[R] adjusted R^2 vs. ordinary R^2

[James Salsman]

I thought the point of adjusting the R^2 for degrees of
freedom is to allow comparisons about goodness of fit between
similar models with different numbers of data points.  Someone
has suggested to me off-list that this might not be the case.

Is an ADJUSTED R^2 for a four-parameter, five-point model
reliably comparable to the adjusted R^2 of a four-parameter,
100-point model?  If such values can't be reliably compared
with one another, then what is the reasoning behind adjusting
R^2 for degrees of freedom?

What are the good published authorities on this topic?

Sincerely,
James Salsman