Degrees of justification#
A degree of justification (DOJ) quantifies how justified a truth-value assignment is in light of a debate. A DOJ always lies in the interval [0, 1] – and can be treated as a probability in the sense that it fulfils the Kolmogorov axioms ([Betz2012], Theorem 6).
See also
The concept was introduced to the theory of dialectical structures in [Betz2012].
- taupy.analysis.doj.doj(pos, debate=None, conditional=None)[source]#
Returns the degree of justification for the position in
pos
relative to adebate
, as defined in [Betz2012]. Ifdebate
is None, the debate stored in the Position object is used.The conditional doj is returned if
conditional
is given another position of the same debate. Whenconditional
is set,debate
must be None.
Tip
taupy.doj()
returns a fraction. If you want to use integers instead,
call float(doj())
.
Unconditional DOJs#
Let
The DOJ of a position
from taupy import Argument, Debate, doj
from sympy.abc import a, b, c
# returns 3/7
doj({c: False}, debate=Debate(Argument(a&b, c)))
Note
The DOJ of an incoherent position always equals zero. The DOJ of a
complete position equals
Conditional DOJs#
We can not only ask the question of how well a position is justified given a
debate simpliciter, but also how well it would be justified if some statements
in the debate were taken for granted. Let
In taupy
, a conditional DOJ is calculated with the
conditional
argument:
from taupy import Argument, Debate, Position, doj
from sympy.abc import a, b, c
pos1 = Position(Debate(Argument(a&b, c)), {a: True})
pos2 = Position(Debate(Argument(a&b, c)), {c: True})
# What is the degree of justification for pos1, conditional to pos2?
# Returns 1/2
doj(pos1, conditional=pos2)