The Absence of Normality
In behavioral science, normality appears defined as the absence of the characteristic being studied. Behavioral research experiments typically recruit at least two groups of people; one group that has been screened to ensure they show behavioral traits of the abnormality being studied, and another group that does not display these traits – the control group. Any number of tests can then be given to all groups and any differences that appear based upon group identity can be verified statistically and the difference published as a finding.
However, it is worth noting that there are no studies determining normality in mental health, after all, in a field that struggles with resource and funding, what would any research team have to gain by pursuing a credible diagnosis for normality? This means that normality is not scientifically verified and is made all the more impossible to pursue by the ever changing nature of a person’s mental health.
Yet, for such a cherished moniker of considering oneself normal, is it good enough to define it simply by the traits/dysfunctions/disorders that you do not have? It appears to be a travesty of thought to make an observation of somebody displaying difference to you and declaring that you are normal because you are not that. How satisfied would we be in situations where we needed to learn about another person, in knowing simply what they are not?
How do you determine a person’s substance by the absence of traits?
Lennard J. Davis notes in ‘The Disability Studies Reader’ (4th Ed.) that the terms norm and average only entered European languages in the 19th Century. Their arrival coincided with ideas that were being used in the field of statistics. What had been applied in the mathematical determination of astronomical events bled over into the study of human characteristics, such as height and weight. However in this natural accretion, unguided and subject to nineteenth century prejudices, the search for normal behaviors quickly became marred by the assumptions of the privileged.
Statistics is a powerful tool and can be used with great effect to convince scientists of the objectivity of research, but they are only as powerful as their interpretation. Statistics can demonstrate difference like nothing else, but the basis of comparison is loaded with assumptions of deviance versus absence of deviance. When it comes to understanding something as precious as humanity, is that good enough for us? Every single study should have a rigorous definition of what has been considered normal in light of the research question. Normal is needed for statistics to work.
Normality seems to be everything about humanity that we do not consider different or deviant, yet when pressed would struggle to define. This leads one to ask, “Is normality more of a feeling than a state of being?” Normality appears to have a lot in common with the mathematical concept of zero. Both concepts trick us into thinking they are well defined when it is in fact the opposite. The infinity of the absence tricks us into thinking there is substance.
In a world of scientifically and medically confirmed diagnoses, the definition of a normal person is one who would without fail qualify for the control group in any research (unless their socioeconomic markers do not match). Normality is a permanent membership in the control group for every possible behavioral experiment, yet this is clearly impossible, and even inhuman.
In a world where those who have been deemed different are having to fight for more inclusion and equal rights, conversations around normality matter.
If only there was a condition called Manifestly Normal Disorder, a list of symptoms to define normal would have to be rigorously defined in order to screen for the experimental group.
It is worth reminding ourselves that the middle of the bell curve is not where to find normal. Normal is the bell curve.