Certainly, detection has influenced these trends and there are many unknowns from the age before Photoshop, but... I still sense a growing antiscience culture within science.
I'm interested to know how crooked scientists come to be. Do they enter a research career with the proper motivation, only to be steered awry by external pressures (e.g., publish or perish)? Or do they simply have the wrong idea from the get-go (e.g., PhD as status symbol, research as entertainment)?
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If even high-quality data is supposed to be replicated -- i.e., treated as untrustworthy -- before being built upon, the least we can do is treat* unverifiable data as falsified data. That would hopefully clear up the lot of papers with vague methods and hidden datasets, and force the fraudsters to work a lot harder.
Certainly, detection has influenced these trends and there are many unknowns from the age before Photoshop, but... I still sense a growing antiscience culture within science.
I'm interested to know how crooked scientists come to be. Do they enter a research career with the proper motivation, only to be steered awry by external pressures (e.g., publish or perish)? Or do they simply have the wrong idea from the get-go (e.g., PhD as status symbol, research as entertainment)?
--
If even high-quality data is supposed to be replicated -- i.e., treated as untrustworthy -- before being built upon, the least we can do is treat* unverifiable data as falsified data. That would hopefully clear up the lot of papers with vague methods and hidden datasets, and force the fraudsters to work a lot harder.
*Treat, not categorize. Important difference.
The system needs a system to systematically monitor the system.
Or just a new system.