Discuss 'deviation from statistical norms' as a definition of abnormality

Firstly, deviation from statistical norms refers to a statistical infrequency (in either direction) from a previously agreed-upon norm. A common deviation from statistical norms can be depicted using IQ scores. For example, an individual with an exceptionally higher IQ would be classified as 'gifted', whereas lower IQ scores can be applied in identifying special educational needs. Defining abnormality through statistical means allows for a quantified measure, reducing the risk of bias. Furthermore, it allows for worldwide generalisation, ensuring a higher test-re-test reliability of a diagnosis, unbound to cultural norms. In this sense, when compared to other definitions, such as 'deviation from social norms', statistical infrequency holds higher applicability and is more likely to remain consistent with time. Nevertheless, it can create stigma and detrimental labels to individuals. Going back to the aforementioned example, labelling an individual with low IQ as 'abnormal' can create stigma, particularly from peers or significant others. Furthermore, over-reliance on abstract measures in defining abnormality can lead to reification - they start being seen as fully accurate descriptions of reality. This can hold potential implications in legal cases, the workplace, even relationships. Although it is important to recognise their objectivity, even psychometric tests are not perfect. For example, IQ tests are revisited every 10 years to maintain an average of 100. In consequence, while it is important to sustain a definition of abnormality with scientific measures, pin-pointing a label to an individual should not be the focus, as it can negatively impact their well-being further, through stigma. Statistical infrequency ought to be seen only as a potential indicator, to avoid over-reliance on abstract concepts.