Interpreting an order logit

#1
This isn't my homework, but was acctually meant for my blog. I had planned on running the ordered logit models, running predicted probabilities and then posting them on my blog but I got a little stuck interpreting my models. Here's one of my five models, can anyone help:

I run everything in R and these are my coeficients for the ologit model as produced using the zelig package in R.



Call:
zelig(formula = typea ~ age + race + edu + income + feel + feel2,
model = "ologit", data = one)

Coefficients:
Value Std. Error t value
age -0.002207 0.003773 -0.5849
race -0.107859 0.066206 -1.6291
edu -0.087984 0.037994 -2.3158
income -0.017992 0.023550 -0.7640
feel 1.139626 0.067260 16.9435
feel2 0.283938 0.048745 5.8250

Intercepts:
Value Std. Error t value
Lowest|2 1.0691 0.2900 3.6868
2|3 2.3517 0.2948 7.9772
3|4 4.0490 0.3090 13.1051
4|Highest 5.8281 0.3288 17.7279

Residual Deviance: 3101.106
AIC: 3121.106
(402 observations deleted due to missingness)


Here's the confidence intervals:

confint(mod1)

2.5 % 97.5 %
age -0.009601091 0.005193541
race -0.237763227 0.021851245
edu -0.162554086 -0.013565462
income -0.064180859 0.028166631
feel 1.008926396 1.272672351
feel2 0.188612935 0.379751001