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How Not To Track Safety · Apr 22, 11:38 AM

(Originally posted 4/22/05)

In what could be a case study in how not to evaluate ride safety, or possibly how website operators can call visits to amusement parks (deductible?) “independent safety observations,” I point you to AmusementSafety.org.

What is, I guess, the heart of the site is the “Inside Tracker, which purports to track trends relating to safety (and, in the case of Cedar Point, complaints about the Hotel Breakers).


But the information provided is both sparse and generally useless. It’s interesting to hear, for example, that 85% of respondents felt unsafe on Top Thrill Dragster, but it doesn’t really tell us anything about the actual safety of the ride. (Indeed, the only injuries related to that coaster of which I am aware were to people not on the ride.) As many psychologists could tell you, people like thrill rides precisely because there is a feeling of risk. Unless those 85% of people had a specific reason—a reason that could be confirmed independently—for feeling unsafe, the statistic just tells me that Top Thrill Dragster is a big ol’ fast ride that scares people, which is exactly what it’s supposed to do.


Similarly, Six Flags New England gets a “poor” rating because apparently lots of people asked if Superman is a safe ride. Again, asking questions about a ride’s safety is interesting (and a good, and understandable, idea), but how that translates into a poor rating is questionable at best. Superman has certainly had its problems (see here for some documents related to some of them), but the data relied upon to say that patrons are “rightfully suspect” of the parks’ rides are entirely absent.


While I appreciate the goal of better reporting of safety issues (and for a good cogent discussion of those issues, see Kathy Fackler’s site), this just isn’t it. It purports to identify signals and comparative data where those data simply aren’t sufficient to support that evaluation. SaferParks.org does a much better job with a much clearer understanding of the limitations of their data.

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