I’ve noticed a lot of people slipping up on how they interpret UK Covid-19 prevalence & testing data, so here’s a very brief thread on how to interpret figures from different sources, and what caveats each source does and does not come with:
• Pillar 2 community testing: these are the bulk of cases picked up at the moment. Case and positivity rates here *could* be influenced by where and who is being tested, so e.g patterns in this data with age, deprivation etc could be skewed by who is getting tested
• @ONS infection survey: these tests are random, and designed to be representative of the overall population.
Therefore trends and patterns in this data *are not* due to e.g certain locations or groups of people being more likely to get tested.
Samples taken for @ONS tests are re-tested multiple times to make false positives extremely unlikely (one in tens of thousands), so any false positive chatter is completely absurd for the ONS survey (and also hugely exaggerated re the Pillar 2 tests)
So when we see things like today’s fascinating @ONS breakdowns of Covid-19 prevalence & growth by deprivation, age, levels of socialising etc, these trends *are not* being driven by differential rates of testing.
For all the talk of a general fall in births, the drop is overwhelmingly driven by people on the left having fewer kids.
By ceding the topic of family and children to the right, progressives risk ushering in a more conservative world.
There’s something of a paradox at play here.
On the one hand, pro-natalism often implies constraining individual liberty and setting back women’s progress. As such, the left’s aversion to worrying about birth rates is perfectly natural.
But: the consequence of this emerging ideological slant in birth rates is that each successive generation gets nudged rightwards, increasing the likelihood that conservative politicians (who want to constrain individual liberty and set back women’s progress) get elected.
NEW: Is the internet changing our personalities for the worse?
Conscientiousness and extroversion are down, neuroticism up, with young adults leading the charge.
This is a really consequential shift, and there’s a lot going on here, so let’s get into the weeds 🧵
First up, personality analysis can feel vague, and you might well ask why it even matters?
On the first of those, the finding of distinct personality traits is robust. This field of research has been around for decades and holds up pretty well, even across cultures.
On the second, studies consistently find personality shapes life outcomes.
In fact, personality traits — esp conscientiousness and neuroticism — are stronger predictors of career success, divorce and mortality than someone’s socio-economic background or cognitive abilities.
There’s been a lot of discussion lately about rising graduate unemployment.
I dug a little closer and a striking story emerged:
Unemployment is climbing among young graduate *men*, but college-educated young women are generally doing okay.
In fact, young men with a college degree now have the same unemployment rate as young men who didn’t go to college, completely erasing the graduate employment premium.
Whereas a healthy premium remains for young women.
What’s going on?
At first glance, this looks like a case of the growing masses of male computer science graduates being uniquely exposed to the rapid adoption of generative AI in the tech sector, and finding jobs harder to come by than earlier cohorts.
The number of people travelling from Europe to the US in recent weeks has plummeted by as much as 35%, as travellers have cancelled plans in response to Trump’s policies and rhetoric, and horror stories from the border.
Denmark saw one of the steepest declines, in an indication that anger over Trump’s hostility towards Greenland may be contributing to the steep drop-off in visitor numbers.
Corporate quotes are usually pretty dry, but the co-founder of major travel website Kayak wasn’t mincing his words: