Posted on 01/29/2021 8:05:17 AM PST by BenLurkin
Tiokhin’s team is not the first to make the argument that competition poses risks to science...But the model is the first to use details that explore precisely how those risks play out, he says.
...Tiokhin and his colleagues built a toy world of 120 scientist “bots” competing for rewards. Each scientist in the simulation toiled away, collecting data on a series of research questions. The bots were programmed with different strategies: Some were more likely than others to collect large, meaningful data sets. And some tended to abandon a research question if someone else published on it first, whereas others held on stubbornly. As the bots made discoveries and published, they accrued rewards—and those with the most rewards passed on their methods more often to the next generation of researchers.
... When they gave the bots bigger rewards for publishing first, the populations tended to rush their research and collect less data. That led to research filled with shaky results... When the difference in reward wasn’t so high, the scientists veered toward larger sample sizes and a slower publishing pace.
...
Rewarding scientists for publishing negative findings—an oft-discussed reform—lowered research quality, as the bots figured out that they could run studies with small sample sizes, find nothing of interest, and still get rewarded. Advocates of publishing negative findings often highlight the danger of publishing only positive results, which drives publication bias and hides the negative results that help build a full picture of reality. But Tiokhin says the modeling suggests rewarding researchers for publishing negative results, without focusing on research quality, will incentivize scientists to “run the crappiest studies that they can.”
Actually it’s funding streams and political influence that causes scientists (at least in this country) to be corrupt. Implying it’s just sloppiness misses 90% of the problem.
It gives us nothing more than what people already knew.
Note, however, the credence given to the simulation. If only the statistical analysis which demonstrates that the 2020 election was stolen were as readily received.
Simply used as a propaganda tool.
Sadly, this publication has become one of the prime examples of “shoddy” during the past decade...
From the link:
The reproducibility difficulties are not about fraud, according to Dame Ottoline Leyser, director of the Sainsbury Laboratory at the University of Cambridge.
That would be relatively easy to stamp out. Instead, she says: "It's about a culture that promotes impact over substance, flashy findings over the dull, confirmatory work that most of science is about."
She says it's about the funding bodies that want to secure the biggest bang for their bucks, the peer review journals that vie to publish the most exciting breakthroughs, the institutes and universities that measure success in grants won and papers published and the ambition of the researchers themselves.
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