Validation- Chapter 10

Determining what validation for qualitative research is is the heart of the issue in this chapter; and upon reflection is really not as contentious as it was presented at the start of the chapter. If we view validation of data as double-checking, corroboration, verifying, then it is as "easy" to do as quantitative or statistical validation. In fact, it should be easier. Since the data validation process precedes conclusion, which should be validated as well, we are not evaluating the interpretation of data, but the accuracy of the information gathered. While Wolcott doesn't find much purpose for validation (Creswell, pg 295), I feel there is importance in ensuring that (what I call) qualitative added-value factors are present in the data (lucid transferable terminology, assurance of meaning, trustworthiness, thick description, etc.). I don't agree with the concept that that validation is against the spirit of qualitative research, as is implied in Wolcott, but I agree that the nit-picking of models of many of the others is more about semantics and reflexive personal interpretations than about the broader spirit of qualitative research.
For me, the questions raised about data validation specifically for Grounded Theory approach provide a good guide as to how to manage this aspect/phase of my own project.
The most relevant issue for me seems to be about making certain that differences in interviewee's verbiage=the equivalent phenomenon. This will require member checking and peer review as the most effective method.