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Oldest tendencies in human understanding of the world:
“reduction” to basic principles ... the first “strucutural” ideas ?
the principles are not directly accessible
Beginning of “combinataion theory” (?):
ancient Greeks: 4 components - water, fire, soil, air
Middle ages: Universalia
nominalism = sunt nomina et flatum vocis
realism
= sunt realia ( Platon-like ?)
Analytical philosophy - theoretical vs. empirical entities and attributes
Strict positivism: reduction sentences - reduction of theoretical to observable
Modest analytical philosophy:
- what are the relationships between them ?
- appropriate concept formation
correspondence problem
Related topics to empirical vs. theoretical problem:
- systems theory:
black box, hidden elements, internal state
- behaviorism:
S - R paradigm, Tolman’s “intervening “ variables
- measurement theory: indirect, associative, pointer measurement, m. “by fiat”
- induction - deduction problem
- exploratory - confirmatory approaches
Layers from directly observable to heuristically hypothetical vs “real”
Levels in analytical philosophy of science:
- empirical - “directly observable” (through “reasonably” scientific diagnostic
procedures, rigorously standardized)
- pure dispositional
- theoretico-dispositional
- theoretical concepts
- hypothetical
the last 4 called often altogether generically
theoretical concepts ... in wider sense
or “constructs”
Philosophical ways to look at theoretical concepts:
fictionalism
conventionalism
theory of levels
constructivism
neutralistic view
instrumentalism
......
operationalism
.....
naive realism
Two dichotomies play role in theory building:
1. empirical vs. theoretical levels
2. “real”
vs. formal level
Problems of formalization:
- formal representation of observation ... data coding - not necessarilly but including
data quantification and
measurement
(“raw research record” - data - variable not-necessarillyquantitative)
- modeling: - theory , its structure, formal model ...
- regression- like models,...
- not-quantitative models
- theory-data relationships
in quantitative models the correspondence problem as
associative measurement problem
Correspondence relationships:
- logical definition, problem: irect explicit definition vs. partial conditional
definition
- “causal” implication
- nondeterministic: - fuzzy logic implication
- stochastic: - conditional probability
- regression, correlation
- information theory measures of association