London, as viewed in the data, may be seen as a discretely identified area even though
this is not the case. Any migratory changes may occur within that area but also from
outside London into it and vice versa. The problem of this ‘real’ movement and that
created by apparent moves, but really through some form of occupational mobility or
otherwise, are confounding factors that make inferences guarded and also came to be
important concerns in the construction of the multiple regression models. The later
use of the Longitudinal Study was intended as an antidote to this measurement
inaccuracy. Inferences from the data at this level should only be utilised at that level
and not at smaller spatial distributions which would make such inferences less able to
cope with the contextual features of such areas.
The first thing that one notes about the data is the basic rates of change for the
variables as a whole in the three areas defined. Mean ward level changes give an
indication of the average percentage point rates of change for the spatial areas.
The most dramatic initial changes were the increases in unemployment
(likely to be subject to many problems of measurement error) and owner occupation.
These changes would appear to fit the period from which the data was taken in which
council house sales, house sales in general and structural declines in various industries
were taking place. The large increases in unemployment are matched in each area by
decreases in working class occupations although one cannot assume that one accounts
for the other the similarity of the figures would suggest a relationship born out by a
correlation of-0.41 showing that roughly 17% of unemployment is explained by the
decreases in working class occupations for Greater London as a whole (with p less
than 1 in 10,000).
It was interesting to note a fairly clear correspondence between rises in each of the
gentrification categories for each area, becoming more pronounced in inner London,
and general decreases in the displacee variables for London as a whole, again
becoming stronger declines for the inner areas. This seemed to be taking place with
the exception of associated rises for unemployment and for lone parents (later shown
to be positively correlated with increases in professionals). It is plausible to suggest
that lone parents have become more widely distributed across socio-economic groups
which would account for these effects.
Clearly change was more pronounced in inner London. Inner London drew larger
increases in the gentrifier variables and greater reductions in the displacee variables.
This is significant even though a direct link between the two cannot be made, it shows
that the division of the data into these areal subsets does have an effect on both the
relationship between gentrification and displacement and the extent of the observed
changes in the variables. This could be for a number of reasons. The decrease in the
size of the population of inner London over the years makes the increases in the
gentrifier variables all the more significant. While working class groups sharply
dropped in inner London there was also a large mean ward increase in the number of
unemployed which might be accounted for by the large scale structural decrease in
working class employers in the centre of the city.
An analysis of the data re-aggregated into quartiles using professionals as the
grouping variable showed these effects more strongly, see table 5.2 below, but one
can lose any idea of the location of such effects (see appendix A, part two for the full
details of the quartiles). These abstract areas also formed the basis of the LS research
which utilised four areas on the basis of increasing levels of gentrification, defined as
an increase in the number of professionals above the city-wide mean.
‘inner London is defined as the following boroughs; Camden, Hackney, Hammersmith and Fulham,
Haringey, Islington, Kensington and Chelsea, Lambeth, Lewisham, Newham, Southwark, Tower
Hamlets, Wandsworth and the City of Westminster (Same as the OPCS’s classification of inner
London)
One can see the linkages between the displacee variables and the
gentrification variables in the wards when divided into quartiles. The ordering
variable is increases in the percentage points of professionals by ward for Greater
London. The data, ordered in this way, provides a demonstration of an inverse
relationship between the gentrification and displacee variables, except for the lone
parents and unemployed which always appeared to increase where gentrification
increased. There appears to be strong correspondence between increases in all
gentrification variables by quartile, as there is for working class, unskilled, ethnic,
renting and elderly; all of which decrease by ascending quartile.
Each displacee variable’s mean ward percentage point change decreases as the number
of professionals increase (apart from lone parents and unemployed). However, if one
looks at the range for working class it is possible to see that although the arithmetic
mean’s decrease over the quartiles remains relatively stable so that one cannot view
this reduction as being due to the increases in professionals. For renting it would
appear that the second quartile was the most significant ‘location’ for what might be
seen as displacement. The dramatic decreases in working class could be for a number of reasons. First, fewer people may be employed in these occupations. Second, such occupations may have
migrated from the capital to areas with something to offer for such groups. Third, part
of the impact of increasing numbers of professionals may be a displacement of
working class. In reality it is likely that a combination of these factors is responsible.
The quartile analysis was too abstract to be conclusive since the mean ward decreases
masked relatively small differences between each quartile for the displacee variables.
Strictly speaking one could not say that increases in the number of professionals was
the key factor in reducing the frequency of the displacee variables. However, it should
be noted that this is only a crude measurement and one which had little intuition
toward contextual changes. That all of the gentrification variables showed marked
increases and that five out of the seven displacee variables showed decreases can be
considered a starting point in the evidence for a process of replacement and
displacement.
- b) The location of gentrification and displacement in London
Whereas the later correlation and regression models are based upon the use of all of the
data extracted for London as a whole (see later), the analysis of the data in its
geographical distribution utilised an idea of ‘abnormal’ change more strongly. Inner and
Outer London provide artificial boundaries with which the data can be divided whereas
use of the arithmetic mean (with the additional criteria indicated in the methodology)
indicates a division of the total area into a new social geography based upon a notion of
the abnormal growth of particular characteristics. This cut off point provides a well-used
method for establishing the proxy occurrence of gentrification as an event signified by
numeric change over a discrete time period.
Gentrification definitions based upon owner occupation and educated workforce were
left out since professionals were the most accurate variable in the measurement of
gentrification activity and in terms of the variables extraction from the census. This
phase of the analysis used the relationship between gentrification (measured as the
increase above mean, of professionals and managers) and the various displacement
variables. In taking a mean growth for London this left 130 wards which could be
considered to have gentrified to varying degrees, from just above the mean to extensive
gentrification. A criteria of elimination was applied for all wards which appeared to
have gentrified but whose increase in the number of professionals had come about
because of relative decreases in the other groups in that ward – in other words
gentrification could not be seen to be occurring in wards where there were actually
fewer professionals in 1991 than 1981 (A list of these wards and their respective
changes is provided in appendix B).
In simple numbers there were more ‘gentrified’ wards in outer (79) than inner (51)
London, which is an interesting result in itself showing that, in general, the wards with
more than average growth were expanding more in the outer than inner areas of London.
However, if one takes these numbers of gentrified wards and express them as a
percentage of the total number of wards in each area one finds that similar ward areas of
inner and outer London had been gentrified (17.1% and 17.2% respectively). This shows
that the concentration and proportion of gentrification in inner London is actually no
more than that of the outer area. On the other hand, if one looks at the number of
‘gentrified’ wards in a borough like Wandsworth one can see that fully 21 out of 22
wards had gentrified to some degree showing an uneven distribution of gentrification in
the larger areas that comprise London. The social and political centrifugal forces that
shape this distribution are considered further in chapter nine.
Key locations were also observed. In particular the riverside in the Docklands areas
appeared to be heavily gentrified, a result consistent with the other views of that area
(Hall and Ogden, 1992). More unexpected locations were also observed. South east
London revealed a number of wards in which gentrification had taken place and outer
London, as previously noted, had seen dispersed but widespread gentrification by
professionals and managers. Areas that had been further gentrified like Richmond,
Kingston and Blackheath highlighted places that would have been excluded from an
analysis which used a criteria of exclusion since their starting percentages were above
the mean. In other words, areas which were already gentrified or established middle
class areas could be gentrified even further.
