It's a question of ideology

1. There is a link between a rise in pandemic events and global warming. "Proving" it was a lab accident can be used as an argument that global warming had nothing to do with it (and of course, doesn't exist at all)

2. Blame: blaming a specific country could mean one could try to hold them liable for damages or at least set them in a bad diplomatic position. Plus when it's "man-made", it's easy to associate it with disliked people, like Fauci in the US pretending it was their personal fault. Holding individuals or institutions accountable/blaming them can also be a way to cope with loss.

3. Shifting the narrative: after millions had died, the narrative that COVID wasn't dangerous couldn't be used any longer. By claiming OT was lab-grown, there was a new story, a new scandal that would overshadow the fact that a lot of politicians, including the POTUS did not act and people can pretend they either never underestimated it or they did so because "a natural virus wouldn't be that bad". These narratives don't necessarily have to be for the public but for some just for their own conscience.

4. Theodicée: might be a bit abstract, but especially conservative americans are in the majority protestantic Christians believing in providence, i.e. that god makes all things natural come to pass. Meaning that a global pandemic would be gods will, meaning that the millions of americans who died would have been according to gods plan, maybe even as a punishment Not unlike the Great Plague in Europe was seen. A lab-grown virus produced by non-christians would be something god had no hand in, and it being "man made", would be a way out of the cognitive dissonance of god being good yet allowing bad things to happen to his devout followers.

Tl, dr: mostly it matters to blame others or explain how it could happen, also, of course as a political talking point.

The high was a response to culling (as well as a rising high in the past 5 years due to US market trends due to things like cage bans and a growing organic market share -- small next to the culling response, but the market hadn't totally responded yet). The historic high was speculative.

How can you tell? Compare the growth in the wholesale price of chickens to that of eggs. Both eggs and chickens had no response when avian flu was first reported in Jan 2022, then rapidly rose with the first culls in March, which continued until another flurry of news stories about culls in Oct-Nov (a Google search is best to see the general distribution of news story dates in 2022, but I don't think I can link my own results now). But chicken prices didn't respond then, because culls had been continuous, while eggs did, which I suspect was market speculation -- that's confirmed because egg prices crashed in January 2023 (back to where they are "supposed to be"), while chicken prices are steady. That's finance QED afaik.

[Edit: My opinion on this is significantly less confident -- see continued comments below.]

Hey, that's a great note. We just updated the above post to include a link to the data source. Apologies! Let us know if that works.

Do you have any hollandaise? (a source)

Not contesting, as it's easy to believe that the mix of 'soft-flation' & actual restriction of production led to outrageous price gouging for consumers, but I haven't read or heard about egg distributors raking in profits above & beyond usual.

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If I understand it correctly, the "average" line gives the average for this day of the year, so it moves up and down periodically. But I'm not sure and it's not explained, what the "historical average" actually is, especially how long that "history" is...

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This data is fundamentally flawed. It's literally provably false, right now, just by looking at the data directly.

JUST the top 10 NFTs, trading only on Opensea, pushed 21,549 ETH in volume just in the last 24 hours alone.

That's $32,323,500 traded over 24 hours calculating at $1500/ETH.

According to the chart, total USD sales were only 13 million.

So basically this is wrong.

Edit: I’m sorry my facts are disrupting your narrative and upsetting your fragile reality. Thanks for the downvotes though.

When you list a source, whether in your graph or in the post here (I'd say especially in the post, but it should be in the graph too), a user must be able to verify the data. I cannot find the source data, and I followed the link to the CPI site.

Furthermore, the source is definitely not the site on which you originally post the graph -- for one thing, that is not "OC". If it's from a newsletter, that's your secondary citation, whereas you still have to make the primary citation to the original data so that, again, we can verify the numbers, who calculated them, their methodology (definitions, date range, their own data sources, etc.), among other things.

What’s that spike? Context would probably be a cool addition to this chart.

Lake mead is a huge source of water for Los Angeles. Water resources are regional so California reservoir levels are only meaningful if you include where the water that California uses comes from.

Rotten Tomatoes isn't actually automated like that. Critics mark their reviews as positive or negative.

So in both of your examples, 9/10 people said "Yeah, I liked this" so you have a 9/10 chance of liking it.

Systemic risk vs dumbass risk.

Hard to be wrong on something I never gave a stance on other than let’s wait and see but ok keep jumping to conclusions

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Auctioning this chart as an NFT. Make yiour offers as a reply to this post. 😁

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Noice! Any idea what happened in 2016?

Ohh, each occurence.. gotcha. Missed that, I though it was just the number of individual words and I was hella confused

Data source: United States Cancer Statistics 2019

Source code and raw data tables available here: https://cancerdb.com/posts/cancer-heatmaps.html

Tools used: Node.js, Scroll, MagicSquares, CancerDB, Truebase

Now that FDA said eggs are healthy, the price might jump even more.

Nice, I‘ll check it out

Interesting stats, but a z-score doesn't really work for time series. It hides the most important part (time-based trends) and can be confusing, which you can see in the comments. Z-scores are designed for looking at the relationship between a number drawn from a sample of similar things. Think "My height vs average height of all people."

There are systematic changes that accrue over time that make, say, 2000 more like 2001 than like 2018. That's what you want to show. A bar chart would have been really interesting here, since the number of terrorist attacks swung wildly from 1,000 to 17,000.

It’s categorically worse. Instead of doing both, it’a poorly attempting and failing to do one.

For RT critics there is no difference between 9 critics scoring 100 and 1 scoring 49, and 9 critics scoring 51 with 1 scoring 49.

You are not equally likely to enjoy both of these films.