for situations where you can afford to lose what you wager. Still, I believe living an interesting life, stumbling upon new ideas, or learning new things, requires more risk than we think.

A just society is opportunity oriented, not outcome oriented.

Justification: Ensuring outcomes is problematic for two reasons. (1) Tough decisions need to be made about what outcomes are acceptable. Settling on a finite list might exclude outcomes some really desire. This privileges some people’s “good life”‘s over others, which is not consistent with a commitment to treating everyone equally. (2) Attempting to guarantee outcomes would require meddling with our lives to an unacceptable extent. Not only would this represent a gross intrusion, but it limits us. Part of our self-respect is founded upon making decisions for ourselves and living with them. To understand our social outcomes are fixed as a result of some gigantic scheme would be disheartening, and deny us an opportunity to exercise the agency that is an essential part of being human.

The best we can do is attempt to ensure everyone has the opportunity and resources at their disposal to pursue the good life as they see it. This idea is borrowed from John Rawls, and a lengthier discussion of it can be found on page 94 of A Theory of Justice.

The plan is to learn more this coming year. The thing I think is most likely to turn out false is that I hope to die in Portland. The thing I actually hope is false is that “wonderful people are rare.” The thing I’m most convinced is true at this point is “Girardian terror is real.”

Friends and strangers: hold me accountable! If you want clarification, aren’t convinced by what I’ve said, or want to chat, send a message.

Here’s to another year.



An overview of online dating

Here are several fun bits and pieces from an article that appeared on MR a bit ago. We’ll start with the funny parts.

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The authors’ take on the effects of online dating on consumer behavior:

An additional knock-on effectof online datingthat initial potential mate matching is increasingly visual, leading to secular demand growth in cosmetics and photography products, while fragrance sales remain flat because their value is irrelevant in the current market. This is largely facilitated via Instagram and mobile usage, and while it is a less important point to this thesis overview, it is an area for more detailed research and discussion

On the forces driving the fundamental structural changes in the dating market:

A conservative estimate of the percentage of new relationships begun online in 2019 is at least 65%, but likely over 75%. So, online dating now produces most new relationships. Why? From the perspective of prime reproductive age individuals, cost structures (safety, monetary, time, social frictions, etc.) have shifted, with many dropping to effectively zero. Because costs (physical safety, social stigma)have been disproportionately impactful to women, their elimination has had the effect of flipping the power dynamic in the market to favor women in prime reproductive age, though the dynamic changes with age.

and an (uplifting) implication:

With the advent of online dating, women in prime reproductive age are in the dominant position in the dating market for the first time in human history.

People tend to be rude and nasty on the internet, especially in romantic contexts if there’s some level of anonymity involved. Yet, online dating seems to be a great improvement for those have been historically disadvantaged by traditional dating methods.

Relevant to the previous post

An article from one of my favorite authors. Selected quotes from the first and last sections of the article to motivate your interest.

As an example, here I’ll tell my own story about my career negotiating the hierarchy in the highly stratified system of higher education in the United States. I ended up in a cushy job as a professor at Stanford University. How did I get there? I tell the story both ways: one about pluck, the other about luck. One has the advantage of making me more comfortable. The other has the advantage of being more true.


In fact, the only thing that’s less fair than the meritocracy is the system it displaced, in which people’s futures were determined strictly by the lottery of birth. Lords begat lords, and peasants begat peasants. In contrast, the meritocracy is sufficiently open that some children of the lower classes can prove themselves in school and win a place higher up the scale. The probability of doing so is markedly lower than the chances of success enjoyed by the offspring of the credentialed elite, but the possibility of upward mobility is nonetheless real. And this possibility is part of what motivates privileged parents to work so frantically to pull every string and milk every opportunity for their children. Through the jousting grounds of schooling, smart poor kids can, at times, displace dumb rich kids. The result is a system of status attainment that provides advantages for some while at the same time spreading fear for their children’s future across families of all social classes. In the end, the only thing that the meritocracy equalises is anxiety.

Do give it a read.