https://statmodeling.stat.columbia.edu/2022/12/08/the-cleantech-job-market-every-modeler-is-supposed-to-be-a-great-python-programmer/ Skip to primary content Statistical Modeling, Causal Inference, and Social Science Search [ ] [Search] Main menu * Home * Authors * Blogs We Read * Sponsors Post navigation J. K. Rowling (2) vs. Joan Didion; Arnold advances The cleantech job market: Every modeler is supposed to be a great Python programmer. Posted on December 8, 2022 2:56 PM by Phil This post is by Phil Price, not Andrew. I've had a run of luck ever since I left my staff scientist position at Lawrence Berkeley Laboratory to become a freelance consultant doing statistical modeling and forecasting, mostly related to electricity consumption and prices: just as I finished a contract, another one would fall into my lap. A lot of work came my way through my de facto partner Sam, but then my friend Clay brought me into a project, and every now and then my friend Aeneas has something that he needs for his company, and I had a couple of clients who found me through having heard about me without any personal connection. One lesson is: even in today's world, with LinkedIn and websites and blogs and other ways of making ourselves known to the world, personal contacts matter a lot in getting consulting work. Or at least that has been the case for me. That's been good for me because I've had good contacts, but it's not necessarily good for society. If you're younger and don't have a lot of work experience, and you don't have many friends doing the same sort of work you're doing, you won't have the advantages I've had. So, for seven years everything was great. But this year has not gone so perfectly: I'm down to two clients at the moment, and one of them only needs a little bit of work from me each month. I'm looking for work but, never having had to do it before, I don't really know how. But one thing I know is that people use LinkedIn to look for jobs and for people to fill those jobs, so I updated my long-moribund LinkedIn profile and clicked a few buttons to indicate that I'm looking for work. Several recruiters have contacted me about specific jobs, and I've also been looking through the job listings, looking for either more consulting work or for a permanent job. Three things really stand out. Here's the TLDR version: 1. There's a lot of demand for time series forecasting of electricity consumption and prices. 2. The modeler has to write the production code to implement the model. 3. It's gotta be Python. That's pretty much it for factual content in this post, but then I have some thoughts about why one aspect of this doesn't make much sense to me, so read on if this general topic is of interest to you. I. Modeling and Forecasting of Electricity Supply, Demand, and Price. There are quite a few jobs for electricity time series modeling, and for optimization based on that modeling. Some companies want to predict regional electricity demand and/or price and use this to decide when to do things like charge electric vehicles or operate water pumps or do other things that need to be done within a fairly narrow time window but not necessarily right now. And then there are other forecasting and optimization problems like whether to buy a giant battery to use when the electricity price is high, and if so how big, and how do you decide when to use it or recharge it. All of this stuff is right up my alley: I'm good at this and I have lots of relevant experience. To give an example of a job in this space, here's something from a job description I just looked at (for a company called Geli): "Your primary responsibility will be to lead the development of our time series forecasting models for solar and energy consumption using machine learning techniques, but you will also help develop new forecasting models as various needs arise (eg: prototyping forecasting wholesale prices for a new market)." This is extremely similar to work I have been doing off and on for one of my clients for the past eighteen months or so. Sounds great. And there's a bullet list for that same job listing: * Feature engineering * Prototyping new algorithms * Benchmarking performance across various load profiles * Integrating new forecasting algorithms into our production code base with robust test coverage * Collaborate with the rest of the team to assess how forecasts can be adjusted for various economic objectives. * Proactively identify opportunities within [our company] that can benefit from data science analysis and present those findings. * Work collaboratively in a diverse environment. We commit to reaching better decisions by respecting opinions and working through disagreements. * Gain in depth experience in an exciting industry as you work with storage sizing, energy financial models, energy tariffs, storage controls & monitoring. Almost all of that bullet list sounds great to me. But not literally all of it. II. Modelers have to be coders. The one thing that doesn't? "Integrating new forecasting algorithms into our production code base with robust test coverage." It's funny how this is just sort of stuck in there among the other items because writing production code, and the tests for the code, is a different skill from conceiving, writing, and testing the models in the first place. If you talk to the recruiters or look at the detailed requirements for the job, it's explicit that they want the person who does this job to write the production code to implement the models. III. The coding is going to be in Python One of the requirements for that job: "Advanced Python skills, as well as familiarity with pandas and scikit-learn." Everyone wants Python. I have looked at a few dozen job listings that are superficially similar to this one and every one of them wants Python. I haven't seen a single one where they're looking for R or even C++; Python rules this roost. I think this may not be the case for other STEM areas like biotechnology, where I think R is still common, but in energy forecasting and optimization Python is really all that matters. I think this may be related to the desired relationship between modeling and coding: R is (in my opinion) vastly better than Python for exploratory data analysis and graphics. I'm good with R and decent with Python and I find it much faster and more pleasant to do my initial analysis and simple modeling in R, to the extent that I'll sometimes do it that way even if I ultimately need to deliver something in Python. When I was a Python newbie a few years ago I thought this was just lack of experience on my part, but it's been clear for a while that that is not the case. Python doesn't yet have anything remotely close to ggplot for rapidly making exploratory graphics, for example. The fact that Python is preferred to R for production code is unsurprising. R is extremely slow at a lot of tasks, for one thing, even more than Python. For another, R's object-oriented programming implementations seem a bit weird; I think they were not originally part of the language at all but were sort of grafted on, whereas Python's object-orientation is more organic. R has at least four object-oriented systems you can use (S3, S4, RC, and R6) and there are cases to be made for all of them, which is maybe an indication that none of them are all that great. IV. Discussion The fact that all of these companies want the modeler to write production code (literally all that I have seen so far) is a problem for me because I don't like writing production code and I'm not very good at it. I claim to be very good at modeling and not good at production coding, but you'll have to take my word for my modeling skills...so I hope Andrew (Gelman) won't mind if I use him as an example instead, because you have more reason to believe me when I say: Andrew is among the best in the world at conceiving of Bayesian mult-level models -- certainly among the top few percent of people who regularly do such modeling -- and yet I think he would agree that he's no great shakes at coding them once they're conceived. Well, I write code like Andrew does, which is the way the Neanderthals did it: I tend to have a procedural rather than an object-oriented way of thinking of things, I tend not to think at all about computational efficiency when I'm designing the model, and I often write code that looks kinda ugly and hard to read unless/until I go back later and fix it up. It's a bit hard for me to judge my skills compared to the average programmer but I think that I write fair but not good Python code, and certainly not excellent Python code; if I were being graded among professional Python programmers I'd be hoping for a B- but expecting a C. If a company says that they need excellent Python skills, and they mean it, then I'm not the right person for that job. I'm a fairly intelligent person and I'm sure I could learn to write better code if I have to, and to some degree I don't much mind if I have to...but I am never going to _enjoy_ coding the way I enjoy the modeling part of the task. I'd much rather get something working and then hand it off to someone else who can refactor it for speed and clarity, and have it conform to the desired style conventions, etc. etc. There's a lot of overlap in the skills required to write a good model and the skills required to write a good program, but the overlap is very far from perfect. Because of my enjoyment of modeling but dislike of programming qua programming I may be biased in my evaluation of the situation, but that doesn't mean I'm wrong when I say: I don't think it makes a lot of sense to require that the modeler write the production code and the tests. Or rather, this might make sense for a really small company but I don't think it makes sense for the companies I'm looking at. It's sort of like putting together a football team and requiring that every player be able to play both offense and defense. It's not like it's totally ridiculous -- if someone has the skills to be a wide receiver they can probably learn to cover the other team's wide receivers pretty well -- and certainly if you do find someone who is great at both roles then it makes sense to hire them. But as a requirement it is very limiting. You're trying to optimize the performance of your team, and in general you're not going to get that if you insist that every player fill multiple roles. Fred Brooks, author of the classic book "The Mythical Man-Month", died recently. I don't know if anyone reads that book anymore but for a few decades it was seen as a valuable source of insights into developing software systems but also into management in general. One of Brooks's points is that in programming, as in any sphere of human endeavor, the best people are much much better than average, even among professionals. The best basketball player on a professional team is much better even than the fourth or fifth-best. In the past few months tens of thousands of programmers have been laid off here in the Bay Area. Literally tens of thousands. Some of these are much better than I will ever be at programming, even if I really try to improve. Different people are talented at different things and some people are talented programmers. Others of us are talented modelers. Why not let me use my Neanderthal-level programming skills to get my model working, and then pass it along to one of these talented programmers to refactor it into something compact and readable, and write the tests for it? This either frees up my time to do more modeling, or to sit around doing nothing and not getting paid. Hire me part-time or as a consultant to write the models, and let the great programmers do the programming. Indeed, this is exactly how things have gone with my work for one of my current clients. We started out with just me and my friend Clay trying to do everything in a software development task. We were a great team for doing the basic modeling but we were struggling with turning it into a good program so we brought in a frontend programmer and a backend programmer and put the entire codebase into their hands. Between the two of them, they refactored just about everything Clay and I had done. The hours per month that Clay and I had been putting into the project dropped way back because the other two were now doing most of the work, but that's the way it should be...in my opinion. Unfortunately for me, the job market does not seem to agree. It appears I will have to improve my Python programming skills, so I'm going to work on that. There are plenty of online tutorials and other resources so I guess I'll look into some of those. If you have advice please leave it in the comments. This post is by Phil. This entry was posted in Jobs by Phil. Bookmark the permalink. 10 thoughts on "The cleantech job market: Every modeler is supposed to be a great Python programmer." 1. [6ac1df32]Ethan on December 8, 2022 3:21 PM at 3:21 pm said: > The fact that Python is preferred to R for production code is unsurprising. One other likely aspect is that Python has a much better error handling system than R, which can often be critical for production systems. A lot of R code will just crash if it runs into an error, while Python tends to rely more on exceptions that can be smoothly handled. > If you have advice please leave it in the comments. Not sure about your development setup, but my main tip is to try out Visual Studio Code for Python development. Also, check out Python's new type hint features, those are generally essential for large codebases. http://mypy-lang.org/ Reply | + [6ac1]Ethan on December 8, 2022 3:25 PM at 3:25 pm said: Also, even for Python development, C++ skills can be extremely useful. Being able to implement critical parts of the code in C++ (and use those critical parts in Python) is extremely handy! Reply | 2. [538c478d]Dale Lehman on December 8, 2022 3:30 PM at 3:30 pm said: You got my attention! I am extreme - more so than probably anybody that regularly reads this blog. I do virtually no coding in any language. I'm not advocating that as a general positive trait, and I certainly don't advocate that for my students. But I don't think that coding (even poorly done) is necessary or sufficient for good data analysis. I recognize that a production environment does require it, but as you suggest, that need not mean that everybody that works with data must be responsible for coding it for production. What I find puzzling and disturbing is the pronounced role given to coding skills for data scientists, rather than to data sense-making skills. I think it is largely due to the former being much easier to measure than the latter. It may also be due to the fact that many decision-makers view data analysis as something that must be done, but not something they really take seriously - they will ignore the analysis if it doesn't suit them (or rather insist it be redone until it shows what they want). As long as some algorithm gets put into production, they can check of a task accomplished and nobody worries much about what the algorithm is doing. Poor decisions may result, but it is difficult to attribute the responsibility. So, I echo Phil's concern though I doubt he would go as far as I do in my complaint. Reply | 3. [85a65305]Skathmandu on December 8, 2022 3:40 PM at 3:40 pm said: Wow, I'm feeling this pretty much word for word. I'm a methods-heavy epidemiologist working in industry and my job is maybe 80% programming, 20% modeling. I love the modeling part, am very slow and clunky on the programming part, but it's not like there are loads of modeling jobs waiting for me... Reply | 4. [9ed09dba]Mitzi on December 8, 2022 3:55 PM at 3:55 pm said: "Python doesn't yet have anything remotely close to ggplot for rapidly making exploratory graphics, for example." Actually it does - a pretty much feature-by-feature port of ggplot2 called "plotnine". I put together a case study last summer showing how to use it: https://mc-stan.org/users/ documentation/case-studies/radon_cmdstanpy_plotnine.html Reply | 5. [61c1be38]John Williams on December 8, 2022 4:44 PM at 4:44 pm said: Here is a perhaps amusing story about a failure in forecasting electrical demand. I live in Petrolia, in a remote part of Humboldt County, CA, in the "Emerald Triangle." A few months ago our electrical utility, Pacific Gas & Electric, fessed up that it had no more capacity to serve the southern part of the county, because electrical use by the marijuana industry for greenhouses, drying plants, etc., has maxed out PG&E's transmission capacity. Reply | + [25e4]Phil on December 8, 2022 5:44 PM at 5:44 pm said: One of my first consulting jobs, back in 2015, involved looking at electric vehicle charging: how much was it happening, how much was it increasing, to what extent could we forecast what it would look like over the next decade and longer, etc. The client was PG&E, and they were trying to figure out how their infrastructure would need to change in order to charge all the electric vehicles that they could see coming over the horizon. One of the big issues was: how do you know how your existing customers with electric vehicles are behaving? How often do they charge them, for how long, starting at what time, etc. We (me and my partner in the work) asked about the feasibility of getting data on who owns electric vehicles, e.g. by using California's data on car registrations, but...well, I don't know what the legal impediments would have been but we were told it was definitely not feasible on the timescale of our consulting project. What PG&E did know, though, was who was on an electric vehicle rate plan. If you owned an electric vehicle you could get on a special PG&E rate plan that made electricity very cheap overnight but more expensive during the mid-afternoon and early evening: they want EV owners to charge when the grid is not under stress. Not everybody with an EV is on an EV rate plan, indeed many are not; and some people get on the plan but then get rid of their EV but don't switch back, so this isn't perfect but it's what we had. So we get the data and we're looking at this and that, including looking at whether we can find a signature of EV charging so that we can determine which of PG&E's customers have electric vehicles but aren't on an EV rate. One oddity that stuck out was that in Humboldt County a disproportionate fraction of customers were on an EV rate. You can only get on an EV rate if you have an electric vehicle registered to you, and it seemed pretty amazing that Humboldt County would have so many EVs..especially seven years ago, when EV penetration was much lower than it is today (and it's still pretty low). But also, when we looked at the electricity consumption pattern of those customers it didn't look like EV users elsewhere. It's really easy to see when someone starts charging an electric vehicle, because that immediately becomes the biggest load of the day by far. And of course you can see when that load shuts off. But some EVs haven't been driven very far and only need to recharge for a few hours; others need to charge all night; etc. So when you look at the load in EV households you see a wide variety of durations for charging. But not in Humboldt! In Humboldt County there were lots and lots of customers whose maximum load would start the moment the price dropped, and the load would stay at the maximum all through the night and the next morning and wouldn't turn off until the price stepped up again. As you have no doubt recognized by now, these people were not charging electric vehicles, they were growing pot. Reply | 6. [268519d0]Jonathan (another one) on December 8, 2022 5:01 PM at 5:01 pm said: I'm a modeler who's a sometime *clever* programmer but never a *great* programmer as well. Here's my suspicion. If you have separate guys doing the the programming and the modeling: (1) they can get into fights that management can't resolve because management has now idea *how* to resolve them. (2) When the project goes bad, neither the programmer nor the modeller is going to take teh blame. (3) Management wants a production model. A great model they can't turn into a production model is just as useless as a crappy model brilliantly instantiated in a program. So what they really want is a modelling/production code team. But they don't know how to to pair the two halves together, or how to buy one without the other. So they insiste on both, knowing at least now if the project goes bad, they know *exactly* who to blame. A final consulting anecdote. At the 500 or so sized company I worked at for years, I did more modelling than anyone else and coded it up like you did... in code that worked, but was... bad. So I asked if I could just be relieved of those duties and just set up a modelling department with no programming responsibilities. They said no, and said it was largely because of the reasons above. They'd rather have kludgy code than fights betwee modellers and programmers. Reply | 7. [34bf2b2a]somebody on December 8, 2022 5:02 PM at 5:02 pm said: I am a full-stack engineer and statistical modeler, and yeah this is a problem. The steel man reason for this lack of division of labor is that it's easy for things to get lost in the abstraction. It's pretty easy for seemingly innocuous implementation decisions to meaningfully alter the distribution of model inputs in a way that creates serious performance differences between prototyping and production. But this is a problem that can be solved by good communication and code review practices. The bigger reason in my opinion is that bad code is easy to notice while bad models are not that obvious, so most companies in practice only need software engineers who know a little bit of modeling. The modeling they're looking for is the ability to find and grab covariates that look relevant, apply some basic log(1 + x) transformations, and feed them into a black box point estimator (usually xgboost), and then graph a cross validated ROC curve. In other words, a modeler in a role like this needs 1. The quantitative literacy to understand what numbers might be relevant and how to put them on a reasonable scale 2. The technical skills to actually pull those numbers from a datastore and write outputs to another datastore 3. The knowledge to specify one of a family of off-the-shelf algorithms that's appropriate Once this is done, if the model raises an unhandled exception during every other data pull or eats all the CPU on a source database or takes 10x too long to run, everybody notices immediately. If the output numbers exist on time and are the correct datatype, but are completely ridiculous, it'll take a much longer time for anyone to notice, and the only ones who would notice are confined to a much smaller domain. If the output numbers seem reasonable, but have a subtle bias or are not as tight as they could be, nobody might ever notice. It might get exposed if the model is put in charge of hard financial decisions that get A/B tested or otherwise evaluated (insert issues with A/ B here). But otherwise, a lot of model performance evaluation is left to the discretion of the modeler themselves. So I'd say you're probably severely overqualified for what these people are looking for in terms of statistics and modeling. A lot of them aren't expecting a custom application specific model, they're expecting you to be able to write a SQL query and glue the outputs to prophet or a recursive boosted tree (which is, imo, a shockingly bad product for forecasting, its stan backend notwithstanding). I think this data plumber + algorithm cookbook approach is fine to get some smoothing or relative ordering for reducing the complexity of some decisions. But it gives up a lot more than people think; where units are not truly i.i.d., where errors are clustered, where uncertainty quantification and calibration are important, all of which represent more real-world problems than people typically assume. Needless to say, I'm not totally happy with the status quo. Too many people think that because sklearn.classifier.predict_proba gives a vector constrained to the unit simplex, it must be giving a calibrated probability, and the only ones with the standing to tell stakeholders that it isn't are the ones giving it to them in the first place. People want answers fast and confident, and it's tempting to give it to whatever instead of taking the time to check if it's correct; who's going to check anyways? Reply | Leave a Reply Cancel reply Your email address will not be published. Required fields are marked * [ ] [ ] [ ] [ ] [ ] [ ] [ ] Comment * [ ] Name [ ] Email [ ] Website [ ] [Post Comment] [ ] [ ] [ ] [ ] [ ] [ ] [ ] D[ ] * Art * Bayesian Statistics * Causal Inference * Decision Theory * Economics * Jobs * Literature * Miscellaneous Science * Miscellaneous Statistics * Multilevel Modeling * Papers * Political Science * Public Health * Sociology * Sports * Stan * Statistical computing * Statistical graphics * Teaching * Zombies 1. Phil on OpenAI's GPT chat bot enters the uncanny valleyDecember 8, 2022 5:54 PM I don't know the origin of TMSAISTI -- it definitely goes back quite a few years -- but here's a... 2. Phil on The cleantech job market: Every modeler is supposed to be a great Python programmer.December 8, 2022 5:44 PM One of my first consulting jobs, back in 2015, involved looking at electric vehicle charging: how much was it happening,... 3. somebody on The cleantech job market: Every modeler is supposed to be a great Python programmer.December 8, 2022 5:23 PM Oh yeah and some dialect of SQL for data retrieval, usually based on postgresql 4. Owen on OpenAI's GPT chat bot enters the uncanny valleyDecember 8, 2022 5:15 PM Such different experiences! I really enjoyed real analysis - in my experience the beauty was that the intuitive definitions (eg.... 5. somebody on The cleantech job market: Every modeler is supposed to be a great Python programmer.December 8, 2022 5:02 PM I am a full-stack engineer and statistical modeler, and yeah this is a problem. The steel man reason for this... 6. Jonathan (another one) on The cleantech job market: Every modeler is supposed to be a great Python programmer.December 8, 2022 5:01 PM I'm a modeler who's a sometime *clever* programmer but never a *great* programmer as well. Here's my suspicion. If you... 7. John Williams on The cleantech job market: Every modeler is supposed to be a great Python programmer.December 8, 2022 4:44 PM Here is a perhaps amusing story about a failure in forecasting electrical demand. I live in Petrolia, in a remote... 8. Anonymous on J. K. Rowling (2) vs. Joan Didion; Arnold advances December 8, 2022 4:40 PM She's "written" more Harry Potter stuff since (without an editor) and it's... not good. Google "Hogwarts plumbing". 9. Sam S on Update 3 - World Cup Qatar 2022 predictions (round of 16)December 8, 2022 4:01 PM Since there aren't ties in the knockout rounds, is the model calling draws based on "tied at full time" or... 10. somebody on Time Series Forecasting: futile but necessary. An example using electricity prices.December 8, 2022 3:55 PM More on this My preferred way to put things like that into the model would be to fit a mixture... 11. Mitzi on The cleantech job market: Every modeler is supposed to be a great Python programmer.December 8, 2022 3:55 PM "Python doesn't yet have anything remotely close to ggplot for rapidly making exploratory graphics, for example." Actually it does -... 12. Skathmandu on The cleantech job market: Every modeler is supposed to be a great Python programmer.December 8, 2022 3:40 PM Wow, I'm feeling this pretty much word for word. I'm a methods-heavy epidemiologist working in industry and my job is... 13. Adam Sales on J. K. Rowling (2) vs. Joan Didion; Arnold advances December 8, 2022 3:33 PM A new Harry Potter story would be fun! But I think if she has one up her sleeve she'll probably... 14. Dale Lehman on The cleantech job market: Every modeler is supposed to be a great Python programmer.December 8, 2022 3:30 PM You got my attention! I am extreme - more so than probably anybody that regularly reads this blog. I do... 15. Ethan on The cleantech job market: Every modeler is supposed to be a great Python programmer.December 8, 2022 3:25 PM Also, even for Python development, C++ skills can be extremely useful. Being able to implement critical parts of the code... 16. Ethan on The cleantech job market: Every modeler is supposed to be a great Python programmer.December 8, 2022 3:21 PM > The fact that Python is preferred to R for production code is unsurprising. One other likely aspect is that... 17. Kaiser on Successful randomization and covariate "imbalance" in a survey experiment in NatureDecember 8, 2022 3:01 PM +1 in particular ,those p-values. should readers care about the individual p-values? 0.004 vs 0.007 etc. On a second look,... 18. Kaiser on Successful randomization and covariate "imbalance" in a survey experiment in NatureDecember 8, 2022 2:55 PM I also prefer grids although in this case, shifting to grids causes some decisions to be made about the other... 19. Chris Wilson on OpenAI's GPT chat bot enters the uncanny valley December 8, 2022 2:48 PM My undergraduate alma mater introduced a hybrid "calculus with theory" sequence that smattered in the relevant theoretical stuff while teaching... 20. Phil on OpenAI's GPT chat bot enters the uncanny valleyDecember 8, 2022 2:42 PM Yeah, I just asked it for python code to discard every row of a pandas datafile in which the column... 21. Jessica Hullman on OpenAI's GPT chat bot enters the uncanny valleyDecember 8, 2022 2:38 PM Well, I'm glad ChatGPT and I agree on the ambiguity. Was going to chalk it up to my general lack... 22. Andrew on J. K. Rowling (2) vs. Joan Didion; Arnold advances December 8, 2022 2:23 PM Zhou: I was kinda hoping she'd come up with a new Harry Potter story! I haven't actually read the Harry... 23. Zhou Fang on J. K. Rowling (2) vs. Joan Didion; Arnold advances December 8, 2022 2:18 PM Everyone knows what Rowling would talk about and I'm rolling my eyes already. Didion please. 24. Anonymous on J. K. Rowling (2) vs. Joan Didion; Arnold advances December 8, 2022 2:15 PM Replied to the wrong comment.... meant to reply to Jonathan 25. Unanon(euoid) on Successful randomization and covariate "imbalance" in a survey experiment in NatureDecember 8, 2022 2:15 PM Anoneuoid, I doubt you are a virologist, microbiologist, or immunologist. My model of you is someone with C.S. or developer... 26. Mark C. O'Connor on Do doctors get too little respect nowadays? Or too much?December 8, 2022 2:14 PM I have always called my physician, surgeon, dentist, optometrist, etc. "Doctor" even though they almost always call me by my... 27. Anonymous moose on Do doctors get too little respect nowadays? Or too much?December 8, 2022 1:57 PM > But what is missing from both the implicit bias and any new findings of differential informality of physicians (by... 28. Alan Goldhammer on J. K. Rowling (2) vs. Joan Didion; Arnold advancesDecember 8, 2022 1:51 PM J.K. Rowliing is for kids; Joan Didion is for adults. Didion's scope of work was vast and her commentary on... 29. Josh on OpenAI's GPT chat bot enters the uncanny valleyDecember 8, 2022 1:49 PM I agree with Phil. This is a clear way to signal that something isn't the case/didn't happen. Interesting, ChatGPT doesn't... 30. Anonymous on J. K. Rowling (2) vs. Joan Didion; Arnold advances December 8, 2022 1:23 PM But there's nothing to test. PrezBo's stance on free speech is well established. The university has hosted far more controversial... 31. Anoneuoid on Successful randomization and covariate "imbalance" in a survey experiment in NatureDecember 8, 2022 1:21 PM The quoted passage was about "herd immunity". The idea was that if everyone got vaccinated the virus would disappear, because... 32. Anoneuoid on Successful randomization and covariate "imbalance" in a survey experiment in NatureDecember 8, 2022 1:13 PM Measles does contradict your points, but you merely need to elaborate on them with more detail. Did you mean "doesn't"? 33. Russ Lyons on Successful randomization and covariate "imbalance" in a survey experiment in NatureDecember 8, 2022 1:04 PM @Anoneuoid Thank you for the info and the link; very useful. Measles does contradict your points, but you merely need... 34. Andrew on J. K. Rowling (2) vs. Joan Didion; Arnold advances December 8, 2022 1:03 PM Jonathan: Not to worry. Elizabeth Taylor's no longer in it, so misspellings and grammatical errors are allowed. 35. Jonathan (another one) on J. K. Rowling (2) vs. Joan Didion; Arnold advancesDecember 8, 2022 12:48 PM And I know commitment only has two t's. 36. Jonathan (another one) on J. K. Rowling (2) vs. Joan Didion; Arnold advancesDecember 8, 2022 12:47 PM Inviting JK Rowling would form an excellent test of Columbia Security staff and the university's committment to free speech principles.... 37. Phil on OpenAI's GPT chat bot enters the uncanny valleyDecember 8, 2022 12:44 PM Jessica, Nobody says "that's my story and I'm sticking to it" if the story is true! You've gotta learn your... 38. Dale Lehman on Do doctors get too little respect nowadays? Or too much?December 8, 2022 12:30 PM I think you are committing a logical fallacy. You observe many unfounded differential treatments of groups A and B, and... 39. Anonymous on J. K. Rowling (2) vs. Joan Didion; Arnold advances December 8, 2022 12:16 PM There's no contest here. Joan Didion is one of the best writers of the last century. While J.K. Rowling has... 40. EB on Do doctors get too little respect nowadays? Or too much? December 8, 2022 12:05 PM Interesting. I would disagree with both you and Dr. Covello that I would completely expect that these implicit biases definitely... 41. Jessica Hullman on OpenAI's GPT chat bot enters the uncanny valleyDecember 8, 2022 11:59 AM Wait, so even the comments on this post are wrongly attributing things? As if there isn't enough misinformation about AI... 42. Navigator on Successful randomization and covariate "imbalance" in a survey experiment in NatureDecember 8, 2022 11:51 AM While most of what you listed makes sense, you forgot the main reason vaccination was helpful in select individuals (elderly,... 43. Victor Miller on Do doctors get too little respect nowadays? Or too much?December 8, 2022 11:45 AM When writing to academics I don't know I'll address them as "Professor". If the reply by first name, I'll reciprocate. 44. Dale Lehman on Do doctors get too little respect nowadays? Or too much?December 8, 2022 11:18 AM What I found is "Doctor comes from the Latin word for "teacher" and originally referred to a small group of... 45. EB on Do doctors get too little respect nowadays? Or too much? December 8, 2022 11:18 AM Physicians aren't scientists. At best they use science, but they're not trained at doing science. 46. EB on Do doctors get too little respect nowadays? Or too much? December 8, 2022 11:16 AM There is definitely a lot of unconscious bias and social slights that are commonplace in medicine (as in all fields).... 47. Ney on Do doctors get too little respect nowadays? Or too much? December 8, 2022 10:43 AM It's funny that someone who completes medical studies automatically receives a doctoral degree. Not the least bit of scientific research... 48. oncodoc on Do doctors get too little respect nowadays? Or too much?December 8, 2022 10:33 AM The important person in the doctor-patient relationship is the patient. The important person in the doctor-patient relationship is the patient.... 49. paul alper on Do doctors get too little respect nowadays? Or too much?December 8, 2022 10:21 AM Admittedly, my knowledge is perhaps a few decades out of date. I was a postdoc in the Netherlands for a... 50. Len Covello on Do doctors get too little respect nowadays? Or too much?December 8, 2022 10:17 AM Dr Lehman- Your points are well taken. Totally anecdotal discussion to follow. I live in an area with a lot... Proudly powered by WordPress