I'm happy you believe that the community can converge on unified standards - I wish I shared the optimism - but that's not where we're currently at and years-long efforts don't help me now. (For example, I'd love to use PEP 695 generics since I found a use case for them around 18 months ago but I can't until I can get away with not supporting 3.11, which is years out.) Maybe everything is perfect in 2028 or so - I'd be thrilled - but that doesn't help the pitch for annotations being a value add for people who are worried about the current jobs.

I'm surprised you already know it's not as bad as I think - have you been able to use it? Working on a team that mixes mypy and pyright is pretty frustrating since they don't agree on everything (i.e. when one changeset passes on one and fails on the other) and I see no reason to believe the inconsistencies will become more rare when the number of opinions goes from two to three

- why not just contribute to the community tool?

- there's already a major split in Python type-checking tools, if there's a third that doesn't agree with either of them it'll be a mess for projects to deal with

- astral has been hiring like mad recently and has yet to communicate that they can actually make money ($5 million doesn't last forever)

- does it actually exist? is this currently a closed-source codebase, or is "we're building" future tense?

Possibly in some medical or social science fields, I don't know. I know there is not such an issue in chemistry and materials science. There also may be some complications for collaborations with industry, but that's kinda a different situation. For people whose career development is not strongly tied to reproducibility of their work (a.k.a. everybody) it's just another step in the overly complex process of publishing in for-profit journals. Funding agencies generally aren't going to punish people for using this excuse and the watchdogs/groups concerned with reproducibility have no teeth.

Not an excuse, but journals don't make it easy to share files, as hard as that is to believe. Some will only take PDFs for supplemental information and many have garbage UIs, stupidly small file size limits, etc. Just uploading to a repo (or tagged release) on GitHub is common these days because there is much less friction.

Not generally, though the tide is slowly turning in the right direction. Unfortunately many laws/policies pushing for openness and transparency in research are sidestepped with the classic "data available upon request," a.k.a. "I promise I'll share the Excel files if you email me" (they will not).

What is disrespectful is not bothering to read what people have to say before dismissing them as liars who are too vested in "the current research direction" and/or money for their perspectives to matter. It only takes reading a few comments to see that's not happening - for starters, people were skeptical of this group's work for a while now.

This was (mostly) true back then, but it is definitely not true today. People tempted to commit fraud now have to be worried about people like Elisabeth Bik exposing them and ruining their careers. In my experience, the type of people known lie in papers overlap strongly with those that are career-minded/money-driven. So having a few journalists with the skills to detect fraud is an obvious win. Some of the frauds will just get better at, that's just how it does, but it's not like there are no imaging experts in the field.