This is Ireland, Part 2, was released this morning. It provides macro-level (national and county) results for a broad set of socio-economic data: labour force, occupation, education, health, social class, travel pattern. There are some maps at ED level for unemployment and a couple of occupational sectors, but the full ED and Small Area data set will not be released until later in the summer. At that stage, we’ll be able to get a much more detailed sense of how the economic crash has played out socio-economically at a local scale.
In this post, I’m just going to concentrate on the socio-economic group and class results. Analysing these at a county level is problematic because aggregation effects mask the highly variable way in which these play out locally, nevertheless we can see the broad pattern changes.
Socio-economic grouping classifies the entire population into one of ten categories based on the level of skill and educational attainment of their occupation (inc. those at work, unemployed or retired, with dependents classed on the basis of whom they are deemed to be dependent). There has been growth between 2006-11 (see Figure 1) at the higher, more skilled end of this classification, with increases in employers/managers, higher professional, lower professional and non-manual, whilst those dependent on manual work have declined (in line with job losses in related sectors such as construction). Moreover, there is a broad spatial pattern to the data with a greater proportion of the highest two categories in and around Dublin reflecting the higher proportion of FDI and public sector jobs around the capital (see Figure 2).
There are also some marked gender contrasts in socio-economic group (Figure 3), with strong differences in the gender profile of some classes. For example, men make up a much stronger proportion of manual, farmers, agricultural workers, self-employed, and are marginally more likely to be employers/managers, higher professional, semi-skilled and unskilled. Women make up a strong proportion of lower professional, non-manual and other. Whilst the balance of the top two classes of employers/managers and higher professional are getting better, it seems that a glass ceiling does still exist.
Figure 1
Figure 2
Figure 3
The socio-economic group data is used as the basis for assigning households into a social class, based on almagmating occupations with similar skill sets together to produce seven classes: professional workers, managerial and technical, non-manual, skilled manual, semi-skilled, unskilled and other. Figure 4 shows the distribution of social class by local authority. Clearly the standout LAs are in the cities. DLR has a disproportionate number of professional and managerial/technical classes, whereas Cork City, Waterford City and Limerick City have low rates compared to their surrounding hinterlands, reflecting the suburbanisation of professional/managerial labour.
Figure 4
Rob Kitchin
Ireland after NAMA 
June 28, 2012
Census 2011: Socio-economic group and class
Posted by irelandafternama under #Commentaries, Data | Tags: census, gender, Geography, social class, socio-economic group |Leave a Comment
This is Ireland, Part 2, was released this morning. It provides macro-level (national and county) results for a broad set of socio-economic data: labour force, occupation, education, health, social class, travel pattern. There are some maps at ED level for unemployment and a couple of occupational sectors, but the full ED and Small Area data set will not be released until later in the summer. At that stage, we’ll be able to get a much more detailed sense of how the economic crash has played out socio-economically at a local scale.
In this post, I’m just going to concentrate on the socio-economic group and class results. Analysing these at a county level is problematic because aggregation effects mask the highly variable way in which these play out locally, nevertheless we can see the broad pattern changes.
Socio-economic grouping classifies the entire population into one of ten categories based on the level of skill and educational attainment of their occupation (inc. those at work, unemployed or retired, with dependents classed on the basis of whom they are deemed to be dependent). There has been growth between 2006-11 (see Figure 1) at the higher, more skilled end of this classification, with increases in employers/managers, higher professional, lower professional and non-manual, whilst those dependent on manual work have declined (in line with job losses in related sectors such as construction). Moreover, there is a broad spatial pattern to the data with a greater proportion of the highest two categories in and around Dublin reflecting the higher proportion of FDI and public sector jobs around the capital (see Figure 2).
There are also some marked gender contrasts in socio-economic group (Figure 3), with strong differences in the gender profile of some classes. For example, men make up a much stronger proportion of manual, farmers, agricultural workers, self-employed, and are marginally more likely to be employers/managers, higher professional, semi-skilled and unskilled. Women make up a strong proportion of lower professional, non-manual and other. Whilst the balance of the top two classes of employers/managers and higher professional are getting better, it seems that a glass ceiling does still exist.
Figure 1
Figure 2
Figure 3
The socio-economic group data is used as the basis for assigning households into a social class, based on almagmating occupations with similar skill sets together to produce seven classes: professional workers, managerial and technical, non-manual, skilled manual, semi-skilled, unskilled and other. Figure 4 shows the distribution of social class by local authority. Clearly the standout LAs are in the cities. DLR has a disproportionate number of professional and managerial/technical classes, whereas Cork City, Waterford City and Limerick City have low rates compared to their surrounding hinterlands, reflecting the suburbanisation of professional/managerial labour.
Figure 4
Rob Kitchin
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