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6. USING CENSUS FOR SMALL AREA ANALYSIS
6.1 VOLUNTEER RATES FOR SYDNEY, SELECTED CHARACTERISTICS(a) – 2006 GSS AND 2006 CENSUS
Due to the sampling error for GSS estimates for Sydney, rate ratios were not found to be significantly different from each other, therefore differences in volunteering between different demographic groups cannot be identified at this level of geographic area. The exception is for the unemployed, which was significantly lower than those employed or not in the labour force (the rate for GSS and Census for unemployed was not significantly different).
Although differences within groups cannot be identified, the estimates for the rate ratios tend to lie within the bounds described in Section 4 (i.e. the GSS volunteer rate is 1.5 to 2.0 times larger than the Census volunteer rate). This suggests the Census can be used to compare differences in the propensity to volunteer at lower geographic regions.
Differences in rates between SLAs were consistent with differences in the predictors of volunteering that were previously discussed in Section 5. Therefore, differences between SLAs in volunteering rates can be compared with reasonable confidence, even though the absolute level of volunteering will be understated within SLAs.
Table 6.2 presents the volunteering rates for the eight SLAs within Sydney – those with the four lowest and four highest volunteering rates. All SLAs are presented in Appendix E.
6.2 VOLUNTEER RATE, SYDNEY SLAs(a) – 2006 CENSUS
Fairfield East has the lowest volunteer rate at 7.9% followed by Bankstown North-East (9.0%). Ku-ring-gai has the highest rate (29.2%), followed by the Blue Mountains (27.1%). This compared to 16.8% for all of Sydney.
Table 6.3 presents the population profiles for selected SLAs to allow for comparison to groups of interest.
The most notable difference for these SLAs can be seen in proficiency in spoken English. The Blue Mountains had the highest percentage of people who spoke English only (95.0%), with Ku-ring-gai (80.8%) being close to the total adult Australian population (82.3%). In contrast, Bankstown North-East (23.0%) and Fairfield East (25.4%) had much lower percentages of people who spoke English only.
Another large difference between SLAs can be seen across highest level of educational attainment. The largest percentage of people who had completed an Advanced Diploma/Diploma or above could be seen in Ku-ring-gai (60.6%), followed by the Blue Mountains (38.3%). These two SLAs were above the average for Australia (28.2%). Conversely, Bankstown North-East and Fairfield East had below average percentages of people who had completed an Advanced Diploma/Diploma qualifications or above (21.3% and 14.7%).
Both proficiency in spoken English and highest level of educational attainment were found to be strong predictors of volunteering in Section 5. Family composition was another strong predictor; however the variations between the selected SLAs for family type were much smaller than those for proficiency in spoken English and highest level of educational attainment.
Bankstown North East and Fairfield East had greater percentages of people in family compositions (such as those with dependent children under 15 years) that are more likely to volunteer compared with the Blue Mountains and Ku-ring-gai.
Differences were also found in other demographic characteristics that predict volunteering, namely age, social marital status and part-time employment status. However, while these differences were smaller than for proficiency in spoken English and highest level of educational attainment, they were in the direction that would be expected. For example, being employed part-time was a positive predictor of volunteering and a greater percentage of people were found to be employed part-time in the selected SLAs with higher volunteer rates compared with the Australian average and the selected SLAs with lower volunteer rates.
Tables 6.4 and 6.5 show that for SLA comparison the Census can be used to compare differences in the propensity to volunteer between SLAs where there are large differences in volunteer rates. These results suggest that the propensity to volunteer involves interactions between a number of the demographic and socio-economic characteristics identified as strong predictors of volunteering.
6.3 PROFILE OF POPULATION, SELECTED SYDNEY SLAs(a) – 2006 CENSUS
6.4 PROFILE OF VOLUNTEERS, SELECTED SYDNEY SLAs(a) – 2006 CENSUS
6.5 VOLUNTEER RATES, SELECTED SYDNEY SLAs(a) – 2006 CENSUS
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