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Rationing and elite cluelessness
I’m not excited about the results from Public acceptability of climate-motivated rationing (9/26/2024). Almost 30% and over 20% of responses in the U.S. are ok with rationing fossil fuels and high-impact food, respectively. The survey responses are higher for taxation. So, who exactly would decide on how rationing is done and what constitutes high-impact food? Consider it a thought exercise. Supposing you really had to ration fossil fuel use, who gets how much and when?
One issue to me is how out of touch with reality our wealthy are. Consider the next graph from Underestimation of personal carbon footprint inequality in four diverse countries (9/12/2024) Does it jump out at you?
Only 1 person in the top 1% surveyed overestimated their carbon footprint. The median response was close to 25 tCO2, when in reality it is over 250 tCO2. Only off by a factor of 10. The top 10% also largely underestimated their carbon footprint, but only by a factor of 3. Worse, the wealthy don’t report their carbon footprint as much more than the bottom 50%. Forgive me for not wanting these folks to decide on rationing schemes.
Gen Z starting to catch on?
There isn't much for me to say about this graph from the NYT article Gen Z Has Regrets (9/17/2024); other than the responses are encouraging. But, will they stop spending so much time on these platforms?
Cool historical map
From the Library of Congress
The influence of neighbors
The NBER paper Neighborhood Quality and Children’s Outcomes: Insights from Military Families (summary 10/1/2024) looks at military families and the outcomes of children related to the neighborhood they live in. This is quasi-random as they look at junior personnel who have little control over their assignment.
They link military personnel data spanning the 1990 to 2017 period to administrative tax records.1 Their database includes information on about 500,000 service members and their 800,000 children. They focus on junior personnel, who have minimal influence over their assignments.
Some results:
A typical 3.5-year assignment to a location where the share of the population with bachelor’s degrees is 10 percentage points above average correlates with a 3.5-point increase in SAT scores and a 0.4 percentage point increase in a child’s college attendance probability. Extended exposure amplifies these effects: two decades in a county 1 standard deviation above average in terms of college-educated population share is associated with SAT scores that are 10 points higher and a college attendance rate increase of 1.7 percentage points. When measured at the ZIP code rather than county level, the impact more than triples to 38 points and 6.6 percentage points, respectively. This suggests more localized neighborhood characteristics exert stronger influences on outcomes.
and a chart
Graph of the week
This comes from the paper Heat tolerance varies considerably within a reef-building coral species on the Great Barrier Reef (9/23/2024), with the main conclusion of
Here, we show extensive variation in the heat tolerance of a foundational coral species complex across the Great Barrier Reef. Thermal thresholds of 569 individuals differed by up to 7.3 °C across scales from meters to >1250 km.
The four boxplot graphs are heat tolerance metrics, and while there are little differences in the means of the groups, some groups have much greater variations (wider box plots).
One implication is that maybe the reefs aren’t completely doomed due to climate change: “While southern populations in this study exhibited lower absolute thermal thresholds, their greater distance from summer maximum temperatures and higher tolerance in retained traits indicate that they may be better positioned to persist through future warming, perhaps enhanced by gene flow of heat-adapted alleles from northern populations.”
Caption
A Variation in A. hyacinthus host genomic cluster assignments across sites on the Great Barrier Reef. B–E Heat tolerance traits from the southern reefs (sites shown in rectangle in A). Groups 1–4 from southern reefs shown in rectangle contained 44, 14, 27, and 51 individuals, respectively. Host genomic clusters were assigned based on genome-wide SNPs with group 1 representing A. hyacinthus “neat” and groups 2–4 representing other putative species in the A. hyacinthus complex. Heat tolerance traits have been adjusted to remove variation due to site using residuals from site-specific means. P-values are shown for each trait using one-way ANOVAs.
Texas energy
There are a couple key points about this eia graph (10/3/2024). The large flexible load is largely the data centers and cryptocurrency mining and
will total 54 billion kilowatthours (kWh) in 2025, up almost 60% from expected demand in 2024. This expected demand from LFL customers would represent about 10% of total forecast electricity consumption on the ERCOT grid next year.
Again, data centers are consuming large amounts of electricity and are driving increased electricity usage. We just want more energy, not less, making the transition to green energy a huge challenge. This is a great fact from the article:
Some of the larger facilities can consume as much electricity as a medium-sized power plant.
The spinning CD
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Comments
Please point out if you think something was expressed wrongly or misinterpreted. I'd rather know the truth and understand the world than be correct. I welcome comments and disagreement. We should all be forced to express our opinions and change our minds, but we should also know how to respectfully disagree and move on. Send me article ideas, feedback, or other thoughts at briefedbydata@substack.com.
Bio
I am a tenured mathematics professor at Ithaca College (PhD Math: Stochastic Processes, MS Applied Statistics, MS Math, BS Math, BS 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.