AI technologies can be used to analyze large amounts of data and identify patterns that aid in selecting superior plant varieties used in plant breeding to accelerate crop improvement and develop new varieties with higher yields and greater resilience to climate changes, such as more frequent and severe periods of drought.
AI Overviews are a wonderful tool but shouldn’t be considered the final word on a topic or query. They are, however, a good place to begin an exploration.
With that in mind, I’ll start subsequent Survive and Thrive posts with an AI Overview on the topic under consideration and then proceed to whatever more I’ve found out in my own explorations.
A year ago I posted Some Tips for Living in a Warmer World, which was rather long on dire predictions and short on tips. I hope to flesh out those tips in this series.
“A sanity-preserving maxim among observers of Mr Trump is to pay attention not to what he says but to what he does. Better yet, pay attention not to what he says or does but to what the courts allow him to do. By this standard, Mr Trump’s first-month frenzy is likely to fall well short of a constitutional crisis. (The Economist, Donald Trump is a reckless president, but not yet a lawless one. February 22, 2025)
This post is an update to a post on rent control I wrote in 2022. It was inspired by a Zoom conversation I had some weeks ago. We were talking about rent control and I mentioned there was plenty of research showing that rent control often does more harm than good. My comment triggered a quick response, “yeah, that’s what conservatives say”. (For the record, I’m not a conservative).
Gray and Pruitt maintain that perception of harm is central to all moral judgments. Or as they put it, “harmless wrongs do not exist”. They also argue that “moral disagreement across politics is in part grounded in different assumptions of vulnerability”. For example…
The last four posts focused on countries with the highest CO2 emissions as a percent of global CO2 emissions: total emissions per country, per capita emissions, changes in emissions since 2000, and the decoupling of emissions from economic growth. This post will look at global trends in CO2 emissions since 2000 and 2010.
It’s rather obvious from the above that CO2 emissions are no longer rising in sync with economic growth, ie, they have decoupled (for the most part).
Per the above chart, CO2 emissions have declined since 2000 in most of the high-income developed countries but are still climbing in several middle-income nations.
The Emissions Database for Global Atmospheric Research (EDGAR) is a joint project of the European Commission Joint Research Centre and the Netherlands Environmental Assessment Agency which estimates emissions of all greenhouse gases (GHGs), air pollutants and aerosols. The latest EDGAR report is a treasure trove of greenhouse gas emissions data…
This series of posts will focus on countries with the highest CO2 emissions: China, the U.S., India, Russia, Japan, Iran, Indonesia, Saudi Arabia, Germany, Canada, and South Korea. First, the percent of total global CO2 emissions for each country
Why does this matter? Because longitudinal studies have found that students who performed worse in PISA at age 15 are less likely to attain higher levels of education by the age of 25, and are more likely to be out of the labor market entirely, ie, not in education, employment or training. For many, a lifetime of economic hardship and reliance on public services follows.
Part of this performance gap can be explained by socio-economic and language factors, e.g., poverty and lack of fluency in the language used on the tests. I imagine age at immigration matters as well: a person who immigrates as a teenager will likely find school harder in their new country than someone who arrived as a baby. Following this logic, I’d expect second-generation immigrants - born in a country to at least one foreign-born parent - would have little difficulty adapting to a country’s education system and so their PISA scores would reflect this.
Immigrant students often do worse on PISA assessments than non-immigrant students, especially in industrialized countries. However, the performance gap between immigrants and non-immigrants varies considerably across countries. For example…
Per the above chart, American 15-year olds have been reading at roughly the same level (on average) as they were 20 years ago. Surprisingly, their reading performance held up rather well during the pandemic years, despite the challenges of extended school closures, remote learning and the high absenteeism.
Facts are nice, but fact-checking is not always relevant or helpful, especially when it misses the point of whatever statements are being corrected.
“Does a person's perception of their place within the general socioeconomic order directly influence their physical and psychological well-being? Let's pretend that researchers find robust evidence that subjective social status does indeed predict various indicators of well-being, e.g., people who rate themselves lower in the pecking order are less healthy or happy than those with higher self-ratings. What can we learn from such evidence? Nothing much by itself. We'd have to dig deeper.” - Singh-Manoux, Adler, and Marmot (2003)
This post was going to compare police response times (RTs) in the ten most dangerous US cities with the RTs of the safest cities (link). Unfortunately, none of the dangerous cities had decent RT data, except for Oakland, California. But we’re in luck! Oakland has great data, not only for RTs but also for police staffing levels, both across several years.
1. Curiosity …
There is no hard-and-fast threshold for an acceptable clearance rate. That said, Oakland’s rate is abysmal. No wonder Oakland’s the most dangerous city in the US!