Weak Naturalism: It is possible to use natural science to investigate social phenomena.
Strong Naturalism: It is necessary to use natural science to investigate social phenomena.
Science in general:
empirical research using observation
develop coherent theory
community to evaluate
P-T (Predictive Theory) naturalism: (string naturalism)
un-observable as tool
law-like, derive consequence
prediction as evaluation
Logical positivism (logical empiricism): beyond scientific logic
science is successful because of its epistemology: "what can be dirrectly observed by the scientists"
confirm or dis-confirm by empirical phenomena that can be deduced from the set of claims that make up those theories.
un-observable properties are parsimonious ways to describe relationships among directly observable phenomena.
universal, exception-less natural laws are central feature of scientific theories
science use common logic to reason about the world
verify predictive theory by its successful at prediction
Anti-positivism: reject ideas above
positivism fails to take bias of holding on to existing paradigmatic ontological and mythological stances.
un-observable entities are real
fails to recognize choice of theory does not depend on empirical adequacy
in tool: theoretical constructs operate as organizing device
ideal types: concept of classification
tool to how specific concrete phenomenon
in law: no law
no law of nature in social science
rational decision-making of human is unpredictable
in prediction: not reliable
by free-will, decision making
in evaluation: prediction is not accurate
good to have categories? in terms of understanding and predicting.
Goal of categorization: be able to make generalization
therefore, it helps us to make prediction, being able to know the range of generalization, although may be inaccurate, but better than nothing
it also help understanding an event
I think categorization is essential to all science, because without categorization, there is no generalization. If a theory is not generalizable, there is no value, because without generalization, there exists no prediction.
Little gives a consistent and coherent account on the issue of prediction and validation of social theories. Little argues that social science does use their theory to predict, but such prediction may only predict a statistical trend that has a high error (page 7), and due to such uncertainty, social theories are tested through individual sub-component of the theory using empirical data (page 8). To make sense of Little's argument, I assume that prediction using the theory as a whole will not generate meaningful results to validate the theory. Instead, social scientists tend to generate predictions using sub-claims of the theory that are more predictive in nature. To validate a social theory as a whole, therefore, is to validate sub-claims of the theory independently. Thus, I see Little's claim and reasoning consistent because although Little agrees that social theory needs empirical support, but such support differs from traditional empirical support used by physical science.
is unity of science a good argument I view that as an intuition from empirical evidence (also says in the paragraph). I guess there is no formal way to prove that "unity of science" always hold?
pluralism's argument valid?
his view: because of diversity, a unified methodology is not achievable, therefore, not necessary.
Logically doesn't make sense. A better argument might be: since we can't make progress using unification, therefore we take a step back to at least make some progress.cmf
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