Charles Coverdale (@CFCoverdale) header
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lukewarm takes on economics and climate science

London, UK
Joined January 2011
Photo by Charles Coverdale (@CFCoverdale)Photo by Charles Coverdale (@CFCoverdale)Photo by Charles Coverdale (@CFCoverdale)Photo by Charles Coverdale (@CFCoverdale)Photo by Charles Coverdale (@CFCoverdale)Photo by Charles Coverdale (@CFCoverdale)Photo by Charles Coverdale (@CFCoverdale)Photo by Charles Coverdale (@CFCoverdale)Photo by Charles Coverdale (@CFCoverdale)Photo by Charles Coverdale (@CFCoverdale)
Charles Coverdale retweeted
london is a city that dares to ask the question: what if there was a world-class capital with bad weather, high cost of living, mediocre food and miserable people? nevertheless, it persists
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Charles Coverdale retweeted
We're about to enter a period where not reading or writing becomes as ubiquitous as smoking once was. We can hope people will eventually realize this is bad for them, as they did with smoking. But this is far from certain; the cost may not be as obvious.
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Charles Coverdale retweeted
You’re deluding yourself if you think AI advances like in math aren’t coming to economics and other social sciences
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Charles Coverdale retweeted
My whole TL today.
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Charles Coverdale retweeted
Encouraging frontier labs to train on my research notes, just to set them back a few years. Doing what I can for AI safety
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Few people know this but in the Cobb Douglas production, the productivity term A stands for Acemoglu.
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Charles Coverdale retweeted
Everyone wants to run a hedge fund, but it appears nobody wants to actually do any hedging
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Charles Coverdale retweeted
I do find it extraordinary that current events in AI don’t make the top ~30 stories on the BBC News homepage
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Dear @JDVance - the company workday has access to incredibly advanced systems and should be restricted to us citizens only
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Charles Coverdale retweeted
on AI and water use. You could ask a frontier model 4 questions per day every day for a year. Or you could eat a single solitary almond.
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Saints teaching us that with enough observations the sample mean converges to the population mean @stkildafc
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I used to dread trying to get my R packages on CRAN. Waiting over a week for an email saying I'd tripped over a rule I'd never heard of. Most of the time I just wouldn't bother at all. But this year, I've shipped 17 packages. Here's the skill that finally fixed it 🧵
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It runs policy scans, hits every external URL with a live request, runs R CMD check --as-cran, and cross-checks every function against the rejection playbook before you submit
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Every gotcha in the playbook is one that sent a previous package to the newbies queue. MIT. Works for compute, API, and data archetype packages github.com/charlescoverdale/… #rstats
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So I built buildRpackage: a Claude Code skill with 7 phases. ideate → name → plan → build → check → submit → resubmit Plus a 12-category code audit and an optional academic methods audit
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Hadley's R Packages teaches you to build a working package. It does not teach the CRAN policy layer that sends first submissions back to the newbies queue for 2 to 10 days
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Common landmines: • \dontrun vs \donttest • globalenv() prohibition • URL 404s in DESCRIPTION • Mozilla UA for EU servers • cache write rules • cross-platform path traps Each is one line in CRAN policy. Each can bounce your submission
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