In her essay “Pragmatic Laws”, Mitchell rejects the
normative and paradigmatic approach to laws. As she said, she is not going to
define what law is, but to discuss the “understanding” of the usage of
generalization in science. Firstly, Mitchell discusses about the traditional
view of laws, the normative approach. In normative approach, scientists need to
find or create strict laws that can be applied generally. By inputting
different initial conditions, these laws will generate specific outcomes that
meet the phenomena of natural world. If people cannot find such laws in
biology, then it means there are no laws in biology. The normative approach
ignores the degree of contingency. Mitchell argues that many laws, especially
biology laws, do not have clear distinction between university and contingency.
Next, Mitchell discusses the paradigmatic approach. In this approach, scientist
will compare the generalization in biology with the laws in physic or other
science to see if there is a match. If the generalizations in biology are like
the law in other science, then there are laws in biology. The paradigmatic
approach fail to define laws in some “unsystematize space” where no physical
laws can be referred.
Finally, Mitchell puts forward her pragmatic approach to biological laws. Since the biological world is relatively complex and involves numerous initial factors, she argues that we should rather focus on the functions of biological generalizations and how they acts as “laws.” If generalizations can provide good prediction of natural phenomena, then we should regard them as “laws”, or at least “law-like.” Mitchell argues that pragmatic laws should be regulate by degree of accuracy, level of ontology, simplicity and cognitive manageability, as well as the stability and strength.
I agree that in biology science, it is difficult to generalize perfect strict physics laws. However, I would regard Mitchell’s pragmatic approach to laws as permissive.
Firstly, the pragmatic approach is permissive because it
allows “unscientific approaches.” Mitchell ignored one of the key functions of
laws of natural, which is that they help and direct science researching path.
By saying “unscientific approach”, I mean to speak of those immature and not
well-formed generalizations, such as Ptolemy’s theory, which predicts the
planets’ orbit but it is false. Strict normative definition of law can exclude
many “unscientific approaches” from science research. The reason we want to
have laws is because we need guidelines in scientific research, but the
pragmatic approach allows these “unscientific approach” to function as laws,
which will bring confusion. Without a clear definition of the laws, how can we
distinguish lawful generalizations from accidental truth?
Admittedly, Mitchell gives precise restriction to her
pragmatic laws by arguing that contingent generalizations should be valued and
restricted by some important parameters, including the degree of accuracy,
level of ontology, simplicity, and cognitive manageability plus stability and
strength (in Leuridan’s paper). Mitchell argues that if they cannot meet the
standards, these generalizations will be considered as not useful and should
not be used as laws. However, her regulations are still permissive. This leads
to my next objection against pragmatic laws.
Mitchell’s pragmatic approach allows contingent mathematical
model become laws. She allows the contingent initial condition to join with the
statement, which is excluded from normative approach. In normative approach, we
do not have initial conditions, or say, all this initial conditions is built
from the Big Bang, from the beginning of the universe. Every normative law is
in the structure of “all P is Q.” While pragmatic laws allows “I→[if P then
Q].” This kind of permissiveness will
lead to the arbitrariness of the formulation of laws. If scientists find out
that a contingent statement I1→[if P then Q] does not function well, they can
easily add more initial conditions until their contingent generalization ( in
the form of I1, I2 I3… In→[if P then Q])becomes more stable and fits the
natural phenomenon. Actually this is the process of mathematical modeling.
Mathematical models are precise generalizations that can help scientists to
predict or analyze nature or social phenomenon, within certain contingent
conditions. In the pragmatic approach, these mathematical models can be fit in
Mitchell’s regulations, especially stability and strength. People may suspect
the simplicity of mathematical models. However, many models do reflect the
natural simplicity. In economics, all we have is these generalizations, which
we call them mathematical models. We have Taylor rule in monetary economics,
which can precisely predict the relationship between nominal interest rate,
GDP, and inflation rate. It can perfectly meet Mitchell’s regulations, since it
is simple, statistical precise, empirical, and stable in a certain timescale.
However, why economists never call their economics models laws? Firstly, models
are merely generalizations. There must be precise strict laws underneath. In
biology and economics, a phenomenon may involve with numerous laws and factors.
It is impossible to find out all the laws and unrealistic to use complex
combinations of strict laws to predict phenomena. Thus, we have to use
contingent generalizations. Secondly, contingent generalizations fail to meet
the functions, as I have mentioned previously. Taylor rules may have good
prediction, but since we are not sure the complex mechanism, it is hard for us
to consider it as a law. Therefore, if Taylor rules cannot be seen as a real
law, then how can we consider those biological generalizations as laws?
In addition, it is not necessary to count “lawful
statements” as laws. Against the criticisms that pragmatic approach is
permissive, Leuridan argues that contingent generalizations do play the role of
laws in the history of science. He also argues that these generalizations “fit
the actual science practice” (326). Leuridan made a mistake by arguing
contingent generalizations are useful when they are being regarded as laws. I
agree with Mitchell and Leuridan’s recognition that contingent generalizations
do have the function as laws of natural. I do realize contingent
generalizations do help scientists develop their science research and explain
the natural. However, the classification of contingent generalizations as laws
does not contribute to their function in science. By this, I mean that it is
true that excluding contingent generalizations from being “true laws” do not
stop scientists from using them in scientific research. Mathematical models
that generalize a complex phenomenon can function well without being regarded
as a law. Economist never say their supply and demand model as a “price law”,
but it still help us to predict price for several centuries.
In conclusion, Mitchell successfully recognize complexity
when explaining biological phenomenon and the useful functions of contingent
generalization, but her pragmatic approach fails to notice the basic functions
of laws.
No comments:
Post a Comment