GLM and Neg. Binomial models

Hi userRs!

I am trying to fit some GLM-poisson and neg.binomial. The neg. Binomial
model is to account for over-dispersion.

When I fit the poisson model i get:
(Dispersion parameter for poisson family taken to be 1)

However, if I estimate the dispersion coefficient by means of: 
sum(residuals(fit,type="pearson")^2)/fit$df.res
I obtained 2.4. This is theory means over-dispersion since 2.4>>1. 

I do not understand what the relation is between (Dispersion parameter for
poisson family taken to be 1) and 2.4.

In a similar fashion, when i fit the neg. binomial model I obtain:
(Dispersion parameter for Negative Binomial(0.1717) family taken to be 1)
Whereas the estimation of the dispersion coefficient as stated above is: 1.4

Why Dispersion parameter and my calculation are not the same?


Any thoughts will be much appreciate it .


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