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10:13am February 6, 2012
mrrscience: The Upside of Dyslexia Wish they would grasp this about more forms of neuro-atypicality. Even things people rarely if ever believe this about often have upsides. And often the reason that research hasn’t noticed it before, isn’t that the data didn’t exist. But rather that there’s a bias towards interpreting positive findings in a negative light when it comes to anything that is (or is considered) generally unpleasant.   So you can get, for instance, research on autism where autistic people get the same scores as nonautistic people in area A and better scores than nonautistic people in area B.  And somehow the researchers will write up the findings as “Autistic people have a deficit in area A” rather than “Autistic people have a strength in area B.”   And most people will never catch the error because they are so biased towards seeing something as absolutely and uniformly a bad thing.  And if the researchers do report a strength accurately, and this gets out to the public, there’s often a backlash from people who seem to think that acknowledging strengths that go with a condition will make people forget that there’s a bad side.  Even if it’s just one teeny little positive study in a sea of overwhelmingly negative ones.  Even if the conclusions finally actually fit the data, instead of being manufactured to make all our strengths into weaknesses.  I’ve heard of similar things happening with depression and schizophrenia as well.  I know very few people (but I do know a couple) who want depression.  I sure as hell hope I never again experience it.  But that doesn’t mean there’s absolutely nothing ever good about it.  There are in fact cognitive strengths that go with depression. And lots of other things that on first glance even to those who have them seem uniformly terrible. (Unlike dyslexia or autism, where there’s always been a sizable number of people with the condition who say that even subjectively we can tell it’s not all bad.) For more on this kind of bias in research, see Morton Gernsbacher’s How To Spot Bias In Research (PDF). The part that sums it all up: So, we have a group of individuals whose more factual descriptions of a meaningless picture were interpreted as insignificant and talkative. We have a group whose more accurate tactile matching was interpreted as sensory prediction deficits. And we have a group whose heightened memory discrimination in one study was interpreted as the result of an as-yet-unknown pathology, and whose equivalent performance in another study was interpreted as  frontal executive impairment.  Confused?  If I told you the group interpreted as providing insignificant and talkative descriptions comprised “normal females,” the group interpreted as unable to predict the sensory consequences of their actions comprised persons diagnosed with schizophrenia, and the group interpreted as having aberrant mental representations and frontal executive impairment comprised persons diagnosed with autism, would it help?  It shouldn’t.  Maggio (1991) recommends that we test our writing for bias by substituting our own group for the group we are discussing. If we feel offended, then our writing is biased. I recommend that we test our interpretations for bias by peeling off the labels, as I’ve done here. If our interpretations make little sense, then our science is biased.

mrrscience:

The Upside of Dyslexia

Wish they would grasp this about more forms of neuro-atypicality. Even things people rarely if ever believe this about often have upsides. And often the reason that research hasn’t noticed it before, isn’t that the data didn’t exist. But rather that there’s a bias towards interpreting positive findings in a negative light when it comes to anything that is (or is considered) generally unpleasant.  

So you can get, for instance, research on autism where autistic people get the same scores as nonautistic people in area A and better scores than nonautistic people in area B.  And somehow the researchers will write up the findings as “Autistic people have a deficit in area A” rather than “Autistic people have a strength in area B.”  

And most people will never catch the error because they are so biased towards seeing something as absolutely and uniformly a bad thing.  And if the researchers do report a strength accurately, and this gets out to the public, there’s often a backlash from people who seem to think that acknowledging strengths that go with a condition will make people forget that there’s a bad side.  Even if it’s just one teeny little positive study in a sea of overwhelmingly negative ones.  Even if the conclusions finally actually fit the data, instead of being manufactured to make all our strengths into weaknesses. 

I’ve heard of similar things happening with depression and schizophrenia as well.  I know very few people (but I do know a couple) who want depression.  I sure as hell hope I never again experience it.  But that doesn’t mean there’s absolutely nothing ever good about it.  There are in fact cognitive strengths that go with depression. And lots of other things that on first glance even to those who have them seem uniformly terrible. (Unlike dyslexia or autism, where there’s always been a sizable number of people with the condition who say that even subjectively we can tell it’s not all bad.)

For more on this kind of bias in research, see Morton Gernsbacher’s How To Spot Bias In Research (PDF). The part that sums it all up:

So, we have a group of individuals whose more factual descriptions of a meaningless picture were interpreted as insignificant and talkative. We have a group whose more accurate tactile matching was interpreted as sensory prediction deficits. And we have a group whose heightened memory discrimination in one study was interpreted as the result of an as-yet-unknown pathology, and whose equivalent performance in another study was interpreted as  frontal executive impairment. 

Confused?  If I told you the group interpreted as providing insignificant and talkative descriptions comprised “normal females,” the group interpreted as unable to predict the sensory consequences of their actions comprised persons diagnosed with schizophrenia, and the group interpreted as having aberrant mental representations and frontal executive impairment comprised persons diagnosed with autism, would it help?  It shouldn’t. 

Maggio (1991) recommends that we test our writing for bias by substituting our own group for the group we are discussing. If we feel offended, then our writing is biased. I recommend that we test our interpretations for bias by peeling off the labels, as I’ve done here. If our interpretations make little sense, then our science is biased.

Notes: