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— zev handel (@ZevHandel) December 17, 2020
The following sentences are in seven different languages, all written in Chinese-character script (or a modification of it). Can you identify the languages?
Sentences are in thread.
(1/3)
Here again are those seven sentences:
1) 他的剑从船上掉到河里去
2) 於世𡗉番𧡊哭唭𢆥尼歲㐌外四𨑮
3) 入良沙寢矣見昆腳烏伊四是良羅
4) 佢而家喺邊喥呀
5) 夜久毛多都伊豆毛夜幣賀岐都麻碁微爾夜幣賀岐都久流曾能夜幣賀岐袁
6) 其劍自舟中墜於水
7) 今天愛晚特語兔吃二魚佛午飯
Six of those seven sentences are historically attested. One is not: I invented #7. I’m going to dive into an exploration of that seventh sentence in today’s thread.
Sentence #7 is an English-language sentence written sinographically — that is, using graphs that originate in the Chinese script. I didn’t do this for fun (even though it is fun), or as a proposal for a new way to write
7) \u4eca\u5929\u611b\u665a\u7279\u8a9e\u5154\u5403\u4e8c\u9b5a\u4f5b\u5348\u98ef \u2013 Modern English
— zev handel (@ZevHandel) December 21, 2020
Today I want you to each two fish for lunch.
That this sentence is a written form of English is undeniable, as the sentence is made up entirely of English words following the rules of English grammar. 23/
I did it as a thought experiment. Why? Because thinking about how the modern Chinese script might be adapted to write modern English can give us valuable insights into historical instances of script borrowing, like those that took place centuries ago in Japan, Korea, and Vietnam.
The latest REACT1 report shows prevalence of infection in ALL age groups has fallen, including children aged 5-12 from 1.59% in Round 8 to 0.86% in Round 9a. The authors of REACT1 report also (wisely) didn't try to interpret the prevalence figures.
If this were a research trial you wouldn't place much weight on the age differences in % prevalence because of the wide confidence intervals, i.e. differences weren't statistically significant.
3/
I've previously tweeted on the challenges (& dangers) of interpreting surveillance data. One would need lots more contextual info to make sense of it & arrive at sound
Misinterpretation of surveillance data is a serious issue. Surveillance data needs to come with a warning label - Open to biases - interpret with caution! Some may not realize that surveillance often does not measure all infection, it's a proxy for actual disease incidence.
— Andrew Lee (@andrewleedr) February 14, 2021
1/
Undoubtedly some will extrapolate from the prevalence of infection figures in children to other settings i.e. schools based on the headline. I'd advise caution as there is a real risk of over-interpretation through extrapolation of limited data. Association is not causation.
5/
If I did thred on finding/acquiring decent raw land would that be something pepo are interested in
— Ovcharka (@ouroboros_outis) January 18, 2021
I think I know a bunch of weird tips/tricks for selection at this point that it might help u guys, lemme know
This is NOT going to be zillow "here is how to google school districts and find walmart" we are not concerned with this malarkey, we are homeschooling and planting victory gardens and having gigantic happy families.
With that said, for my frog and frog-adjacent bros and sisters:
CHOICE SITES:
Zillow is obvious one, but there are many good sites like Billy Land, Classic Country Land, Landwatch, etc. and many of these specialize in owner financing (more on that later.) Do NOT treat these as authoritative sources - trust plat maps and parcel viewers.
TARGET IDENTIFICATION AND EVALUATION:
Okay, everyone knows how to google "raw land in x state" but there are other resources out there, including state Departments of Natural Resources, foreclosure auctions, etc. Finding the land you like is the easy part. Let's do a case study.
I'm going to target using an "off-grid but not" algorithm. This is a good piece in my book - middle of nowhere but still trekkable to civilization.
Note: visible power, power/fiber pedestal, utility corridor, nearby commercial enterprise(s), and utility pole shadows visible.