![]() ![]() # - Excluding technical academy awards to make results more comparable # - Collecting larger sample of films (e.g., prior years) # - Other data (say budget or date of release) # - List of films with Metacritic scores above ~69 with zero nominations # Metacritic scores taken from individual film pages on meteoritic # Fractional Oscar nominations (e.g., 8.75, 9.25 instead of 9) done to prevent overlapping labels # Number of Oscar nominations taken from above and wikipedia More broadly, there doesn’t appear to be much correlation between what critics like and recognition by the Academy.Īs to the plot, there’s lots of room for improvement so I’ve posted the data and code below. That said, both films appear to have gotten a raw deal when you compare critical reception to Academy Award nominations. So, is Selma an outlier? David Carr appears to have missed one other film, Two Days, One Night, that rated slightly higher than Selma on Metacritic and received only one nomination. ![]() What’s the relationship between critical acclaim and Oscar nominations? Practically none. This got me wondering, was Selma an outlier?Ĭurious to assess the relationship between critical commentary and nominations, I quickly collected some small data and plotted the relationship among films nominated in the major categories: Perhaps that partly explains why “Selma,” which was second to “Boyhood” in critical acclaim as measured by Metacritic, received just two nominations, for best picture and best song. The movie was completed near the end of the year, and the screeners came late and somewhat sporadically. Reading David Carr’s piece on Why the Oscars’ Omission of ‘Selma’ Matters, I was struck by this passage: See the article and video segment, here: ![]() “And so the instant matching has the effect of reducing the individual discretion where those sort of implicit biases may come to play a role in the judgment of the passenger and the driver.” “What’s nice about what’s happening on Uber is there’s no discretion for the driver or the passenger in this kind of instant matchmaking to say, ‘I don’t want that type of person to be driving me,'” Wasow said. The key may be the app’s interface, which makes it harder for drivers to refuse passengers on the basis of their race or their destination. Wasow, who focuses on race and technology, argues that on-demand sites and apps have the potential to reduce subtle and not-so-subtle forms of discrimination.įor example, Uber has been credited by some for making it easier to hail a taxi for people of color. It reflects the same kinds of social biases that we see in the real world.” It invites the kind of discrimination that we’ve seen for a long time in accommodations,” Omar Wasow, an assistant politics professor at Princeton University, told “Nightline.” “The internet is not a utopia. “On a service like Airbnb where you’re not necessarily automatically matched, the host has some discretion about accepting you or rejecting you. Though Uber and Airbnb are often thought of as similar kinds of online marketplaces, Uber’s matchmaking happens without much input from either party while Airbnb grants hosts significant control of whether to accept a particular guest. While some prior research has focused on the role anonymity in reducing bias, I argue that the key issue in this case is whether transactions are automatic or optional. Nightline recently investigated allegations of racial discrimination in the “sharing economy” following the rise of the #AirbnbWhileBlack hashtag on Twitter.
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