Lack of Variation in Slopes

Hi all,

I have a very perplexing issue that I can't solve.  I am running a model
that resembles the following:

model.lmer<-lmer(A~B*C+(B+0|Male)+(1|Male)

A--continuous response variable
B--continuous, grand mean centered predictor variable
C--Factor with 11 levels
Male--Factor with 33 levels

When I check coef(model.lmer), the results under column B (i.e. slope) are
the same across all 33 males.  This does not make any sense to me.  When I
change the response variable to anything else other than A, I see variation
in the slopes.  This goes for my 2012 data set only.  When I run my 2011
data using the same exact model from above, but referencing the 2011 data
frame, I see variation in slopes.  Finally, when I swap the data for C from
2011 to C for 2012, I also see variation in slopes.

 For whatever reason, I can't figure out what is going on with the 2012
data set.  I have checked and rechecked my data in excel.  I have also
exported the data as a .txt file and reimported it back into excel and that
hasn't fixed anything.  There is absolutely no reason that I can think of
for this to occur.  Any ideas?

You were spot on with your suggestion.  Thank you very much for your help.
I had mentioned before that I probably should keep random slopes within my
models since that is a primary interest of my study, regardless of whether
a LRT suggests they are needed.  Would you still recommend keeping them
within the model?

Jacob