I noticed, via Twitter, that a colleague had written an interesting post about survival strategies for lecturers[Edit: I hadn’t appreciated that this had been written pre-pandemic, but it is what largely motivated my post]. I had been thinking about writing something similar, so thought I would pen some of my thoughts about how this pandemic has influenced university teaching. They won’t be quite as insightful as my colleagues.
I was quite fortunate that I wasn’t doing any lecturing when the pandemic struck, so I didn’t have to suddenly switch teaching modes in the middle of a semester. However, I do have a fairly heavy teaching load in the first half of semester one (which typically starts in September), so was rather dreading preparing for it. I also really dislike watching myself in a video, or even listening to myself, so really wasn’t looking forward to editing and captioning my lecture recordings.
A consequence of this is that I started early. I spent most of August and September turning my lecture notes into a presention (in one of my courses I normally do what is often referred to as “chalk and talk”) and pre-recording my lectures, which I would try to divide into 20 minutes chunks. I would typically re-record these at least twice, and spent virtually every morning drinking my coffee and editing the captions. I eventually did get into this, and got over my dislike of listening, and watching, myself. I don’t think I ever didn’t find some silly mistake in a recording, but I eventually realised that it wasn’t possible to re-record my lectures enough times to entirely avoid this.
The actual teaching involved releasing about a week’s worth of lectures in advance, then running one live online lecture. In one of the courses this involved working through an example problem, while in the other it involved going over one of the pre-recorded lectures. We’d then have one live online tutorial, and a set of in-person tutorials, that were very socially distanced (a few students in a room that would typically have a much larger capacity).
The response from the students was fantastic. Even though not everything went as well as it possibly could have, they really seemed to appreciate that we were doing our best. They also seemed to like having some live classes (either online, or in-person) and they seemed to appreciate having the ability to watch the pre-recorded lectures in their own time.
Even though it was a lot of work, I ended up quite enjoying it. I think it mostly did work quite well, and it did make me appreciate that there are alternative ways to teach. I wouldn’t like to repeat exactly this, but it has made me think about things we could start incorporating into our teaching (although I haven’t got any firms idea about what, or how).
I was possibly fortunate that I was teaching first and felt nervous enough about it that I started pretty early. Probably also fortunate that I had the time to do the preparation. I’m looking forward to going back to a more standard style of university teaching, but I do think that I’ve learned from having to teach under different circumstances, and I hope the students found it a reasonable learning experience too.
Her lines start with a Capital B, mine are lower case and in italic.
* * *
B. I am available today for ex but I know it’s late notice. Once I know how next week looks, I’ll let you know!
could be later on if you want to get it over, i have an outline
B. Ah sure!
could be soon
B. I’m here largely doing nothing Smiling face with open mouth and cold sweat
could be now let me get a coffee
B. Cool cool! I got mine, sure!
btw i’m on my laptop and my space key sticks i try tocorrect but ifi miss i hope youcatch them see this is how it is when i don’t correct
ah, ok i’ll send you the transcript beforehand now, let’s see my notes *becomes more serious* hello still on the boat?
B. Not today Today at friends’ place Ah we started 🙂 OK I can be more explicit and clear than that. We’re at the boat 3-4 days a week but unfortunately the marinas around here have live aboard limitations 😦
where are you
B. San Mateo, CA
so you made it all around the world
B. That’s sort of an open wound. We made it here from northern WA coast and were supposed to be heading south to Mexico right about now. But Covid plus some technical problems on the boat led to a change of plans. Right now we’re trying to figure out what we can/cannot realistically do this year.
i thought i caught a glimpse of you in turkey, where you’re from
B. I was there last summer. I don’t get to visit home that often. Maybe 4-5 times in total in the last 17 years.
so you mix and match the photos you post or i misremember
B. But we sure hope to sail there sometime. It’s a matter of timing. Yeah I may have posted something but I can’t remember either. I post too many photos I suppose and sometimes out of order.
my favorite ones are of course your dishes and your cocktails we talked about this chat around the time i wrote about the Auditing Problem
B. Ah yes we did. I remember that post!
that post was about replication, you wrote a piece on this with friends or colleagues
B. Yes. I have by now 4 papers that somewhat touches on or is directly related to replication and reproducibility issues. Two preprints, two published. I have not written anything specifically on replication markets other than on twitter though.
can you summarize your main takeaways
B. Can I start a bit earlier? From our motivation?
you can start wherever you please
B. Thank you 🙂
When I got first interested in the replication crisis and the following developments, I was very much fed up with my own field. My PhD was on experimental consumer behavior, which is sort of a spin-off of social psychology with a marketing flavor. Anyway it is a field experiencing the same problems social psych has. And I knew that wasn’t what I wanted to continue doing.
Luckily I also have a Masters degree in Stats and a desire to put that to better use. Also great collaborators.
At first I was following the replication conversations with delight, hoping that this meant things could change. But then I felt like these new discussions were still more superficial than I would have liked to see and somewhat hasty at replacing new heuristics with new ones. To me it wasn’t all that different from everything that preceded it. Still lots of talking, not a whole lot of depth. When people referred to reproducibility of results, I didn’t see a clear, precise definition. I didn’t see the ideas carefully evaluated, dissected. I didn’t feel like the right questions were being asked. I wanted to see the basics first, the foundations laid out.
B. Anyway, this desire to actually understand the dynamics driving the state of affairs we observe was the motivation behind my work. I wanted to find out for myself what reproducibility meant. Why it mattered. Or when it did. Whether we can tell anything meaningful about what we observe in replication studies. Whether it would be actually good for science to pursue higher reproducibility. etc.
I don’t or rather I can’t take any of these for granted. Work needs to come before insights. I observe lots of insights not based in anything but faith. So I digress. What was the question again?
that looks like a good justification for that paper
B. Ah cool the first paper 🙂 Yes! Exactly.
I’m both very fond of and proud of that paper. It’s everything I wanted it to be. Probably has something to do with interdisciplinarity of the team and 4 years of work behind the scenes.
4 years is a lot of work; it’s my favorite paper, i think
B. Let me find the second. It’s a homeless preprint. There are two versions and I like the first better. But it’s a weird one. Doesn’t follow the usual template.
This is somewhat of a conceptual analysis of some ideas about open science and reproducibility using basic statistical concepts.
ah, i thought it was the same
B. Tells me I need to learn how to write better titles.
well, you got to sell your model centrism why do you call your approach model-centric
B. Yes that was the core idea in the first two papers really. That we need to get away from focusing on hypotheses so much. Model-centric approach is much richer and it subsumes hypotheses.
what is the big difference
B. Good question. Let me think. I think it’s the way one sees how science makes progress. One way of viewing thinking about it is: We keep testing and rejecting hypotheses. These tests would guide us toward some ultimate truth (or an approximation of it) by accumulating loosely related facts. Another is: We keep updating our view of the world (or phenomena of interest). That is, we make scientific progress by exploring, selecting, comparing, evaluating, updating our models.
When you think in terms of models, you have to acknowledge the underlying assumptions, the variables of interest, the parameters, the constants, the model structure… It’s a complete picture. In a lot of hypothesis-centric literature, you cannot find a single assumption explicitly acknowledged. It’s obscure, underdetermined, underspecified, and not quite theoretically motivated. At least in the part of social science I am familiar with, which may not generalize outside. It seems to focus too much on binary outcomes and doesn’t talk much about how they relate to the phenomena. And doesn’t quite explain what’s going on. That was wordy and not very clear, I’m afraid but I’m not writing a paper so I’ll cut myself some slack 🙂
allow me to help: your paper’s main result is that “the scientific process may not converge to truth even if scientific results are reproducible and that irreproducible results do not necessarily imply untrue results” —so there is a need to accept that science is an open-ended quest
B. That’s one, for sure. Some others have been received much more interest though! Absolutely. Yes, I like that way of putting things.
and the model-centric approach seems to be more suited for exploratory research
B. Sure is. I imagine us searching through an infinite model universe. Trying to find the best strategy for an efficient search.
so you don’t dispute that there is a need for confirmatory research, you just ask that we approach the problem like scientists would, not cops
B. In my view, so much of what we do is description and exploration. But a hypothesis-centric view makes it seem like each hypothesis test is out to confirm something. I think that is deeply flawed.
it echoes an old divide
B. Oh yes, of course. There are times we will need to confirm. And yes, I do not like a cop’s view of science for us.
B. Yes now that you say so, it does seem like a natural transition to this new project. Similar underlying themes, different approaches. I am not a particularly “fun” presenter. I tend to be too serious and frown a lot. Maybe better to read the paper after all!
i like to listen to voices and am a visual learner and think leaving a textual trace is very important, but i also think that papers are on their way out, we should have sites
B. I tried to keep that one accessible to most audiences because I wasn’t sure who would be listening. Also, I am not the theoretical statistician in the team so I cannot pretend to derive the proofs myself.
B. I like talking about these ideas though. Obviously because I think they matter but also I know they spark some reaction in the listeners. Some things we talk about are not easy to digest right away.
Ah yes, that’s a more collaborative piece. based on a small workshop organized by Joachim Vandekerckhove and Michael Lee from UC Irvine.
the theme seems to be similar
B. The theme is similar but that’s understandable. I was invited because of that PLOS one paper. Because i had a different voice and new things to say. the idea about the workshop was, which of these new scientific reforms could possibly have a role in cognitive modeling and which did not vibe.
so there’s some kind of fight over computational models
B. I have to declare upfront that I am not a cognitive scientist. I wouldn’t possibly dare speak on their behalf. I have met great cog scientists and collaborated with them recently. But I have a different perspective on things and am not too familiar with their internal wars.
(we’re almost done, btw)
B. Seems like there is an overall tendency to marginalize modelers in psychology though. It’s not considered mainstream work even if it should be.
were i to find a theme, it’d be pluralism, but then i’m very biased, both toward you and toward pluralism i might as well plug that presentation by hasok
B. I’d love to talk about pluralism. So far my contribution to these science reform discussions have brought a model-centric and a formal perspective. We do need these perspectives. We cannot have a single approach dominate. That’s another takeaway from the Plos One paper too. Epistemic diversity is the key to avoid traps.
i suppose that’s how we add robustness eric winsburg reached similar conclusions
B. I am a fan of Hasok Chang’s. Inventing Temperature, this talk, … Wonderful!
i find him a very good counterpoint to STS theorizing who decided that philosophers can’t experiment?
B. It does make sense, no? I was just earlier having a chat with Iris van Rooij about a model she is developing with her colleagues. She uses deterministic models. We use stochastic. She tries to stay away from stats as much as possible. I run toward it
But we’re interested in similar problems. We necessarily have different approaches. At the end our conversation converged on how much we can learn from each other’s approaches while continuing to pursue our own. That’s beautiful to me.
that’s a great way to end the serious part
B. I gotta read that link but have not yet. But I thought philosophers do experiment nowadays. OK let us end it on that inspiring note 🙂
sometimes they do, sometimes they don’t
B. Right of course.
[inaudible digression about philosophy and philosophers]
B. I was just commemorating a review we received on the plos one paper. To paraphrase: “But you just have math and simulations. Where’s the science? Why should we believe you?”
*Where Is Science* is a project i have to make it’s a good question, but it’s not to be asked for that kind of silly gotcha game
B. Best approach to me is to ignore and disregard all hierarchies. They’re misleading and largely useless.
that makes you happier, and it shows
B. Yup it’s best to not partake of those games at all! It does. I feel kinda outside of the game. Idk why though. Where does this feeling come from?
i can play these games, and my tweeting character is good at that, it turns these games into an art form insecurity, mostly feelings of inferiority, the tournament structure, the little payoffs
B. It is an intriguing character. One that makes me feel ok with the anonymity. I have been increasingly suspicious of many anonymous accounts lately.
twitter in general suffers from that W is a good clown i like him
B. 🙂 He is likeable.
❤ “no u” would he reply
B. Haha! Idk that I am but I also lack that kind of awareness.
you are yourself, that should be enough one thing i wonder tho do you like music?
B. It would be paralyzing for me to think about my twitter as a persona and guess how people perceive it/me. Does anyone say no?
i like to end these chats with music
B. I do! So have I noticed 🙂 Nice!
then hit me with your best shot
B. Well it’s 2020 and the world is going batshit and politics is giving us nightmares everyday. So my cure is Boney M. Rasputin. Or Daddy Cool. Just don a cape, watch, dance like the front man, and have fun. (Also read up about the strange story of the whole project.) I have found that Boney M is not as popular in the US as it is/was in Europe but who can say no to disco?
Just watch and try to not smile.
why would i so there you have it wasn’t that hard, was it
B. No it wasn’t 🙂 It was a pleasure. And thank you! Hope I made at least some sense.
A couple of years ago I wrote a post where I tried to explain why I thought climate change was a different kind of problem when compared to most of the other issues we might face today. I find it a tricky argument to make, because I don’t want to suggest that the other problems we face don’t matter, or that there aren’t consequences to not addressing them now, but the essential irreversibility of climate change does make it a somewhat unique issue.
I noticed that Jonathan Gilligan had highlighted a quote on Twitter, from Jody Freeman, that – I think – neatly summarised the point
You can put rules back in place that clean up the air and water. But climate change doesn’t work like that.
Yes, in many situations, if we were to implement processes to address our impact, then we can reverse that damage that’s been done. Climate change doesn’t really work like that. A significant fraction of the CO2 we’ve emitted will remain in the atmosphere for a very long time.
This is illustrated by a figure from a very nice paper on how [p]ast climates inform our future, by Jessica Tierney and colleagues. The figure shows past, and potential future, atmospheric CO2 concentrations. The key thing is the x-axis, which shows a period of over 600000 years. On our current trajectory, atmospheric CO2 will remain above 400ppm for thousands of years, and won’t return to pre-industrial levels for 100s of thousands of years.
Additionally, we’ve already increased atmospheric CO2 to levels comparable to that of the Pliocene (a few million years ago) and could increase it to levels not seen for 10s of millions of years.
What I’m getting at is that what we’re doing is unprecedented and has extremely long-term consequences. This isn’t to say that we should ignore everything else and only think about addressing climate change. I do think, though, that it’s worth being aware of how climate change is likely different to the other kind of problems we may face and should bear that in mind when thinking about how to work towards a better future for all.
The paper claims that whatever we do, we’re now past a point of no return for global warming. It received quite a lot of media coverage, which I won’t link to, but there was a good response in the Independent – by Daisy Dunne – which includes a quote from Richard Betts:
Having talked to various colleagues, we don’t think there’s any credibility in the model.
What’s very odd is that you just need to look at the figures in the paper to see numerous problems. The paper considers two scenarios; an immediate cessation of emissions, and one where they reduce to zero by 2100. In both cases, the model suggests that atmospheric CO2 concentrations will reduce to 300ppm by 2200. This well below what is now regarded as likely; even if we stopped emitting now, atmospheric CO2 would probably not drop below 350ppm for many generations. The latter scenario also shows atmospheric CO2 starting to drop before emissions get to zero, which is also not consistent with our current understanding.
The paper also suggests that warming continues even though atmospheric CO2 concentrations are dropping. This is supposedly due to surface albedo changes, increasing atmospheric water vapour, and emission of carbon for melting permafrost. The surface albedo change is apparently much larger than other estimates, water vapour is a feedback, not a forcing, and cumulative carbon release from permafrost is (according to their paper) 175 GtC by 2500. This is roughly equivalent to what we’re likely to emit over the next 15-20 years, but over the next ~500 years. Not negligible, but not really enough to lead to the level of warming their model suggests.
For some reason, their model also suggests that the CO2 forcing will continue to increase, even if atmospheric CO2 drops back down to ~300ppm, which makes little sense.
My main point, which I’ve taken a while to get to, is that there are a number of obvious issues with what is presented in this paper that anyone who is working in this field should notice. It’s hard to see how anyone who has developed an earth system model wouldn’t notice these obvious problems, and it’s particularly difficult to understand how any competent reviewer could let these pass. They’re not exactly subtle points. Scientific Reports doesn’t exactly have a great reputation, but this is pretty egregious.
A couple of days ago, I retweeted an article with the title [t]he trouble with ‘Covid denialism’. I thought the article was reasonable, but some objected to the use of ‘denialism’. There are a number of very credible scientists who have promoted some of the scientific ideas being highlighted in this article and we should, ideally, treat these alternative scientific ideas with some respect and should engage in constructive discussions, rather than suggesting such people are in denial.
However, having been engaged in the public climate debate for quite some time, I’m somewhat inured to the use of denial, or denialism. On the other hand, this may be an opportunity to discourage its use at an early stage of a topic so that we can maybe encourage more constructive dialogue. I would certainly be in favour.
Unfortunately, my experiences in the public climate debate has also made me rather cynical. Certainly, in the climate context, the use of denial, or denialism often seems entirely justified and the complaints are typically more related to people trying to deligitimise their critics, than a genuine desire to improve the dialogue. It can be a way to try and get the freedom to promote contentious scientific views in public without being criticised. Similarly, in my experience in the climate debate, those who complain most about tone are often people who are quite comfortable being pretty blunt when it suits them.
I also tend to think that scientists shouldn’t expect the same level of engagement in the public sphere as they might in a more formal scientific setting. Scientists shouldn’t expect some kind of special treatment in the public sphere just because they’re scientists. They should, of course, get the same level of legal protection as anyone else who is engaging publicly, but they shouldn’t expect to not be judged for the views they choose to express, or the groups with which they choose to associate.
Of course, our understanding of Covid-19 is not nearly as mature as our understanding of anthropogenically-driven climate change. Hence, maybe we should avoid throwing around labels at this stage and maybe we can still engage in constructive dialogue with those who promote scientific ideas with which we disagree. You’ll excuse me, though, if I’m not confident that we’ll actually do either.
I was listening to the a Received Wisdom podcast. It’s a podcast by Shobita Parthasarathy and Jack Stilgoe, which I have written about before. At the beginning of the podcast, the hosts were discussing the Great Barrington Declaration, and Jack Stilgoe said something that I found quite interesting. He suggested that – in the UK – the Great Barrington Declaration has been taken up by certain groups to generate an alternative scientific narrative and went on to say
oh god, is this like climate change all over again? A vital debate about policy options actually gets had in the language of science.
I agree that this there are many parallels with what is happening now with respect to COVID-19 and what has been happening for many years with climate change. I also agree that it’s very unfortunate that debates about what we should do, end up being debates about the scientific evidence. I think both in the context of climate change and COVID-19, it would be much better if the public debate were more about what we should do, than about the science itself.
However, one thing that motivated my rather uncharitable previous post was that the research field that could help us to understand how to do this, is the very field to which the hosts of this podcast belong. Researchers in this field have had many years to study this in the context of climate change and have, in my view, largely failed to come up with suggestions as to how to mitigate this.
In fact, in my experience, some of the contributions from researchers in this field have been less than helpful. One way you might help to limit the policy debate degenerating into a discussion of the science is to stress where the consensus lies. That way it might be obvious who is basing their arguments on fringe views and who is basing them on the views held by a majority of relevant experts. However, researchers in this field have explicitly argued again consensus messaging, because it’s, apparently, polarising and narrow.
Jack Stilgoe himself suggested that the Lancet letter (a response to the Great Barrington Declaration) was potentially an example of stealth advocacy. I should acknowledge having signed the Lancet letter, but given the signatories, who has endorsed it, and the list of those presenting similar arguments, it would indeed seem to be presenting a consensus position.
So, if someone is going to undermine attempts to highlight the consensus, then it seems a bit ironic to then complain when the policy debate degenerates into the language of science. It seems like an obvious consequence of a situation where the scientific evidence suggests that we may need to do things that some would find inconvenient, or that might challenge their ideologies. They will clearly then be motivated to promote any evidence that seems to support their preferences and the debate will degenerate into one that’s more about the science, than about policy.
Maybe there are ways to avoid this without highlighting the consensus. If so, I’m not quite how this would work. I may well misunderstand the basic issue, but that the debate about COVID-19 has degenerated into a fight about science is unsurprising, given that this has happened in the climate context too. I do think that this distracts from the discussion that we should really be having: what should we do?
Would be nice if there were a way for scientists and those studying the science/policy interface to work together to find ways to address this issue. This, however, hasn’t worked all that well in the climate context and I suspect it’s going to be no better in the COVID-19 context either. I hope I’m wrong.
As Sonia Sodha mentions, The Honest Broker sets out a typology of science engagement, with one of the categories being stealth advocates. Stealth advocates are those who hide their advocacy behind a facade of scientific objectivity. Sonia Sodha implies that this applies to those associated with the Great Barrington declaration. If you’re thinking of how one might counter those who promote outlier ideas, what’s presented in The Honest Broker might sound like an appealing narrative. I would like, though, to urge some caution.
In the climate context, the narrative presented by The Honest Broker is not regarded as particularly constructive. For example. accusations of stealth advocacy have more commonly be aimed at mainstream climate scientists who have chosen to speak out, than at those who are promoting mis-information. You can even find the author making this accusation against Realclimate authors in this comment. In case you don’t know, Realclimate is probably one of the most credible climate blogs.
Of course, you might find some useful typologies in The Honest Broker and I’m not suggesting that one should dismiss it entirely. I do think, though, that it’s worth being aware of some of the history when considering if this might be a useful narrative to introduce into another contentious scientific topic.
In a related note, I wanted to end this post by mentioning a new project called EScAPE, which aims to evaluate science advice in a pandemic emergency. The project team includes a number of people familiar to my regulars, and is led by the author of The Honest Broker.
If you’re naive, like I was once, you might think: great, a group of researchers who will help us to better understand how to use science advice to develop effective policy. If you do think this, you’d probably be wrong. Their contributions in the climate context is often regarded (in my experience, at least) as not being wildly constructive, at least if you think that we should be using science advice to develop effective policy.
Some have been vocal critics of consensus messaging. I was also involved in writing a response to one of their papers that misrepresented what was presented in an IPCC press conference. A couple have recently re-litigated Climategate, when stolen emails were taken out of context and blown out of proportion. The leader of EScAPE is also often the source of claims that are then used to argue against climate action.
You may think the above is a little unfair, and maybe it is. I’m mostly suggesting that it may be useful to be aware of some history. I do think there is quite a lot of overlap between what has been happening in the climate context, and what is happening now with coronavirus. There may be a benefit in trying to avoid making the same mistakes twice.
The work was motivated by trying to explain what seemed to be some counter-intuitive results presented by the Imperial College group in mid-March, in a document often referred to as Report 9. Specifically, there are some scenarios presented in this report, where adding an intervention leads to more deaths than a similar scenario without that additional intervention. For example, if you look at Table A1, the model predicts that adding place closures (PC) to case isolation (CI), household quarantine (HQ) and social distancing of those over 70 (SDOL70), would ultimately lead to more deaths than if place closures had not been implemented. A similar effect occurs if you add general social distancing (SD) to a scenario with CI and HQ.
The reason for this counter-intuitive result is illustrated by the Figure on the right, which shows ICU bed demand for the scenarios presented in Report 9. Some of these produce a single wave of infections. However, in some cases, adding a new intervention, substantially impacts the first wave, but means that once the interventions are lifted you can get a second wave, which – if the most vulnerable are not suitably protected – could produce more deaths overall, than the equivalent scenario without this additional intervention.
So, does this mean we should not have added some of the interventions? Well, for starters, these are model projections none of which specifically match what we actually did. Also, as James Annan has pointed out quite forcefully on Twitter, some of the model parameters used in Report 9 were clearly not correct (i.e., the basic reproduction number, R0, was lower than we now know to be the case). We were mostly trying to understand why some of these results presented were counter-intiutive, than make any kind of specific prediction, or update what was presented in Report 9 in mid-March. The result may well be different if we were to redo this using updated parameters [Edit: I should have been clearer here. I mean the results presented in Report 9 might have been different, not that our results would have been different].
Additionally, in all of the scenarios presented in Report 9 where there was a single-wave leading to herd immunity, the ICU bed demand and the total number of deaths far exceed what we actually experienced. If we had followed such a scenario, it would almost certainly have over-whelmed the healthcare system and would have almost certainly been perceived as far too extreme. Hence, I don’t think that our paper specifically supports an argument against the lockdown (although people can, of course, make their own interpretations).
Does this mean that we should now follow some kind of herd immunity strategy? Again, these are model results, so one should bear that in mind when drawing interpretations. We did finish the paper by doing some comparisons with actual data, and the model does do well if you update the parameters (i.e., higher R0 value and the epidemic starting sooner than suggested by Report 9). However, there are lots of things that the model doesn’t include. It doesn’t include the long-term impact on those who get infected and don’t die. It does suggest that limiting deaths would require properly shielding the vulnerable, but it doesn’t tell us if this is actually possible. It doesn’t tell us if we will actually develop immunity. There are many caveats that, I think, should be considered before drawing strong conclusions.
At the end of the day, what we were really trying to do was better understand the results presented in mid-March, which I think we’ve now done. There may well be implications to this, but I do think one should be cautious of drawing strong conclusions from a single study that was more motivated by trying to clarify what’s already been presented than make any specific predictions.
no, AT’s is an astrophysicist’s blog, i’m just a ninja what kind of covid contrarianism?
“It’s no worse than the flu, shutting down is a huge overreaction” etc
shutting down was an overreaction but hindsight is 20/20 and this does not imply we can open up like some states did so notice the frame 1. yes 2. but 3. and
(I’m in the States, watching everyone open up)
ask him about ICUs the more people maintain distance and wear masks, the quicker we can open there is evidence that shutting down for kids was actually bad and he’s a pediatrician, so you can’t just dismiss everything he says same with breakthrough stuff
the Breakthrough Institute follow AT’s links, the article provides the background but basically, mike is what we call an Ecomodernist hippie 2.0, cali style green, but tech so nuclear, cities, and ogms of course he made TED talks
A Green Vision of Technology nuclear is really hard to lift off in the western world these days too risky, too expensive, too much regulations cities are fine, but even then we got space and Le Corbusier’s utopia leads to really bad cities and is fascist
I don’t really understand this attitude. It seems like a kind of hollow environmentalism, with technology fixing a problem which it can’t even seem to understand as a problem…
think of Dennett, but for green stuff optimism is an attitude that people like it’s not that problems go away if you only focus on feel-good futuristic utopias but when you had a long day at work, it makes sense
“While many mainstream environmentalists want to make peace with nature through the sustainable use of natural resources, the modernists want to cut the links between mankind and nature.”
yes, so let’s reinvent Descartes
Man, read alongside Baird Callicott this just sounds psychotic Yeah it’s wicked Cartesian
the opposition is probably between two strawmen most reasonable persons would agree that we need a little of both so focus on what you share with your bro
Okay, thanks for the resources
the actual models have already taken into account technological fixes, and since the future is not rosy, your bro is better be right the tl;dr is this say yes try not to say a bigger “but” and since he’s into futurism, dream about and’s with him good luck
* * *
This simple exchange emphasizes two tips. The first is to proceed dialectically. The second is to show humanity.
The yes-but-and game plan echoes what Randy calls the ABT technique. I’m not sure what’s special about that. If people need to buy seminars to learn conversation manners, so be it.
(Legend has it that the thesis-antithesis-synthesis comes from Hegel. Problem: Georg mentioned it once, only to mock it. Gustav haz receipts. By serendipity, Hegelianism is currently being revived by American philosophers. One culprit could be Wilfrid’s avatar.)
The second tips echoes George’s, especially those in his How to Talk to a Denier. Seek common ground; show respect; hold and own your views; tell your personal journey; frame your points to connect with your interlocutor’s worldview; offer rewards.
These tips apply to conversations in general. They sometimes apply to ClimateBall, but online exchanges go beyond conversational conventions. Mileage varies. As a philosopher once said, plans are good until you get punched in the face.
There was a recent Conversation article about methane called Climate explained: methane is short-lived in the atmosphere but leaves long-term damage that caused a bit of a stir on Twitter. One way people assess the significance of different greenhouse gases, is to use what is called the Global Warming Potential (GWP). This is determined by integrating the radiative forcing due to a pulse of a particular greenhouse gas over some time interval and then comparing that to the equivalent calculation for a pulse of CO2 of the same mass.
A greenhouse gas like methane has a lifetime of only about a decade, but the initial radiative impact is so large that even if you calculate the GWP over a period of 100 years, it is still has a much larger GWP than CO2. This calculation is correct, but people then interpret this as suggesting that the climate impact of a pulse of methane after 100 years will be much greater than the impact of a pulse of CO2 of the same mass. This is not correct, because most – if not all – of the pulse of methane will be gone after 100 years.
If you consider CO2, then if emissions are increasing, warming accelerates. If emissions are constant, then we continue warming at a constant rate. If emissions are going down, then we continue to warm until emissions get to zero.
Methane, on the other hand behaves quite differently. Methane emissions can increase and we could still end up warming at a constant rate. If methane emissions are constant, then we’d relatively quickly reach a state where methane-driven warming stabilised. If methane emissions start going down, then the impact of methane would actually lead to cooling, and we could eventually reverse all the methane-driven warming. By comparison, the only way to reverse CO2-driven warming is to actively remove CO2 from the atmosphere.
There are, however, some complications. If we’ve had increasing methane emissions for a long time, then this could have led to warming of the deep ocean, which will persist for a long time. If the source of methane is fossil-fuel-related, then when it decays to water and CO2, this will be a new CO2 molecule, which will contribute to long-term warming. However, relative to the long-term impact of direct CO22 emissions, these impacts are probably still quite small.
One reason why I think this is important is highlighted in this Realclimate post by Ray Pierrehumbert. If we think that there is some long-term benefit to rapidly reducing methane emissions and we do so at the expense of reductions in CO2 emissions, then we could end up reducing emissions of a species that will have little long-term impact while failing to reduce the emissions of one the impact of which will persist for generations.
This is not, though, to argue that we shouldn’t be looking at reducing methane emissions. All I’m suggesting is that we should be properly comparing the impact of the different greenhouse gas species when deciding what we should do and should not be basing these decisions on a metric that probably over-esimates the impact of short-lived greenhouse gases, like methane.
There’s also a potential fairness issue. When we expect a CO2-emitting industry to reduce their emissions, we’re effectively asking them to limit how much they contribute to future warming. When we expect a methane-emitting industry to reduce their emissions, we’re effectively asking them to reverse some of their past warming. There may be good reasons for doing this, but I would argue that it’s better to be clear about this than to suggest an equivalence that isn’t actually correct.