I really enjoyed the book Mathematica by David Bessis, who writes about his creative process as a mathematician. He makes a case that formal math is usually the last step to refine/optimize an idea, not the starting point as is often assumed. His point is to push against the cultural idea that math == symbols. Sounds similar to some of what you're describing.
I really didn't like that book. Its basic premise was that we should separate the idea of mathematics from the formalities of mathematics, we should aim to imagine mathematical problems visually. The later chapters then consist of an elephant drawing that isn't true to scale and tell me why David Bessis thought it would be best to create an AI startup, that just put the final nail in the coffin for me. There's some historical note here and there, but that's it - it really could've been a blog post.
Every single YouTube video from tom7[0] or 3blue1brown[1] do way more on transmitting the fascinations of mathematics.
It would be more relevant to look at reading scores for children who specifically tuned into Reading Rainbow. I suspect the number of viewers was a small fraction of all children in the US, in which case the show's ability to affect the nationwide reading scores would be low. In other words, I don't believe the data you cited supports a conclusion that the show was ineffective at educating individual viewers.
We'd also have to figure out whether children who already loved reading watched Reading Rainbow, or if children who hated reading started liking it after watching. Since nobody has that data, I'll go with the aggregate.
> In other words, I don't believe the data you cited supports a conclusion that the show was ineffective at educating individual viewers.
I don't think it conclusively proves anything, but I do think it supports a skeptical position. The article doesn't cite anything supporting the notion that Reading Rainbow improved childhood literacy, so I'm wondering if you take the position that it did—and if so, on what basis?
At the State university where I teach, literally part of our mission statement is to graduate every student who we admit. It has become a big part of the messaging from upper administration in the last few years.
I can think of two factors. First, some direct costs could be prohibited. But more importantly, to make this work universities would need to restructure to make all of their services fee-based, and researchers would need to allocate these fees item by item in their proposals. Which seems doable, but is no way to run an efficient operation. Even if the bottom line looked the same, the value to NIH and taxpayers would be far worse due to the inefficiency.
More likely, overpriced institutions like Harvard will cease to be competitive for grants, and those which offer better value for money will be better placed to submit competitive grant proposals.
Im sure there is fat to be cut but the indirect model eliminates the need to spend so much effort accounting for the 5 minutes this grad student used this piece of shared equipment, 20 minutes that post doc used this equipment. Have you ever had to account for number of sheets of paper printed on a shared printer? Total waste of time when considering the cost of accounting and time of these expensive workers. Indirects are an imperfect solution to a real efficiency problem. I really think the solution is to identify “abusers of the commons”and hold them accountable
This sounds good in some niche cases, like an English class with a small class size and a highly experienced teacher. However of all the potential fads in higher education this one seems particularly risky to students. In the end the grade is given based on how the prof feels about you, and if they agree with your self assessment. Which can be easily gamed (e.g. student pretends to be a bad writer at first and has a seemingly miraculous transformation) and is subjective. The assessment will also be tainted by one's individual biases, by definition. Whether you agree or disagree about the importance of diversity equity and inclusion in higher ed, one useful principle of that movement is that of clearly defined evaluation, precisely to avoid effects of personal bias.
Agree. Academics are now going to write an extra $11k into their grants (=$15k if you count uni indirect costs), with the justification "I plan to produce Nature quality results". If your article doesn't get accepted by Nature, all the better there's now an extra $9k in your budget to play with. Let's just keep in mind, these grants are funded by taxpayers.
My layman's understanding of earthquakes is that they have a heavy tailed probability distribution which makes predictions fundamentally difficult. Does ML (as in this approach) get around that somehow?
I would agree with many others here who say publish it. In some fields there is an additional question of where to host it, lest your paper's impact outlast the lifetime of your current GitHub repo or whatever. There are good solutions out there. Assuming you are at a university it's worth having a chat with a librarian.
For many of the papers I read (engineering) I would love to be able to click on symbols in an equation and have it link me back to where that term was first defined in the paper, either in another eqn or in the text. Tracing back in this way is a major pain point e.g. when trying to reproduce calculations. Seems like something journals/latex could easily implement in an automated fashion (maybe already possible?)
I use glossaries-extra. It allows the usual glossary stuff (acronyms), but can also be used to define symbols. All symbols then become hyperlinks, linking to the nomenclature at the beginning or end of the document. And in that nomenclature, glossaries- extra allows one to have a column of "first used", specifying the page of first occurrence.
