Qualitative_data_analysis

236 QUALITATIVE DATA ANALYSIS
Even if we have confronted all the evidence, we may still ‘misinterpret’ our data.
We can see the words ‘let him have it’ as either an encouragement to pass over the
gun, or as an incitement to use it. If one of these interpretations is correct, the other
is wrong. Supposing Bentley spoke those words, what did he mean by them? Even if
Bentley said he meant Craig to hand over the gun, can we believe him? We cannot
know for sure, because this interpretation was clearly so much more in his own
interest than the other. We would expect Bentley to lie if necessary to protect
himself from the gallows.
In interpreting this case, we are liable to make one of two errors. If we believe
Bentley told the truth, we may make an error in accepting his explanation. If we
believe Bentley lied, we may make an error in rejecting his explanation. Whichever
interpretation we choose, we run the risk of error. Suppose we decide to reduce the
risk of error by assuming that Bentley would lie to protect his own interest, though
not otherwise. In trying to reduce the probability of error in one direction, we
merely increase it in another. Once we suspect that Bentley might lie to protect
himself, we increase the risk that we will mistakenly reject his account.
If the interpretation we choose is at odds with what actually happened, we
‘misinterpret’ the data. When does an interpretation become a ‘misinterpretation’?
There may be some reluctance to admit the possibility of ‘misinterpreting’ data, on
the grounds that there is no such thing as an ‘objective’ account—we’ll never know
what really happened. All we have are different interpretations, and these are
inevitably subjective. This assumes that each interpretation may have its own
merits, but none can claim superiority over the rest—one interpretation is as good
as another. The problem with this approach is that it eliminates the possibility of
error, and therefore of making and learning from our mistakes. It eliminates
progress and reduces social research to a useless exercise in story telling. While we do
want to ‘tell a story’ about our data, it is not just any story, but one which we can
claim is valid. My dictionary defines ‘valid’ as ‘sound’, ‘defensible’, and ‘wellgrounded’
and despite the more technical interpretations of validity in social
science, this is as good a definition as any. A valid account is one which can be
defended as sound because it is well-grounded conceptually and empirically. If it
doesn’t make sense, then it cannot be valid. If it fails to account for the data, then it
cannot be valid.
To produce a valid account, we need to be objective. This refers to a process, of
which a valid interpretation is the product. Being objective does not mean being
omniscient—it doesn’t mean we can know ‘what really happened.’ It means
accepting the canons which govern rational inquiry as a basis for realizing
conclusions which are reasonable. It means taking account of evidence without
forcing it to conform to one’s own wishes and prejudices, and accepting the