R help - Oct 2013 - Using calibrate for raking (survey package)

I'm studying the calibration function in the survey package in preparation
for raking some survey data. Results from the rake function below agree
with other sources. When I run calibrate, I get a warning message and the M
and F weights seem to be reversed. Even allowing for that, the deviation
between calibrated and raked weights is much more than I expected. I see
that in the calibrate function "population" is supposed to be a vector
or
table, but can't figure out how to adjust. Can you clarify? Thanks.

-M. Laviolette

satisfy <- c(2,5,2,3,4,3,3,3,4,2,2,3,2,3,4,3,3,2,3,3,4,3,3,3,2,
             3,3,3,2,1,4,4,3,3,2,3,4,2,3,3,3,5,3,1,4,3,3,4,4,2,
             3,3,3,5,4,4,5,3,4,4,5,3,3,4,3,3,3,3,2,4,4,3,3,4,3,
             2,4,4,3,4,4,4,5,3,3,4,4,4,3,2,2,4,3,4,3,4,4,3,3,3,
             3,4,4,4,4,3,3,3,3,2,3,3,2,2,5,4,5,2,4,4,4,3,4,4,2,
             4,4,3,4,3,4,2,3,3,2,4,3,4,4,3,5,2,4,4,3,4,5,3,3,3,
             3,2,3,4,4,4,2,4,4,2,3,5,2,2,3,3,3,3,3,4,4,3,3,4,4,
             4,4,4,4,4,4,3,2,3,3,3,3,4,4,4,3,3,4,3,4,4,4,3,3,2)

Gender <-  c(1,2,1,1,2,1,1,2,1,2,1,1,2,1,1,1,1,2,2,1,2,1,1,2,1,
             2,1,1,2,2,1,1,2,1,2,2,1,1,1,1,2,1,1,1,1,1,1,1,2,1,
             1,1,1,1,2,1,1,2,2,2,2,2,2,2,2,2,1,1,1,1,2,1,2,1,2,
             1,1,2,1,1,2,1,1,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,1,2,
             1,1,2,1,2,1,2,2,1,1,1,2,1,1,1,2,1,1,2,1,2,2,2,1,1,
             2,2,1,1,1,2,1,2,1,2,2,1,1,1,2,2,1,2,2,2,2,1,2,2,1,
             2,1,2,1,1,2,2,1,1,1,2,2,1,2,2,2,1,2,2,1,1,1,2,2,2,
             1,2,1,2,2,2,2,1,1,2,1,1,1,2,1,1,2,2,1,1,1,1,2,1,1)

Age <-     c(2,3,2,1,2,2,2,2,3,2,2,1,2,2,2,2,2,2,2,2,2,2,2,3,2,
             3,3,3,1,2,2,3,2,2,2,1,3,2,2,2,2,2,2,3,2,2,2,2,2,1,
             3,3,2,3,2,2,2,2,2,2,2,3,2,2,1,2,2,2,1,2,2,3,2,2,1,
             2,2,1,2,2,1,2,2,2,2,2,2,2,3,2,2,1,3,2,2,2,3,2,2,2,
             3,1,2,1,2,2,1,2,2,2,2,2,2,1,2,2,3,1,2,2,2,2,2,2,2,
             2,3,1,1,2,1,2,2,2,2,2,2,2,2,1,3,2,2,2,1,2,1,1,2,1,
             2,1,1,2,2,2,2,2,2,2,2,3,2,1,2,1,1,2,3,3,1,3,3,2,2,
             2,2,2,2,2,2,2,3,2,3,3,2,2,2,3,1,2,1,2,3,2,2,2,3,2)

emp.dat <- data.frame(Gender = factor(Gender, labels = c("M",
"F")),
                      Age = factor(Age, labels =  c("<30",
"30-44", "45
+")),
                      satisfy)
pop.gender <- data.frame(Gender = c("M", "F"), Freq =
c(3800, 6200))
pop.age <- data.frame(Age = c("<30", "30-44",
"45+"),
                      Freq = c(2000, 5000, 3000))

library(survey)
emp.svy <- svydesign(ids = ~0, strata = NULL, weights = ~rep(50, 200),
                     data = emp.dat)
rake.svy <- rake(emp.svy, list(~Gender, ~Age), list(pop.gender, pop.age))

cal.svy <- calibrate(emp.svy,
                     formula = list(~Gender, ~Age),
                     population = list(pop.gender, pop.age), cal.fun
"raking")
# Warning message:
#   In regcalibrate.survey.design2(design, formula, population,
aggregate.stage # = aggregate.stage,  :Sample and population totals have
different names.

# check weights--M and F seem reversed when "calibrate" used
library(reshape2)
check1 <- with(rake.svy, cbind(variables, weight = 1/prob))
dcast(check1, Gender~Age, sum, value.var = "weight", margins = TRUE)
check2 <- with(cal.svy, cbind(variables, weight = 1/prob))
dcast(check2, Gender~Age, sum, value.var = "weight", margins = TRUE)