Jada Pinkett Smith sent out the following tweet regarding the Oscar nominations:
On Monday, Martin Luther King Jr’s birthday, both she and Spike Lee announced that neither would attend the Oscar ceremony because of the lack of diversity in the nominations. The diversity that she is pointing out here is the lack of underrepresented minorities nominated in the four actor/actress categories.
For the record, the last two years of Oscar nominations have been less diverse in terms of underrepresented minorities than some of the previous years. The following table shows the number of nominations in each of the actor/actress categories as well as the best director category by race — White/Under Represented Minority — for 2010 through 2016.
The row identifies the number of the nominations in each year that belonged to one of the two classes identified (White or Under-represented minority). Between 2010 and 2015, 15 of the 150 nominees in these categories qualified as underrepresented minorities – exactly 10%. So, is Hollywood too white? Do the Academy Awards give ‘enough’ accolades to underrepresented minorities? How does this relate to human resources?
Pitfalls in Analysis
There are two parts of this analysis. The first is identifying underrepresented minorities. I use the AAMC definition: African Americans, Native Americans, Mexican Americans and Mainland Puerto Ricans. But, I cheat a little – I also include Mexicans and Cubans – two groups of persons who are, in my opinion, underrepresented minorities. The second part of this analysis is choosing the categories and the time frame under which to examine them.
These elements are important in human resources because if your organization is going to engage in a study of diversity, you need to establish if you are going to examine the number of workers who are white relative to non-white, examine workers by race as identified by the EEOC, focus your analysis on underrepresented minorities, or parse your data by some combination of these identifiers. Second, you need to establish a time frame across which you can draw comparisons and find and interpret trends.
Although I examine the Oscar nominations according to underrepresented minority status, I could easily have focused on age across the different categories or identified the frequency with which a woman is nominated for the best director Oscar. In your setting, it might make sense to perform multiple analyses depending on the types of questions you are seeking. Also, I could have just looked at 2016 and seen that only 1 underrepresented minority was nominated and declared the Oscar nomination process a complete failure with respect to underrepresented minorities. But, when looking at the last 6 years, you can see that there are some successes; although only 10 percent of the best supporting actresses are underrepresented minorities, they have won the Oscars 50 percent of the time.
If (or when) your organization decides to look at its workforce through the lens of age, race, ethnicity or status, pay close identify the kinds of questions you want answers to and then categorize your data accordingly. And, look at your data across multiple years to find long-run trends. Remember, your data can tell a great deal about your organization if you take the time to work the numbers in a mindful way.
I’ve written more about the Oscar nominations here: https://theconversation.com/how-white-are-the-oscars-and-does-it-matter-53466
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This Blog was authored by Thomas More Smith, PhD, CHRS Labor Specialist – January 23, 2015