From Terminator to Governor to Adulterer

Arnold, really? Ten years ago you weren’t satisfied enough, either emotionally or sexually, that you needed to cheat on your wife of 15 years? And worse yet, you cheated on Maria without using proper birth control so you inadvertently ended up fathering a child with your mistress?
I hope, for Maria’s sake, you also didn’t end up with an STD that you then passed along to her.
Your past indiscretions are now at the forefront of the nightly news.
Here’s what you have you passed on to the four children conceived with Maria:
Embarrassment.
Shame.
Deceit.
Disregard for commitment.
Disregard for the dignity of their mother.
As a former radical feminist in my college years, I can tell you every reason why marriage can be oppressive for women. I could go back to my scholarly books and explain why the institution of matrimony keeps women economically and emotionally dependent on men, and the reasons why women should choose to remain single.
But I am not going to…
Because when I married my husband thirteen years ago, I married my best friend.
Marriage, either religious or civil, is ultimately a social contract that reflects a couple’s commitment to share the joys and burdens of this world together on a single journey. It is why gay men and lesbians are fighting to have marriage legalized. There is something profoundly human and otherworldly when we give our life to another for a lifelong commitment.
Marriage says life is more meaningful and beautiful when shared, that there is something greater than just me. That together, we can make a change for good.
So to witness Arnold Schwarzenegger or James McGreevy or Bill Clinton cheat on the mother of their children, I want to cry.
I want to mourn for all the children who will think sex is more necessary than being honest and forthright with their wife or husband.
I want to mourn for all the children who won’t believe a lifelong commitment is possible.
And I want to mourn for all the children who themselves will one day become part of the statistic 1 in 2.


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