[R-sig-ME] How to interpret the output for nested random factors in glmer and what to write in a table

[N o s t a l g i a]

Hi, this is something I posted on Cross Validated a few days ago, but 
since I failed to get any substantial answers, I am posting a question 
here, hoping someone could help me, as I am getting desperate.

I am looking at an alternation of a character in a word using a Japanese 
congressional record. I have a binary outcome dependent variable (kuni), 
the date of the meeting expressed as the standardized number of days 
since 1949/05/31 (days_cnt2) as the only fixed variable, and two random 
factors for meeting (meetid) and word (morphid). Because there are 
several meetings in a given day, and a meeting is specific to a specific 
day, the meeting variable is nested under days_cnt2. Thus, the model 
looks like kuni~days_cnt2+(1+days_cnt2|morphid)+(1|days_cnt2/meetid). I 
ran a binomial logistic regression with glmer and got the following output:

Command:
result <- 
glmer(kuni~days_cnt2+(1+days_cnt2|morphid)+(1|days_cnt2/meetid),data=glmmdata6,family=binomial, 
control=glmerControl(optimizer="bobyqa",optCtrl=list(maxfun=2e5))

A part of the output (summary):
Random effects:
  Groups           Name        Variance Std.Dev. Corr
  meetid:days_cnt2 (Intercept) 14.0795  3.7523
  days_cnt2        (Intercept) 26.7335  5.1704
  morphid          (Intercept)  3.3889  1.8409
                   days_cnt2    0.2283  0.4778   0.71
Number of obs: 748186, groups:
meetid:days_cnt2, 12034; days_cnt2, 1189; morphid, 301

Fixed effects:
             Estimate Std. Error z value Pr(>|z|)
(Intercept)  -9.2793     0.3416  -27.16   <2e-16 ***
days_cnt2   -11.8274     0.3045  -38.84   <2e-16 ***

The ICC values are:
Adjusted ICC: 0.931 Unadjusted ICC: 0.237

Now I have several questions for this result:

1. Am I right in saying word (morphid) has less effect than meeting 
(meetid) on kuni, based on the fact that the former has only about half 
SD (1.8409) of the latter (3.7523)?

2. How should I interpret the two days_cnt2 parameter values in the 
random effects section?

3. When publishing the result in a paper, should I include the values 
for all of the four effects (meetid:days_cnt2, days_cnt2, morphid, and 
days_cnt2) or should I skip days_cnt2?

Thanks in advance,

Kenjiro Matsuda