Why can't LinearSVC do this simple classification?

I'm trying to do the following simple classification using the LinearSVC object in scikit-learn. I've tried using both version 0.10 and 0.14. Using the code:

from sklearn.svm import LinearSVC, SVC
from numpy import *

data = array([[ 1007.,  1076.],
              [ 1017.,  1009.],
              [ 2021.,  2029.],
              [ 2060.,  2085.]])
groups = array([1, 1, 2, 2])

svc = LinearSVC()
svc.fit(data, groups)
svc.predict(data)

I get the output:

array([2, 2, 2, 2])

However, if I replace the classifier with

svc = SVC(kernel='linear')

then I get the result

array([ 1.,  1.,  2.,  2.])

which is correct. Does anyone know why using LinearSVC would botch this simple problem?