QTRS May 22, 2025

Graphs, commentary, and interesting content for the curious

As I see it…

Doomberg is worth reading even as a free subscriber. A recent post looks at why we have stalled in generating nuclear energy and how recent executive orders may change that. In short, the Atomic Energy Commission (AEC) was created in 1954, and one of its tasks was to encourage “private investment in the peaceful uses of nuclear energy, especially for electric power.” The situation changed in 1973 when the AEC was eliminated and replaced with the Nuclear Regulatory Commission (NRC).

The NRC’s mandate was limited strictly to regulation and safety, while promotional objectives were deemphasized. It didn’t take long for the new regime to effectively halt new reactor construction in the country.

Why did we stop with nuclear energy? This is the key paragraph.

The main weapon of the NRC is the linear no-threshold (LNT) model—an unscientific ethos that treats all exposure to radiation, no matter how minute, as both dangerous and cumulative. In other words, there is no threshold below which otherwise insignificant exposures are considered harmless. Combined with the risk-averse bureaucrat mindset and you get this astonishing result: only two of the current fleet of US reactors were approved and built under the auspices of the NRC.

It is a good article worth reading, but my point here is not about nuclear energy but about doing what the “experts” say we should do.

As I see it, experts are like data. We should be informed by them, but we don’t want them necessarily making decisions for us because the experts may not have the same values as the majority in the country as well as generally being “risk-averse.”

As an analogy, consider the creation of a Skydiving Regulatory Agency with the threshold model of no skydiving deaths. Every time there is a death, this agency adds regulatory limitations to skydiving. Eventually, skydiving will become too expensive as businesses would have to deal with the cost and aggravation of regulations. There will be no more skydiving. The experts will then promote their success in eliminating skydiving deaths. Experts would ignore the fact that people lost out on the joy of skydiving or the economic impacts. This is largely what happened to nuclear energy. The NRC regulated nuclear energy to halt its development based on a specific value, without considering the balance of risk versus reward.

When you hear the phrase “listen to the experts,” what the person is saying is that you should do what the experts say, and they also likely agree with the experts. Ultimately, experts exist to provide us with information that aids in decision-making, similar to data; however, since experts are human, they possess specific values, including their comfort levels with risk, which may not align with those of the general public.

For example, skydiving is dangerous at 0.27 fatalities per 100,000 jumps. For some people, the risk of skydiving is worth taking due to the enjoyment they derive from the activity, while for others, it is not worth it. The Doomberg article, again worth reading, gives an example of how the NRC's risk-averse “experts” views may have led to more cancer deaths, let alone how much atmospheric CO2 might have been averted.

Gaps in college enrollment

One of my data rules is that we should always consider other factors, as single-factor explanations are rare. When we look at who does and doesn’t go to college based on various group characteristics, we need to consider other factors than just sex, minority status, or socioeconomic status. Brookings does some of this for us in the article Persistent gaps in academic preparation generate college enrollment disparities (5/6/2025). Here is one graph from this article.

Caption: The orange dashed line indicates that, among high school graduates with similar grades, AP/IB participation, advanced math course-taking, and test scores, the gaps in college enrollment were quite a bit smaller than the without controls gaps (the blue line), but still large. For academically similar high school graduates, the gap between the first and fifth SES quintiles was 31 percentage points in 1982, 20 percentage points lower than the without controls gap.

In other words, many students from the lowest SES group possess the academic qualifications necessary to attend college, but they do not pursue that option. Whether they should or not is another question, but given enrollment challenges, colleges are missing out on capable students, with one reason likely being cost.

The article did the same analysis for different group comparisons. Two key quotes:

Black high school graduates were about 10 percentage points less likely than white high school graduates to enroll in both any college and four-year colleges across the cohorts. Controlling for academic achievement reverses both the any and four-year enrollment gaps; that is, among students with the same level of academic preparation, Black high school graduates were more likely than their white counterparts to enroll in both any college and four-year colleges.

In other words, Black students with the academic preparation go to college at higher rates than similar White students. This isn’t a surprise given the politics of higher education.

One more

That is, across all four cohorts, gender gaps in four-year college enrollment were about what would be predicted based on gender gaps in high school preparation.

In other words, the female-male college gap is largely due to male high school achievement.

There are more comparisons, but based on what I have here, we can conclude that the Black-White disparity in college is due to Black students’ high school achievement. Similarly for the female-male disparity. This is on high schools and society, not on colleges. On the other hand, there are poor kids who are prepared for college that aren’t getting there. This is on colleges, assuming you think they should go to college.

On college students

The NBER paper US College Students’ Well-Being (May 2025) examines Dartmouth students as a case study. This paragraph is from the conclusion.

The main Dartmouth findings are that females are more depressed than males, which declines in age after around 23. Lower grades are associated with worse mental health. Also, physical exercise and being an athlete is associated with lower depression, as is being in an academic club or a religious organization. Membership of a gender or sexuality organization is associated with higher depression. There are few race effects other than the ‘other’ variable which includes Native Americans who we know have higher depression rates. At Dartmouth residing in a fraternity is associated with higher depression, whereas simply being a member is not. The stress variables are highly significant, to such a degree that adding them in column 3 removes the (negative) significance of the Dartmouth variable. Financial stress seems important.

Females being more depressed than males is not surprising given what we know nationally. What is a bit surprising, if you believe the narratives from higher ed, is that there are “few race effects.” Dartmouth has an endowment of $1.2 million per student, so something is wrong given the issue of financial stress. The “gender or sexuality organization” is likely tied to broader societal issues, although it is hard for me to now wonder if part of this is due to campus rhetoric.

How hot was April 2025?

The month of April's temperature anomaly is where we might expect it for an ENSO neutral month, as you’ll see in the first graph below. In the second graph, the April anomaly (black) is lower than the past few months. The pattern is similar to past neutral periods. This all looks as expected. The recent neutral grouping is higher than the past neutral period but lower than the recent El Niño period. This aligns with our expectations regarding global warming.

It is worth reminding ourselves that on average global temperatures are warming, but that doesn’t mean everywhere is warmer or that some places aren’t cooler. This excerpt from the NOAA April 2025 report emphasizes this point.

Much-warmer-than-average April temperatures were present across much of the globe's surface. The most notable high temperature departures were observed across much of the Arctic, Asia, parts of Antarctica and the southeastern U.S., where temperatures were at least 2.0°C (3.6°F) higher than the 1991-2020 average. Record-high April temperatures were observed in the British Isles, Ireland and the surrounding ocean, and across parts of Asia, the Indian Ocean, the western Pacific Ocean, and the southern Ocean. Record-high April temperatures encompassed only 4.2% of the globe's surface.

Meanwhile, cooler-than-average April temperatures were observed across the Norwegian, Greenland, and Barents seas, central and eastern Antarctica, southern South America, and parts of Australia, where temperatures were at least 1.5°C (2.7°F) cooler than the 1991–2020 average. According to the April 2025 percentiles map, no land or ocean area had a record-cold April temperature in 2025.

eia graph of the week

It is worth recalling how important China is to the making of batteries. From the eia

The spinning CD

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Please let me know if you believe I expressed something incorrectly or misinterpreted the data. I'd rather know the truth and understand the world than be correct. I welcome comments and disagreement. Please feel free to share article ideas, feedback, or any other thoughts at briefedbydata@substack.com.

Bio

I am a tenured mathematics professor at Ithaca College (PhD in Math: Stochastic Processes, MS in Applied Statistics, MS in Math, BS in Math, BS in Exercise Science), and I consider myself an accidental academic (opinions are my own). I'm a gardener, drummer, rower, runner, inline skater, 46er, and R user. I’ve written the textbooks “R for College Mathematics and Statistics” and “Applied Calculus with R.” I welcome any collaborations. I welcome any collaborations.