PHIL 481
April 1
More on factors that are part of Giere’s six-step program
Theoretical models:
Part of an “imagined world”
They describe “possible” structures, relationships, objects, and so forth
Not all theoretical models have scale models
“Does the model fit?”
A theoretical hypothesis claims that a particular model, M, is indeed similar to
some aspect of the world
Truth values (T or F) are appropriately attributed to a theoretical hypothesis, but
not to a theoretical model
“In general, asking whether a specific theoretical hypothesis is true is asking
whether a specific theoretical model fits the real world”
Theory: a family of models and a set of theoretical hypotheses
Evaluating theories using data
Gained through directed physical interaction with the world
Reliably detected
Determining whether a model fits is often not a matter of “just looking”
Predictions: using reasoning to determine what a model predicts and if this is in
keeping with accepted data
Components of an episode that will be used to construct a model for evaluating whether
theoretical models fit the world:
i.
ii.
iii.
iv.
a “real world” object or process to be investigated
a model of that object or process
some predictions derived from the model concerning what the data
would be like if the model fits
some data generated through interactions with the real world
relevant to these predictions
We do not speak of models as being ‘true’ or ‘false’ because they will fit the real world
only in some respects and then only to a specified degree of accuracy
Figure 2.9
Model fits/doesn’t fit
REAL WORLD 
MODEL
 Hypothesis True/False


Observation/
Reasoning/
Experimentation
Calculation

DATA


PREDICTION
Agree/Disagree
On the left side of the diagram are things and processes that are physical (real world,
observation, data)
On the right side, the objects are symbolic not physical
Step 1: Identify the aspect of the real world that is the focus of the report
Step 2: Identify a theoretical model whose fit with the model is at issue
Step 3: Identify a prediction, which is based on the model, that says what data should be
obtained if the model does have a good fit
Step 4: Identify the data that actually have been obtained by observation or
experimentation involving the real world objects the model is supposed to fit.
Step 5: Does the data agree or disagree with the model’s predictions. If not, this is
negative evidence: evidence that the model does not fit the real world and that the
theoretical hypothesis is false. If it does, proceed to the next step…
Step 6: Was the prediction likely to agree with the data even if the model does not fit the
real world? If so, the data are inconclusive in terms of whether the model fits; if not, they
are positive evidence that the model does fit and that the theoretical hypothesis is true.
Cases discussed: The model of DNA as a triple helix (as W & C constructed it) and the
double helix model; the Ptolemaic v. Copernican models of the (then known) universe;
Intelligent Design v. Darwinian evolution