Rick,
If I used the third method(FISHER option of PROC CORR) to calcualted RSquare and its CI,
I could get the more similiar result with Olkin-Finn rather than Bootstrap ,regardless of it is a big or small sample.

%let N = 500; /* sample size */
data BWeight;
set sashelp.bweight(obs=&N);
keep Weight Black Married Boy MomSmoke CigsPerDay MomAge MomWtGain;
run;

proc glm data=BWeight noprint;
model Weight = Black Married Boy MomSmoke CigsPerDay
MomAge MomAge*MomAge MomWtGain ;
output out=Fit1 p=pred;
quit;

ods select none;
ods output FisherPearsonCorr=FisherPearsonCorr(keep=Corr Lcl Ucl);
proc corr data=Fit1 fisher(biasadj=no);
var Weight pred;
run;
ods select all;
data FisherPearsonCorr;
set FisherPearsonCorr;
RSquare=corr**2;
RSquare_lcl=lcl**2;
RSquare_ucl=ucl**2;
run;
proc print;run;

RESULT:
Corr Lcl Ucl RSquare RSquare_lcl RSquare_ucl
0.31035 0.228891 0.387497 0.096319 0.052391 0.15015