  Social inequalities are ubiquitous and evolve towards a universal limit.
Herein, we extensively review the values of inequality measures, namely the
Gini ($g$) index and the Kolkata ($k$) index, two standard measures of
inequality used in the analysis of various social sectors through data
analysis. The Kolkata index, denoted as $k$, indicates the proportion of the
`wealth' owned by $(1-k)$ fraction of the `people'. Our findings suggest that
both the Gini index and the Kolkata index tend to converge to similar values
(around $g=k \approx 0.87$, starting from the point of perfect equality, where
$g=0$ and $k=0.5$) as competition increases in different social institutions,
such as markets, movies, elections, universities, prize winning, battle fields,
sports (Olympics), etc., under conditions of unrestricted competition (no
social welfare or support mechanism). In this review, we present the concept of
a generalized form of Pareto's 80/20 law ($k=0.80$), where the coincidence of
inequality indices is observed. The observation of this coincidence is
consistent with the precursor values of the $g$ and $k$ indices for the
self-organized critical (SOC) state in self-tuned physical systems such as sand
piles. These results provide quantitative support for the view that interacting
socioeconomic systems can be understood within the framework of SOC, which has
been hypothesized for many years. These findings suggest that the SOC model can
be extended to capture the dynamics of complex socioeconomic systems and help
us better understand their behavior.
