Qualitative_data_analysis

PRODUCING AN ACCOUNT 263
consistent with telling the time by the speaking clock. We are both referring to a
common-sense view of time, not one which might be relevant psychologically or in
astrophysics. Incidentally, if I was navigating at sea and dependent on satellite
signals to determine time, I would be better relying on astrophysics than on the
common sense view (Hawking 1988:33). I am also assuming a common frame of
reference, such as British Summer Time. In other words, in checking validity I have
to consider whether my concept of time is consistent with that employed by other
measures. If my concept proves inconsistent—for example, if I have forgotten to
switch to British Summer Time—then I may again doubt the validity of my
measuring instrument. Of course, I could instead doubt the validity of British
Summer Time, but such immodesty would be unbecoming. We have to accept the
authority of established concepts unless we have very good reasons to do otherwise.
This fit (or lack of it) between the concepts we are using and previously established
and authoritative concepts is called ‘construct’ validity.
Finally, I can check that the two measurements are consistent. If my measurement
does prove consistent with the measurements obtained from other indicators, then I
can be confident that my own instrument is a valid measure. This fit (or lack of it)
between measures provided by different indicators is called ‘criterion’ validity. In the
case of the speaking clock, I have such confidence in its efficacy as a measure of time
that I would not seek any further confirmation from other sources. The situation in
social science is usually less clear-cut, because we cannot obtain established
indicators through a simple phone call, and where indicators do exist they are often
less authoritative. Think only of the problems in measuring class, intelligence,
power, status or job satisfaction. Nevertheless, where we can find a reasonable fit
between our own measurements and those derived from established indicators, we
can have more confidence that we have devised a valid measure of the concept we
are interested in.
In qualitative analysis, where we are often trying to break new ground and create
new tools of analysis, we are more likely to be interested in the ‘face’ and ‘construct’
validity of our account. In the absence of satisfactory ‘measures’ achieving
confidence through consistency in measurement is a less likely prospect. The ‘face’
validity of our account turns on the fit between our observations and our concepts,
and this is something we can be more confident about. The whole thrust of
qualitative analysis is to ground our account empirically in the data. By annotating,
categorizing and linking data, we can provide a sound empirical base for identifying
concepts and the connections between them. Other interpretations and
explanations of the data may be possible, but at least we can be confident that the
concepts and connections we have used are rooted in the data we have analysed. But
how can we create a similar degree of confidence in others?