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Guest Thinkers

Understanding Our Latent Feelings About Race

The main thing I try to remember whenever I write a piece for this blog is to stay in control of the narrative. The narrative is not just an academic sounding term that comes to mind whenever you watch a movie or read a book – it is the underlying storyline that underpins every kind of communication we engage in, whether it is in person, via phone or text message, or through a news show, a TV commercial, or a sales pitch. Even our religious beliefs are guided by the narrative form. Practically every religion in the world is built around stories of trial and triumph, of outer struggle and inner peace, which are the same elements that any writer in any arena strives to use to the best of his ability.

I would hope, after a week like the one we’ve been through, that the narrative on race is expanding. We’ve got a population where people of all stripes need to see beyond the end of their own experiences, but are mighty, mighty comfortable with the labels we allow ourselves to be stuck with. So tonight, if you are still up, like I am, surfing the web, I challenge you to spend ten minutes to take the Race Implicit Association Test devised by Harvard researchers at Project Implicit who are trying to understand our latent feelings about race.

To be honest with you, I was concerned about taking the test. I was certain that I would be pegged as a future Black Panther, a budding revolutionary ready to take it to “The Man” by any means necessary.

Instead, I got this:

Your data suggest little to no automatic preference between European American and African American.

The interpretation is described as ‘automatic preference for European American’ if you responded faster when European American faces and Good words were classified with the same key than when African American faces and Good words were classified with the same key. Depending on the magnitude of your result, your automatic preference may be described as ‘slight’, ‘moderate’, ‘strong’, or ‘little to no preference’. Alternatively, you may have received feedback that ‘there were too many errors to determine a result’.

Give it whirl. You may be surprised at the results.


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