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Oops I didn't relaize claude share doesn't share inline citations. But the ones in the inline citations definitely did not support the statement
The link you shared is about May 2025 which is not related to the result for June 2025 my claude chat is about. That article says that offenses for YE (year ending in?) May 2025 increased 20% y/y, which is a record. But Claude said that offenses for YE June 2025 increased 13% y/y (correct, and also less than 20) and said that it was a record (which wrong).
Anyways it's undeniable that your favorite model still slopped out a multitude of errors on literally the first query ai I tried on it.
That's on me, too; I should have checked the links in your quotes, not just looked at the Claude transcript and assumed it included everything in the quotes.
One of the two links I shared was an April story, the other a July story; both were data through March 2025.
Personally I'd have used the phrase "near-record levels" (after rising 30+% above trend, it dropped back 0.13% - yay?), but I'm not sure that'd be any more informative a summary - "near-" could be applied just as well to a record set 13 years earlier, while "representing" is a closer fit for 3 months earlier. "Reached record levels" or "was a record" wouldn't be supported by Claude's inline link, but both of those were your rewording, not Claude's.
You seem to have confused me with @RandomRanger. Claude is my second-favorite model, because while I've repeatedly caught it in errors, it at least always tries to fix them when I correct it; ChatGPT-5-Thinking is the only thing I've seen that's (so far, for me; others have had worse luck) been good about avoiding errors preemptively, and IIRC all the non-Claude free models I've tried have made significant errors and often tried to gaslight me about them afterward.
I'm not entirely on board with Claude claiming that 99.8% of a recent record is "representing" that record, but it's clearly all too easy to slop out errors. Would that either of us were under 0.2% off!
Looking at your other complaints, they're mostly either not errors or not clearly errors, which amusingly means that appellation is itself in error each of those times:
When Claude refers to "Operation Pegasus", that's a term even the BBC has used, referring to the same thing as "Project Pegasus", though it's not used in the story at that particular inline link, which is about details other than terminology variants. (it is in one of the other links Claude found) When Claude is correct about something that seems too simple to justify, but it turns out that "too simple" is in the eye of the beholder, that's still not an error.
The difference between "Wrong" and "There's no citation" also applies to the Crime and Policing Bill - is it wrong? Then what is the primary response to the problem? Four out of the five quoted sources in the linked article mention the Crime and Policing Bill by name, which seems to be a solid first place showing; why would we not want AI to use Grice's Maxims here?
When you say "The source does not indicate that any mapping of what's happening was done at the summit.", you're misparaphrasing Claude's summary, which says "coordinate efforts on mapping", and is actually a pretty good abridgement of "see what more we can do together to map what's happening" from the source article.
Your claim of "outdated" is like something out of a South Park joke. 2023! The Before Times! The Long Long Ago! It's good to see an October 23 2025 article in the mix too, but I want citations that provide a little context; "born yesterday" is supposed to be an insult! Perhaps at some age "outdated" becomes "unsupported", but that's still not "erroneous" - is the data actually out of date? Which of those policies has since ended?
Ironically, the one thing I've seen change most since 2023 is AI itself. In 2023 I was giving AIs benchmark questions that could be answered by most first-year grad students in my field, watching them instead make sign errors that could have been caught by anyone who's passed Calc 3, and then watching the various models either flail about at failures to fix the problem or gaslight me about there not being a problem to fix. In 2025 I can still catch the free models in math errors, but the one time I've "caught" a top model it turned out to be because I had an embarrassing typo in my own notes. Actual top-of-their-field geniuses are still catching top models in math errors ... but using them to prove theorems anyway, with reports to the effect that it's faster to try new ideas out with the models and correct the errors than it is to try every idea out manually.
I do like talking to Claude, at least for anything where I can double-check its work, both because it's capable of avoiding rude language like "slop" and "dogshit" and "shitty", and because when I do find errors upon double-checking, it acknowledges and tries to fix them. You've been pretty good about the latter so far, at least; thank you!
To go on a tangent, I find it sociologically interesting that one big group of people likes talking to AI partly because it’s always polite, kind and inoffensive, while another hates dealing with it for precisely the same reason.
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Oops sorry.
Heck if I know, but there's not guarantee that the most publicized approach is the primary approach. It could just as well be that it gives the best soundbites and the bill is actually dead.
The linked pages specifically say that they were initiatives under a previous administration, so I think there is definitely a burden of proof in asking if they are still applicable.
And when it comes to crime and countermeasures 2 years is certainly an eternity.
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