Clarissa's Blog

5 responses to “Pseudo-science”

1. 

   matt

   December 26, 2016

   yep. that and their are other biases too. I am not a statistician so I am probably slightly botching this, but the high level theme is true.

   Studies usually try to have a p value of <0.05, which if properly designed means there is a chance of less than 5% that the result is “random” vs being meaningful. So in general, if 20 such studies are done you will see this result. With there being 10’s of thousands of randoms studies done each year hundreds (if not thousands) will be published with “novel” results. The most novel ones will get press coverage. You can see how this will go.

   Also, as researchers need to “publish or perish”, they have a bias, explicit and implicit to search for these “unique” findings vs reafirmming more important, yet already discussed ideas.

   Lastly, with all the data mining activity and capabilities which currently exist “p hacking” is a thing where the data can be made to scream to create some unique or insightful finding.

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2. 

   Alex

   December 27, 2016

   I suspect that these researchers would have preferred to find bias running the other way. This data contradicts certain narratives, which makes it a harder sell.

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   1. 

      Clarissa

      December 27, 2016

      It’s harder to sell in some places and easier in others. These kind of “researchers” always find exactly what they want.

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      1. 

         Alex

         December 27, 2016

         I’m pretty sure that they would have been more comfortable finding anti-woman bias. Here’s the original article: http://www.tandfonline.com/doi/full/10.1080/08989621.2016.1268922

         Look at Figure 4. It clearly shows that male and female scientists both rated female scientists better than males, though the pro-female difference was smaller among male scientists than female scientists. You cannot read these results as supporting any narrative of anti-female bias, and the authors first seem to acknowledge as much. But then they follow it with:
         “we cannot rule out that in-group bias led male scientists to rate female scientists lower on the scientific traits than women themselves did.”

         It is true that men rated women lower than women did. But men also rated men lower than women did, and they still rated women at least slightly better than they rated men.

         Granted, they qualify it with “We cannot rule out…” but there are lots of things that they cannot rule out. They commented on this one because it’s what they’re expected to find and rather than comparing and contrasting with other studies that find similar things (e.g. Ceci and Williams) they put heavy disclaimers in to leave some room for results that run counter to theirs.

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3. 

   Tal Hartsfeld

   December 27, 2016

   “The only interesting data we can get from them is what the biases of the people conducting the study are”.

   Isn’t that true of ANY kind of research …be it forensics, climate change, psychology, politics, financial, popular trends, and so forth?

   People can be so partisan and demographic, so of course their viewpoints stand to be a bit myopic and dogmatic.

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