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The justice fallacy is a cognitive distortion when a person begins to apply the laws and rules of a particular society to his life situations, giving them an objective meaning. However, justice is subjective and differs significantly in each case from different points of view. Belief in a just world is an extension of this delusion, which can both create a false sense of security if a person does nothing wrong, and in the case of discrimination and bullying, create a feeling that a person is getting what he deserves (Shickel et al., 2020). In both cases, the so-called fairness error is triggered.
I chose this cognitive bias because I think it is pretty standard and needs special attention. This position is often deeply embedded in people, and they may consider it the only accurate view of the world and the opportunity to get used to the rules. The diametrically opposite delusion about an unjust world also has negative consequences, only of a different nature. In general, a person becomes more indulgent to himself, less responsible, and often seeks to explain what is happening to the environment. In many cases, this problem is not identified by people and even by those around them, which only reinforces this misconception, leaving a negative effect.
I suggest the client talk about the categories that often show this error. The most straightforward test is the degree of agreement with phrases such as “I feel like life rewards and punishes me as I deserve” or “I feel like people treat me with the respect I deserve.” Merits, dignity, awards, and the right to something allow identifying a mistake if most of them are tried on for any favorable events in a person’s vocabulary. Similarly, with bad luck – they tend to shift the blame for an unfortunate combination of circumstances beyond the control of people. Therefore, I will try to evoke agreement or disagreement with the client with such phrases, which will show the degree of faith in a just world.
Reference
Shickel, B., Siegel, S., Heesacker, M., Benton, S., & Rashidi, P. (2020, October). Automatic detection and classification of cognitive distortions in mental health text. In 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE) (pp. 275-280). IEEE.
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