should the cut-off point be? Should the cut-off be based on age alone or on work
experience? Can we reasonably aggregate the classifications based on the two
different systems?
As illustrated repeatedly in the first part of this paper, there is no simple answer to
such analytical questions. Yet every analysis covering patterns of participation must
make, even by default, a bewildering number of decisions just like this, and every
analyst might quite reasonably make a different set of decisions. Unless these
analytical compromises are clearly reported, there is a danger that debates about what
is happening in widening participation will be misinterpreted by commentators as
being about issues of substance, whereas they are, in reality, merely about differences
in making these analytical decisions.
Defining the relevant population
The next step in establishing that there should be more of any particular social group
in HE requires us to assess the prevalence of that social group in the relevant
population of those who could be participants. Unfortunately, when researching
episodes of post-compulsory learning, it is not clear what this relevant population is.
An analyst using figures for all adults is open to the charge that the inclusion of
people over the age of 50, for example, is irrelevant since so few of these are currently
participating in HE even though they represent a large proportion of the population.
Another analyst using only young adults, however, is open to the charge of presuming
that WP is only about traditional-age students, and so excluding from the analysis
precisely those to whom access could and should be widened. It is not even clear what
is the youngest age that should be considered in the population of potential HE
students. Some HE institutions admit students at age 16, or even younger on rare
occasions. This decision about age is crucial to our results, however, because the
characteristics of the birth cohorts in the UK have changed over time in terms of the
relative prevalence of ethnic and occupational groups. Using population figures for all
ages, for example, may lead one analyst to conclude that working-class students are
under-represented while an ethnic minority is over-represented in HE. Another
analyst, using the same figures for HE but using population figures only for those