A professor of women’s studies (what else?) writes in an op ed in the Boston Globe today that age bias results in too many old people dying. You know, she’s right. In fact, 100 percent of old people die in one way or another, whether due to accident, illness, or intentional act. It’s a national crisis!
Seriously, Margaret Morganroth Gullette argues that Hurricane Katrina shows us that we neglect our old people and they died in higher proportions than other age groups. I am not kidding.
More than 1,400 people in Louisiana perished because of Katrina. In November, the Louisiana Department of Health and Hospitals reported that 78 percent of the identified dead were over 51. Thirty-nine percent of the total were over 75.
Fifty percent of New Orleanians over 65 had disabilities, according to Elizabeth Fussell of the Social Science Research Council. That so many were poor, female, African-American, or ill only added to their vulnerability.
Yes, Gullette has come to astounding conclusion that those who were old and feeble and otherwise already at a health disadvantage were more likely to die in the natural disaster of Katrina. Quick, somebody get her a government grant to study whether water is wet!
It reminds me of the classic parody headline: “World to End Tomorrow: Women, Minorities Hardest Hit.”
Certainly, the elderly and infirm should not be forgotten in a crisis, but let’s keep in mind that many of those most determined to stay in their homes are those who told their would-be evacuators that they’ve lived a full life and would rather not abandon their homes or that the strenuous evacuation was much of a threat to their lives as staying was.
But for liberals like Gullette someone else’s misfortune or tragedy is never just, well, a misfortune or tragedy, but an opportunity to attack traditional institutions and highlight how the old patriarchal society (i.e., “rich white men”) uses and abuses those who are not the “winners of life’s lottery.”[Hat tip to Harry.]
Technorati Tags:ageism, discrimination, Katrina, liberalism