Entropy Balancing Did Not Create Balanced Means (R)

Question

I am looking at how sex impacts judicial decision making and am trying to balance my dataset where my treatment variable is named "gender.judge" (0 for control group, males, and 1 for treatment group, females). I want to balance the data on these relevant variables: jcs, confirmation year, party, racial minority, and judicial experience.

By using this code, I am able to create and add weights to my dataset. However, when I use the summarize function to assess whether the balancing was successful, I am left with different weighted means in the treatment and control groups.

Why is my entropy balancing not successfully weighting the covariates?

My code:

library(ebal)
library(data.table)
eb <- ebalance(Treatment = abortion$gender.judge,
               X = cbind(abortion$jcs,
                         abortion$confirm.yr,
                     abortion$party.judge,
                         abortion$minority.judge, 
                     abortion$jud.experience))
#all the treated observations have weight=1
abortion_treat <- abortion |>
  filter(gender.judge==1) |>
  mutate(weights=1)
#control observations have weight based on the entropy balancing
abortion_con <- abortion |>
  filter(gender.judge==0) |>
  mutate(weights= eb$w)
abortion_balanced<- bind_rows(abortion_treat, abortion_con)
#Verifying that the groups were properly balanced
abortion_balanced |> 
  group_by(gender.judge) |>
  summarize(weighted.mean(jcs, weights), 
            weighted.mean(party.judge, weights), 
            weighted.mean(confirm.yr, weights), 
            weighted.mean(minority.judge, weights),
            weighted.mean(jud.experience,weights))