Grounded Theory and Disability Studies: An Investigation Into Leg ...

Revolutions (Kuhn, 1996), which discussed the nature of artificiality and paradigmatic theory development. The publication of The Discovery of Grounded Theory also came only 5 years before Poppers’s concluding work on this issue, Objective Knowledge (Popper, 1979). In this, he argued that the scientific process of induction is itself a progression of developing from one problem (P1) to another (P2) through error elimination in an analysis of evidence (EE) and the development of a new tentative theory (TT). This is discussed in greater detail in the context of the framework of analysis in chapter 4.

Thus, it was not wholly unsurprising that a model working towards a notion of objectivity, of continually testing and reworking theories with the understanding that they could be refined over a period of field studies, managing to be empirical but not positivist at the same time, should gain credibility in this era. However, what was perhaps most significant about the early development of grounded theory was its system of describing social phenomena through abstract notions in the same manner as formal narratives of data. In doing so, grounded theory gained credibility as a more structured alternative to looser ethnographic and anthropological studies, which required visibly less rigorous testing of evidence (Geertz, 1989).

In terms of data gathering, Glaser and Strauss also arguably pioneered two general values of data collection and coding in this era. The first was that ‘All is data’—that is to say, anything could be seen as data within the coding of a study, no data should have priority over any others, and no data needed to be rejected before their value to the whole study could be fully assessed. Thus, data that were gathered early in a study and that initially did not seem important to the investigation as a whole were to be kept and compared to new findings at some later stage of the research process or when rereading raised further testable ideas. As Glaser later wrote on this notion,

‘All is data’ is a [well-known] Glaser dictum. What does it mean? It means exactly what is going on in the research scene is the