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Sex is in vogue among scientists; College rankings are a scam. – Scientific researcher



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Sex is a hot topic in scientific research, and not for the reasons you might think. trans Nature,

“Over the past decade or so, a growing list of funders and publishers, including the US National Institutes of Health (NIH) and the European Union, have asked researchers to include the two sexes in their work with cells and animal models.

Two main catalysts motivated this policy. One has been the growing recognition that sex differences, often linked to hormone profiles or genes on sex chromosomes, can affect response to drugs and other treatments. Another was the realization that including two genders could increase the rigor of a scientific study, increase reproducibility, and open up questions for scientific inquiry.

If the studies do include the two sexes, the results could be important for health. For example, sex is known to affect people’s response to common medications, including some antibiotics, and the risk of cardiovascular disease appears to be increased with lower blood pressure in women than in men.’

It makes so much sense that it’s surprising it took so long to realize and implement the change. https://go.nature.com/3Lc1MKH


Generally, keeping wild animals as pets is probably not a good idea. This can often have tragic consequences. According to Associated Press,

A man who may have kept a wild kangaroo as a pet has been killed by the animal in south-western Australia, police said on Tuesday. It was reported to be the first fatal kangaroo attack in Australia since 1936.

A relative found the 77-year-old man with “severe injuries” on his property on Sunday in semi-rural Redmond, 400 kilometers (250 miles) southeast of the Western Australian state capital of Perth.

He is believed to have been attacked by a kangaroo earlier in the day and was shot dead by police because he was preventing paramedics from getting to the injured man, police said.’

Sad news all around. For a person. For kangaroos. https://bit.ly/3eP1jCd


Ratings. Grades based on test scores. Presents prizes. They’re all pretty dumb, but people love them because they provide a simple, lowest common denominator way to quantify quality. There is some backlash against popular university rankings, especially in light of Columbia University’s admission that it beat the system to take second place in the rankings last year. According to CNN,

“…experts say the ranking offers a narrow view of what success should look like for students who want to pursue a higher education, especially with rising costs.

“In 2022, higher education must measure what matters, not just what has become tradition,” said Mamie Voight, president and CEO of the Higher Education Policy Institute, a nonprofit research and advocacy group.

“​​We need to recognize and celebrate institutions that help their students achieve social and economic mobility. That kind of upward mobility — especially for students who have historically been left behind after college — is what should qualify as ‘prestige,’ not the test scores students get when they enter college or the number of people an institution turns away.”

It is unlikely that these institutions will claim the first places in the ratings, according to experts.”

Will anything change in the short term? I doubt it. In the long run? I doubt that too.


On the technical front… We are all drowning in oceans of unread messages. Electronic letters. Text messages. Facebook. Twitter. Blah blah blah. However, one type of message stands out. A recent article in Guardian lamented the tyranny of belonging to WhatsApp groups,

“…What terrifies me the most are WhatsApp messages, specifically WhatsApp group chats. If I were a brave woman, I would simply leave these chats as soon as I was added to them; but I feel the weight of social duty, and so I stay.

I’m not the only person who feels this way. Last month, WhatsApp bowed to public pressure and announced that users would be able to seamlessly leave groups without informing other members of their decision. (However, the new policy has yet to be implemented.) We conflict avoiders rejoiced: now, finally, we can slip out of groups without being perceived as rude. But 11 years after the instant messaging app introduced the group chat feature, will we ever be able to escape the tyranny of the WhatsApp group?”

I KNOW, RIGHT? https://bit.ly/3xk1b3Q


It’s no secret that despite ​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​through through way down through it out, its narrow comfort zone/area of ​​knowledge, all the fancy and mundane things AI can do, it can be outsmarted. And sometimes, even in this space, it’s not that hard to find some random exception that throws the whole system into a spiral. Article in Proceedings of the National Academy of Sciences explores the state of artificial intelligence/deep learning and alternatives to current models and begins by noting that while deep learning is useful, it also has serious drawbacks.

“Deep learning emulates this kind of automatic response well, so its most successful applications tend to involve tasks where perception and recognition skills are paramount, such as photo editing and voice recognition. The basic idea, which dates back to the first neural networks inspired by the brain in the 1940s, is to process input data through a network of neuron-like nodes connected by synapse-like connections. This network is trained by asking the processing systems for a given input library, while adjusting the flow of data through each connection until the network produces satisfactory results.

Early neural networks were small and limited in their capabilities. But their capabilities and speed have improved dramatically since the dawn of the deep learning era around 2010, thanks to advances in hardware and software that have allowed networks to reach gigantic scales. DeepMind’s Gopher natural language system, for example, was trained on roughly 2 trillion English words while tuning 280 billion parameters into its compounds.

However, the success of deep learning has exposed its greatest weakness: the ease with which the network can be confused by input not considered in training.

People can also be confused by strange situations. But that’s when we start looking for solutions using System-2 thinking: a much slower and more complex way of knowing that dominates our consciousness and is not automatic. “Maybe you’re driving in a new city where the traffic rules are different, like you have to drive on the left instead of the right,” says Joshua Bengio, an artificial intelligence researcher at the University of Montreal in Canada. You can’t just go by habit, he says. You have to be careful, remember the new traffic rules and decide where to go next, right away.

Compared to system-1 thinking, system-2 is a tiny fraction of what goes on in our brains. But since this is the only kind of cognition we know of, most of the founders of artificial intelligence in the 1940s and 1950s assumed that this was all that machine intelligence needed. This inspired the symbol processing paradigm that dominated AI for the first half century until the deep learning revolution of the last decade. The idea was to give the computer some model of the problem in the form of a data structure similar to the mental models of the world we build in our minds, and then look for a solution to the problem by manipulating the model with algorithms that mimic our system-2.”

If/when quantum computing does come into its own, it will be interesting to see how AI paradigms change with exponential increases in computing power. https://bit.ly/3L9kgLI

Thanks for reading. Let’s be careful there.

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