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How to Measure Scope in Tricky Resolutions


In the last post, we discussed Scope, a foundational concept in Omni theory. Scope is not always obvious. For example:

Resolved: The majority of people in an American city should permanently move to one specific province in Canada.

If you just look at the key phrases (Majority, permanently, one specific), this resolution is hard to evaluate. It’s difficult because we don’t have a clear idea of what an instance is. Let’s break it down by trying to identify the smallest possible instance.

  • An American city: Chicago

  • The majority of people in that city: 1.4 million

  • One specific province: Ontario

So one instance would be: 1.4 million Chicagoans permanently move to Ontario.


But is that the smallest possible instance?


We could shrink it down by picking a smaller town. Brewster, Florida is a company mining town that was shut down in the 60s. The company then lost the deed to the town in a legal settlement. 3 people still live there, making it the smallest occupied city in America.

Just for fun, let’s name the occupants of Brewster. Let’s call them Brianna, Hannah, and Savannah. The smallest instance of the resolution is: Brianna and Hannah should permanently move from Brewster to Ontario. If just Brianna moves, it’s not an instance. The resolution requires the majority of people in a city.

You may be noticing that most resolutions have a lot of instances. Just in Brewster, we have:

  • Brianna and Hannah move to Ontario.

  • Hannah and Savannah move to Ontario.

  • Brianna and Savanna move to Ontario.

  • Brianna and Hannah move to British Columbia …

If the resolution is specific, the affirmative only needs to find one possible combination that works. If it’s general, they have a lot more work to do.

Once you start looking at a larger city like Chicago, the number of possible instances becomes astronomical.


We’ll explore this idea more in the next post.


See this form in the original post