“I’ll grant that if we roll the dice enough times, the 1⁄100 cases will start to dominate, but we only have 2 categories of near misses. That doesn’t seem like enough to let us assume a 1⁄100 ratio of catastrophes to near misses.”
In this case total probability of near misses will be something like (1/100 +1/3000)/2 = almost 1⁄200. If we look into nature of cold war near misses we could see that 1⁄100 estimate is more probable.
More research need to estimate what field is more equal to cold war. Probably it would be nuclear accidents on power stations.
Large research on the topic is here.http://www-pub.iaea.org/MTCD/Publications/PDF/Pub1545_web.pdf But it doesn’t give exacxt estimate of the frequency of NM, stating it as few to thousands.
They define NM as chain of events and they also stated that rising security measures help to reduce NM frequency.
On my first link near-miss frequency is already aggregated: “Studies
in several industries indicate that there are between 50 and 100 near misses for every accident. Also,
data indicates that there are perhaps 100 erroneous acts or conditions for every near miss. This gives
a total population of roughly 10,000 errors for every accident. Figure 1 illustrates the relationships
between accidents, near misses and non-incidents.” http://www.process-improvement-institute.com/_downloads/Gains_from_Getting_Near_Misses_Reported_website.pdf
Ah, thanks for the explanation. I interpreted the statement as you trying to demonstrate that number of nuclear winters / number of near misses = 1⁄100. You are actually asserting this instead, and using the statement to justify ignoring other categories of near misses, since the largest will dominate. That’s a completely reasonable approach.
I really wish there was a good way to estimate the accidents per near miss ratio. Maybe medical mistakes? They have drastic consequences if you mess up, but involve a lot of routine paperwork. But this assumes that the dominant factors in the ratio are severity of consequences. (Probably a reasonable assumption. Spikes on steering wheels make better drivers, and bumpers make less careful forklift operators.) I’ll look into this when I get a chance.
“I’ll grant that if we roll the dice enough times, the 1⁄100 cases will start to dominate, but we only have 2 categories of near misses. That doesn’t seem like enough to let us assume a 1⁄100 ratio of catastrophes to near misses.”
In this case total probability of near misses will be something like (1/100 +1/3000)/2 = almost 1⁄200. If we look into nature of cold war near misses we could see that 1⁄100 estimate is more probable. More research need to estimate what field is more equal to cold war. Probably it would be nuclear accidents on power stations. Large research on the topic is here.http://www-pub.iaea.org/MTCD/Publications/PDF/Pub1545_web.pdf But it doesn’t give exacxt estimate of the frequency of NM, stating it as few to thousands. They define NM as chain of events and they also stated that rising security measures help to reduce NM frequency.
On my first link near-miss frequency is already aggregated: “Studies in several industries indicate that there are between 50 and 100 near misses for every accident. Also, data indicates that there are perhaps 100 erroneous acts or conditions for every near miss. This gives a total population of roughly 10,000 errors for every accident. Figure 1 illustrates the relationships between accidents, near misses and non-incidents.” http://www.process-improvement-institute.com/_downloads/Gains_from_Getting_Near_Misses_Reported_website.pdf
Ah, thanks for the explanation. I interpreted the statement as you trying to demonstrate that number of nuclear winters / number of near misses = 1⁄100. You are actually asserting this instead, and using the statement to justify ignoring other categories of near misses, since the largest will dominate. That’s a completely reasonable approach.
I really wish there was a good way to estimate the accidents per near miss ratio. Maybe medical mistakes? They have drastic consequences if you mess up, but involve a lot of routine paperwork. But this assumes that the dominant factors in the ratio are severity of consequences. (Probably a reasonable assumption. Spikes on steering wheels make better drivers, and bumpers make less careful forklift operators.) I’ll look into this when I get a chance.