This seems like extending the "known knowns" concept to an additional dimension, involving truth.
In the known-knowns model, you have knowledge and metaknowledge (what you know, what you know you know):
K U -- What you know
K KK KU
U UK UU
\
What you know you know
If we add truth to that, you end up with a four-dimensional array with dimensions of knowledge, knowledge of knowledge, truth-value, and knowledge-of-truth-value. Rather than four states, there are now 16:
TT TF FT FF (Truth & belief of truth)
---- ---- ---- ----
KK | KKTT KKTF KKFT KKFF
KU | KUTT KUTF KKFT KKFF
UK | UKTT UKTF UKFT UKFF
UU | UUTT UUTF UUFT UUFF
False information is the FT and FF columns.
In both the TF and FT columns, belief of the truth-value of data is incorrect.
In both the KU and UU columns, there is a lack of knowledge (e.g., ignorance), either known or unknown.
(I'm still thinking through what the implications of this are. Mapping it out helps structure the situation.)
In the known-knowns model, you have knowledge and metaknowledge (what you know, what you know you know):
If we add truth to that, you end up with a four-dimensional array with dimensions of knowledge, knowledge of knowledge, truth-value, and knowledge-of-truth-value. Rather than four states, there are now 16: False information is the FT and FF columns.In both the TF and FT columns, belief of the truth-value of data is incorrect.
In both the KU and UU columns, there is a lack of knowledge (e.g., ignorance), either known or unknown.
(I'm still thinking through what the implications of this are. Mapping it out helps structure the situation.)