I watched this happen recently in real time. This article interpreted a Flurry study wrong and was featured on Tech Meme (its headline has since been softened): https://www.macrumors.com/2021/05/07/most-iphone-users-app-t... – "Analytics Suggest 96% of Users Leave App Tracking Disabled in iOS 14.5"
But none of those articles are interested in correction and the initial visceral reaction and herumphing tweets have all since occurred. Hundreds of thousands of people got the wrong idea.
What it shows it that there is very little original reporting, people don't ask study authors for clarification, and misinterpreting of data happens all too often.
> Using date range commands, the author claimed to compare searches for five months in 2019 to the same five months in 2020 — pre-pandemic to mid-pandemic. They did so not by turning to Google Trends data — the method promoted by the scholars they cited — but by inputting their search phrases with date delimiters using Google search.
> They reported the number of hits Google displays at the top of the page as the number of searches made for that search string.
>These numbers were exceptionally high because, well, the search phrases were not enclosed in quotation marks. All this in an article arguing for the value of tech-enabled “rapid response” research. A culture of “move fast and break things” is common in Silicon Valley, but academics typically work a bit more slowly and carefully to avoid these kinds of errors.
The number of hits reported by web-scale engines like Google and Bing are fabrications. When I was the CTO of a full-web search engine startup, I'd get an API access request every couple of months by someone wanting to use hit counts for an academic purpose. I would always them no and why; often they wanted to argue with me.
Even then, if it had been executed flawlessly, you can only expect that search term frequency and violence remain correlated ceteris paribus, i.e., when all else is the same. The two time periods are clearly different, so how the hell did it even get published?
Regardless of the subject matter, I think it’s good policy to do what arXiv does with retractions: they become a new, empty version, alongside a corresponding explanation, but all previous versions remain on the record.
>How did this article get through peer review? Like the author, the journal’s reviewers and editors seemed to have been glamoured by the shine, tech fetishism, and naive empiricism of even the most poorly executed digital methods — without the methodological humility to work together with colleagues from information science, or at least check in with someone familiar with the basic workings of tools like Google
Well, that's what happens when your institution is brimming with ideologues who practice one sided research and immediately praise any results that confirms their political, dogmatic biases. Doubly so when criticizing certain results or topics will get you implicitly or ex-communicated, particularly if you are not part of an approved protected class.
The retraction doesn't matter very much, the damage has already been done, and far more eyes will have been exposed to the results than to the retraction.
The "we need males to continue the species"-argument isn't a very good one to keep men around. Very few men can impregnate an enormous amount of women. You might want keep around a good selection in your breeding zoo, for genetic variance. However, you won't need >50% as nature dictates.
[+] [-] ec109685|4 years ago|reply
Then the game of telephone began as bloggers simply rewrote the article and added their own spin: https://www.techmeme.com/210507/p14#a210507p14
- Ars: 96% of US users opt out of app tracking in iOS 14.5, analytics find
- iMore: 96% of iPhone users have opted out of app tracking since iOS 14.5 launched
- Wccftech: Analytics Reveal 96 Percent of Users Have Disabled iOS 14.5's App Tracking on Their iPhone
- Ubergizmo: 96% Of iOS Users Have Opted Out Of App Tracking
- …
Flurry since updated their study to make it clear what it was measuring and found opt out in rate to be about 24% for prompted users (not the 4% cited): https://www.flurry.com/blog/ios-14-5-opt-in-rate-att-restric...
But none of those articles are interested in correction and the initial visceral reaction and herumphing tweets have all since occurred. Hundreds of thousands of people got the wrong idea.
What it shows it that there is very little original reporting, people don't ask study authors for clarification, and misinterpreting of data happens all too often.
[+] [-] Cenk|4 years ago|reply
> They reported the number of hits Google displays at the top of the page as the number of searches made for that search string.
>These numbers were exceptionally high because, well, the search phrases were not enclosed in quotation marks. All this in an article arguing for the value of tech-enabled “rapid response” research. A culture of “move fast and break things” is common in Silicon Valley, but academics typically work a bit more slowly and carefully to avoid these kinds of errors.
[+] [-] wumpus|4 years ago|reply
http://searchengineland.com/why-google-cant-count-results-pr... http://homepage.ntlworld.com/jonathan.deboynepollard/FGA/goo...
[+] [-] tgv|4 years ago|reply
[+] [-] croes|4 years ago|reply
[+] [-] ezequiel-garzon|4 years ago|reply
[+] [-] croes|4 years ago|reply
[+] [-] alecco|4 years ago|reply
[+] [-] tryonenow|4 years ago|reply
Well, that's what happens when your institution is brimming with ideologues who practice one sided research and immediately praise any results that confirms their political, dogmatic biases. Doubly so when criticizing certain results or topics will get you implicitly or ex-communicated, particularly if you are not part of an approved protected class.
The retraction doesn't matter very much, the damage has already been done, and far more eyes will have been exposed to the results than to the retraction.
[+] [-] doggodaddo78|4 years ago|reply
[deleted]
[+] [-] incrudible|4 years ago|reply