This idea of using modifiers comes up pretty often. I posted about it a while back.
Here’s my issue with it. By using a modifier in the way you describe, Buzan isn’t actually creating a true “4-digit” system. He’s creating a “1+3 digit” system. He needs two intentional elements to encode that 1+3 structure. By doing that, he’s reducing the data compression to 4 digits across two elements, equivalent to the 2:1 compression ratio that you get from a 2-digit system. This “4-Digit System” is actually a DOWNGRADE from just using a 3-digit system where the three digits are represented by a truly single intentional element at a 3:1 compression.
(There is an important difference when talking about how many digits are compressed into each single mnemonic ELEMENT vs. how many elements and/or digits a SCENE contains, and how we communicate that when we talk about what a SYSTEM is capable of. I think people often confuse these things when talking about creating “a new x-digit system.” Here’s an older post about trying to clarify some of those terms to try to help folks communicate a bit more clearly.)
Think about a PAO where each element encodes 2 digits. It isn’t a “6-digit system.” It is a structure that allows you to encode 6 digits across 3 elements. A 2-digit PAO gives you a 2:1 compression ratio with the elements used and the scenes that are constructed. A 2-digit PO gives you the same 2:1. Even a single association system where every 2-digit number only gets one element associated with it gives you a 2:1 compression.
Yes, you can fit more digits into one SCENE by adding categories or modifiers like “person-action-adjective object”, or “environment-person”, or by repeating structural elements like making a “person-action-object-person-action” scene, but you need to consider the total number of elements that must be combined intentionally in order to create that scene and that ratio of digits:elements. Person-Action-Object-Person-Action isn’t a 10-digit system. It’s a 2-digit system with a 10-digit scene structure across 5 elements per scene. To me, the digits-per-scene number is basically irrelevant and not a good metric to use to compare systems.
When I talk about a 4-digit system as being theoretically superior to a 3-digit one, I mean a system that can take 4 digits and compress them into a single non-compound mnemonic element. So something like 1274 being represented by a “TaNKeR” truck would be a single element in a “true” 4-digit system. Compare this to the modifier system where 1274 is represented by a door kNoCKeR being encased in a block of Ice. The structure of that association isn’t really 1274, it’s actually 1-274, a compound image made from two distinct intentional elements. The Ice is an intentional single-digit modifier element that needs to be actively considered and incorporated into the scene when looking at the 1, then the 274 needs to be similarly translated so that you know what is being affected by the Ice. You get the same value (4 digits, 2 elements) from just doing a PO (ToNy CaR), PA (ToNy CaRRy) or even a 2-digit “adjective-object” system (TiNy-CaR.) In those cases, you only need to learn 200 associations, much easier compared to the 1000+10 needed with a Modifier+3digit system. If you’re only getting a 2:1 overall compression ratio from your scene, you might as well stick with a system with less associations to learn. Or, since you’re using two elements anyway with a modifier system, just combine two 3-digit elements to keep your 3:1 ratio: 127-471 = TaNK RoCKeT.
Lets look at examples of each type of system with 2 intentional elements per scene:
- 1-digit - 12 - Tea Neo - 2 digits per scene using 2 elements, 1:1 compression
- 2-digit PO: 12-74 = Tony Car - 4 digits per scene using 2 elements, 2:1 compression
- 3-digit + Modifier: 1-274 = Ice kNoCKeR - 4 digits per scene using 2 elements, 2:1 compression.
- True 3-digit: 127-471 = Tank Rocket - 6-digits per scene using 2 elements, 3:1 compression.
- True 4-digit: 1274-0274 = Tanker Sinker - 8 digits per scene using 2 elements. 4:1 compression.
The true 4-digit is clearly superior for data compression and scene capacity, but there are 10,000 associations to learn fluently, making it impractical. The sweet spot usually ends up being 3-digits with 3:1 compression where 1000 total fluent associations is realistically manageable.