I think we have to expand our thinking about the toroidal sphere even more. When looking at maps, I noticed the da Vinci map, from 1514, which uses the Reuleaux Triangle. This triangle is formed from 3 intersecting circles, and is in the center of a trefoil.
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Hugh Everett's birthday! Pioneer of the Many-Worlds Interpretation of quantum mechanics. Let us celebrate by thinking about ontological extravagance. I will do so by way of analogy, because I have found that everyone loves analogies and nobody ever willfully misconstrues them.
We look at the night sky and see photons arriving to us, emitted by distant stars. Let's contrast two different theories about how stars emit photons.
One theory says, we know how stars shine, and our equations predict that they emit photons roughly uniformly in all directions. Call this the "Many-Photons Interpretation" (MPI).
But! Others object. That is *so many photons*. Most of which we don't observe, and can't observe, since they're moving away at the speed of light. It's too ontologically extravagant to posit a huge number of unobservable things!
So they suggest a "Photon Collapse Interpretation." According to this theory, the photons emitted toward us actually exist. But photons that would be emitted in directions we will never observe simply collapse into utter non-existence.
The physicist Hugh Everett III was born #OTD in 1930. His \u201crelative state\u201d formulation of quantum mechanics, which we now call the \u201cMany Worlds Interpretation,\u201d was published in 1957. pic.twitter.com/ZqMsZcPJDG
— Robert McNees, the bastegod (@mcnees) November 11, 2020
We look at the night sky and see photons arriving to us, emitted by distant stars. Let's contrast two different theories about how stars emit photons.
One theory says, we know how stars shine, and our equations predict that they emit photons roughly uniformly in all directions. Call this the "Many-Photons Interpretation" (MPI).
But! Others object. That is *so many photons*. Most of which we don't observe, and can't observe, since they're moving away at the speed of light. It's too ontologically extravagant to posit a huge number of unobservable things!
So they suggest a "Photon Collapse Interpretation." According to this theory, the photons emitted toward us actually exist. But photons that would be emitted in directions we will never observe simply collapse into utter non-existence.
@mugecevik is an excellent scientist and a responsible professional. She likely read the paper more carefully than most. She grasped some of its strengths and weaknesses that are not apparent from a cursory glance. Below, I will mention a few points some may have missed.
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The paper does NOT evaluate the effect of school closures. Instead it conflates all ‘educational settings' into a single category, which includes universities.
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The paper primarily evaluates data from March and April 2020. The article is not particularly clear about this limitation, but the information can be found in the hefty supplementary material.
3/
The authors applied four different regression methods (some fancier than others) to the same data. The outcomes of the different regression models are correlated (enough to reach statistical significance), but they vary a lot. (heat map on the right below).
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The effect of individual interventions is extremely difficult to disentangle as the authors stress themselves. There is a very large number of interventions considered and the model was run on 49 countries and 26 US States (and not >200 countries).
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I've recently come across a disinformation around evidence relating to school closures and community transmission that's been platformed prominently. This arises from flawed understanding of the data that underlies this evidence, and the methodologies used in these studies. pic.twitter.com/VM7cVKghgj
— Deepti Gurdasani (@dgurdasani1) February 1, 2021
The paper does NOT evaluate the effect of school closures. Instead it conflates all ‘educational settings' into a single category, which includes universities.
2/
The paper primarily evaluates data from March and April 2020. The article is not particularly clear about this limitation, but the information can be found in the hefty supplementary material.
3/
The authors applied four different regression methods (some fancier than others) to the same data. The outcomes of the different regression models are correlated (enough to reach statistical significance), but they vary a lot. (heat map on the right below).
4/
The effect of individual interventions is extremely difficult to disentangle as the authors stress themselves. There is a very large number of interventions considered and the model was run on 49 countries and 26 US States (and not >200 countries).
5/
It was great to talk about reproducible workflows for @riotscienceclub @riotscience_wlv. You can watch the recording below, but if you don't want to listen to me talk for 40 minutes, I thought I would summarise my talk in a thread:
My inspiration was making open science accessible. I wanted to outline the mistakes I've made along the way so people would feel empowered to give it a go. Increased accountability is seen as a barrier to adopting open science practices as an ECR
It also comes across as all or nothing. You are either fully open science or your research won't get anywhere. However, that can be quite intimidating, so I wanted to emphasise this incremental approach to adapting your workflow
There are two sides to why you should work towards reproducibility. The first is communal. It's going to help the field if you or someone else can reproduce your whole pipeline.
There is also the selfish element of it's just going to help you do your work. If you can't remember what your work means after a lunch break, you're not going to remember months or years down the line
Thank you again @JamesEBartlett for a fantastic talk (with a really nice personal touch) on reproducible workflows!
— RIOT Science Club Wolverhampton (@riotscience_wlv) February 16, 2021
Thanks especially for the co-leads @IMLahart for co-hosting and @DrManiBhogal for nabbing James!
Slides: https://t.co/CNqxzOhch1
Video: https://t.co/YjHEHuRJlz
My inspiration was making open science accessible. I wanted to outline the mistakes I've made along the way so people would feel empowered to give it a go. Increased accountability is seen as a barrier to adopting open science practices as an ECR
It also comes across as all or nothing. You are either fully open science or your research won't get anywhere. However, that can be quite intimidating, so I wanted to emphasise this incremental approach to adapting your workflow
There are two sides to why you should work towards reproducibility. The first is communal. It's going to help the field if you or someone else can reproduce your whole pipeline.
There is also the selfish element of it's just going to help you do your work. If you can't remember what your work means after a lunch break, you're not going to remember months or years down the line
Why are lunch breaks important for #code?
— Dr Rebecca Hirst (@HirstRj) February 11, 2021
If you can't remember what your variable names refer to after lunch, you sure as hell won't remember in 3 months.
