Fundamental research and humanities both have these funding issues. It may be worth a discussion if these fields could benefit from increased public funding, because some forms of research don't result in an immediate economic benefit.
Add to that the number of distractions that everyone is subjected to in the modern world, and I start to feel like it's no wonder we're still struggling with quantum interpretations or going beyond the standard model.
Now, I'm not saying that we should reduce the number of conferences or papers, or amount of outreach. Just the amount of time academics need to spend on them. Of course there will always be a few of the elite who will find time to sit and think for hours per day outside of these, nevertheless the harder you make it the more knowledge will suffer.
He published Freakonomics together with Stephen Dubner then went back into academia while Dubner went down the podcaster route.
15 years later, Dubner has reached millions of people with his work and Levitt recently started a podcast and soft quit academia after realizing that one of his best papers after years of research and hard work got 3 citations. He assumes fewer than 20 people will ever read that work.
Levitt in particular says he feels like his research can have a bigger impact if it’s shared broadly with people than if it reaches 10 other academics and that’s it. We’re not talking about likes on social media, we’re talking about breadth of audience for academic research and how scientists can do better than chasing meaningless citation stats.
Levitt talks about his thought process in this wonderful episode of Freakonomics. https://freakonomics.com/podcast/math-curriculum/
You did.
> Dubner went went down the podcaster route. 15 years later, Dubner has reached millions of people [...]
I assume this is measured in terms of subscribers or listen counts.
I'm not saying the Freakonomics Stevens have/haven't had quality contributions to the world, I'm not even saying anything w.r.t. average podcast quality vs. average academic paper quality. I'm only saying that people often measure impact along only one dimension.
This is the Freakonomics episode where he talked about this https://freakonomics.com/podcast/math-curriculum/
Interesting that they put their hopes on data fluency on the College Board while the SATs are falling out of fashion.
The ability to use the web, citation indices, etc. to discover and read papers has made the whole of the scholarly literature much more useful to me than it would have been a few decades ago.
The code itself is always usually a mess: no readme, no license, random binaries, and a 'pipeline' which is simply a bunch of perl and python scripts cobbler together from snippets found on the web.
People publish, then move onto the next project. There is no maintenance.
I agree with you that this is research and there's no reason for it to be pretty. The fact that it's unsightly and brittle makes a lot of people reticent about sharing it online since it could reflect on the quality of their non prototype code. Maintenance is a large burden and once the original goal of the paper has been proved, there's little benefit to the researcher to keep the code around, so I understand why they might say let's not release it at all.
A recent example of this was I was building a gesture classifier using an accelerometer to generate data. I decided do use an svm as based on what I had read, it would be the simplest to port to the microcontroller I was using. I was getting decent performance but needed to extract better features. I found several papers talking about the topic with some novel ideas and their impressive results. While it was nice to know that accuracy could get that high, none of the papers explained how the features they extracted were made. It was usually a one or two sentence line about using both time and frequency domain data.
Excuse me. Is this your actual experience or the meme that everybody is simply repeating?
In the admittedly few papers I have published, the reviewers’ feedback has been a net positive I wouldn’t be without.
Also, the general focus on code in science here on HN is so incredibly myopic and narrow minded. Code for research are not high-profile software projects. They are a piece in the toolbox used to solve a problem. Some grow to become larger projects, some fulfill their purpose and stay fixed in time.
One of the causes of the slowdown (even if marginal) of science and research in general is the administrative and social media overlays that were added to them.
I'm not sure you appreciate how hard this might be for someone who is not closely connected to a project.
The people who can do that reliably will have: a) the academic chops on a similar level of a peer reviewer b) social media skills. a) puts them back in the bracket of people you don't want to 'slow down'.
More over : the population of people who are good at doing something isn't necessarily the same as the one good at explaining it.
It's like saying Newton would have to spend 20% of his time explaining to 14yrs old kids what he's doing when someone less capable than him would do it as good but would leave Newton free for what he does best.
https://youtu.be/m05abdGSOxY