Scheduled Tribes and the Politics of Inclusion in India

As the identification of Scheduled Tribes (STs) is left to the state government – which bases decisions on political considerations rather than the established criteria for identification of STs – there are bound to be emerging demands for inclusion in the list of STs. Meanwhile, in the name of extending welfare projects and affirmative action to tribal people, the state is legitimizing its control over tribal resources. For STs, the important issue is not integration into mainstream society, nor development by any outside agency, but recognition as peoples in their own right, treatment as equal partners, and control over their lands and livelihoods and, through this, the ability to develop themselves.     

Measuring diversity in biological populations with logarithmic abundance distributions

Fisher's logarithmic distribution for species abundance is derived under a suitable set of conditions. The derivation explains the explicit meaning of the two parameters of the distribution.     

A characterization of invariant power-series abundance distributions

Consider a population the individuals in which can be classified into groups. Let y, the number of individuals in a group, be distributed according to a probability function f(y;ø_o) where the functional form f is known. The random variable y cannot be observed directly, and hence a random sample of groups cannot be obtained. Consider a random sample of N individuals from the population. Suppose the N individuals are distributed into S groups with x₁, x₂, …, x_S representatives respectively. The random variable x, the number of individuals in a group in the sample, will be a fraction of its population counterpart y, and the distributions of x and y need not have the same functional form. If the two random variables x and y have the same functional form for their distributions, then the particular common distribution is called an invariant abundance distribution. The paper provides a characterization of invariant abundance distributions in the class of power-series distributions.     

Selecting a power-series distribution for goodness of fit

The binomial, Poisson, logarithmic, negative binomial, and extended negative binomial distributions are characterized in the class of power-series distributions (1) through a differential equation based on the ratio of two successive derivatives of the series function, (2) through the ratio of two probabilities associated with two successive values in the range of the random variable, and (3) through the ratio of two consecutive factorial moments. The ratios referred to in (2) and (3) above can be utilized to discriminate between the five power-series distributions mentioned at the beginning.