LOS REQUERIMIENTOS DIARIOS DE NUTRIENTES PARA TERNEROS
2.2. Procesos entéricos causados por bacterias en terneros
2.3.1. Escherichia col
The different socio-economic make-up of the two cities could also be seen to influence their valuation patterns. The two cities are characterised by dissimilar levels of income, employment and education (see Table 3.1), all of which could influence the extent to which cultural resources are considered important. Furthermore, socio-economic and demographic background varies within cities as well as between them. It was therefore necessary to explore what variables associated with the demographic and socio-economic background of respondents explained a higher or lower valuation of cultural resources. Similarly to what explained in relation to the
114
model presented in Table 4.8, Negative Binomial Regression was chosen as the preferred statistical technique for this investigation.
However, Logistic Regression was also used for a preliminary exploration of what factors made respondents more likely to assign “some” value to culture and Leisure, as opposed to none. Therefore, the scores assigned to the Culture & Leisure bundle were initially recoded into a binary variable of 0 and 1. Explanatory variables included age, gender, income, education qualifications, the presence of children in the household and employment. In the case of the latter, the original variable was recoded to reflect the amount of free time participants have, in order to assess whether this had any influence on preferences for cultural resources. Free time was coded as low, moderate and high, depending on whether participants were, for example, in full time employment, part-time or retired/unemployed. While the recoding into three categories was far from ideal, and a differentiation between, for example, retired and unemployed individuals would have been desirable, the low frequencies in each sub-category when considered individually would have made any analysis impossible. The coding for all other variables was maintained as described for Table 4.8. The results of this initial investigation are reported in Table 4.9.
115
Table 4.9: Results of logistic regression analyses exploring factors that made respondents more likely to score Culture & Leisure some as opposed to zero tokens.
Dundee (n=663)
Edinburgh (n=613)
Variable OR Sig OR Sig.
Gender (ref. Female)
Male
1.09
0.412
0.93
0.825
Children (ref. No)
Yes
1.82*
0.036
1.56ˆ
0.058
Age (ref. 18-24)
25-34
2.27
0.656
0.98
0.915
35-44
0.71
0.320
0.49
0.248
45-64
0.57
0.561
0.88
0.263
65+
0.78
0.365
1.28
0.750
Income (ref. < £20,000)£20,000 -
40,000
0.89
0.717
1.42
0.416
£40,000 –
60,000
0.92
0.829
1.51
0.425
£60,000+
1.88
0.195
0.79
0.680
Qualifications* (ref. Highest)Low
0.53*
0.044
0.68*
0.013
Medium
0.92**
0.009
0.65**
0.009
High
0.40**
0.002
0.41 ˆ
0.066
Free Time (ref. Low)Moderate
0.86
0.656
1.08
0.872
High
1.12
0.804
0.78
0.636
Model Fit
Omnibus Test 15.525, Sig: .001 22.748, Sig: .000116
As can be seen in the table, the presence of children in the household appears to be linked to the participants’ likelihood to allocate some value to culture and leisure, rather than zero, in both cities. This result was statistically significant across both case studies, and can be interpreted as the result of the inclusion in the culture and leisure bundle of some resources that are typically directly important to parents, such as sports and other extra-curricular classes for children and public libraries. The other variable that was found to be significant in both cities was the level of educational qualifications. More specifically, participants with qualifications from an undergraduate degree upwards appeared to be more likely to attribute some tokens to culture and leisure than respondents with lower qualifications. The results were found to be consistently significant for all the three observed categories, and demonstrated a link between education levels and a higher value being attached to culture and leisure. Therefore, this could provide an initial explanation for the higher overall score obtained by Culture & Leisure in Edinburgh, as the average levels of educational attainment are higher than those in Dundee. In order to widen and deepen the analysis, negative binomial regression was again utilised, this time to identify what factors made respondents more or less likely to assign a higher value to culture & leisure. The results of this analysis are presented in table 4.10.
117
Table 4.10: Results of negative binomial regression analyses exploring factors that made respondents more likely to score Culture & Leisure more highly.
Dundee (n=663)
Edinburgh (n=613)
Variable OR Sig OR Sig.
Gender (ref. Female)
Male
1.14
0.412
1.30
0.152
Children (ref. No)Yes
0.57***
0.001
0.39***
0.001
Income (ref. < £20,000)£20,000 –
40,000
1.65
0.155
3.34***
0.001
£40,000 –
60,000
0.74
0.251
3.23***
0.001
£60,000+
0.93
0.799
2.37**
0.010
Age (ref. 18-24)25-34
0.98
0.963
1.28
0.457
35-44
0.75
0.915
1.12
0.739
45-64
0.96
0.444
1.32
0.387
65+
0.80
0.499
9.62**
0.001
Qualifications* (ref. Highest)No Qual. & 1
0.66
0.253
0.64ˆ
0.062
2
1.58
0.156
0.60ˆ
0.054
3,4,8
0.85
0.412
0.75
0.249
Free Time (ref. Low)Moderate
1.29
0.228
1.67ˆ
0.064
High
1.76
0.216
1.93*
0.045
Economic Activity (ref. active)Inactive
1.13
0.253
2.81**
0.008
Model Fit Omnibus Test Deviance BIC 11.994, Sig: .052 1.037, Poisson: 1.221 5114.839, Poisson: 5732.982 300.705, Sig: .000 0.643, Poisson: 0.437 5318.384, Poisson: 5377.214
119
The first feature to be immediately evident from the table above is how background variables appear to be more able to explain higher scores in Edinburgh than in Dundee. In the latter case, only the presence of children resulted to be significantly linked to the score obtained in the questionnaire. However, while having children in the household seemed to make respondents more likely to assign some value to culture and leisure rather than zero, it also resulted to reduce the likelihood of higher scores. The interpretation of this apparent contradiction could be that some features of culture and leisure represent a resource for parents (for example libraries and community classes for children), which explain their reduced propensity to score Culture & Leisure a zero. At the same time, however, they prefer to “save some tokens” for resources of more immediate importance to them, such as school catchment or, in the case of Dundee in particular, proximity to family for childcare reasons. The result is a likely score above zero, but below average. This initially counter-intuitive relationship was also observed in the Edinburgh sample.
For Edinburgh, the valuation of cultural resources was found to be linked to numerous background variables. The importance of education observed in the previous regression was confirmed here, with lower qualifications being statistically linked to lower than average scores. In addition, all three income brackets included in the analysis were observed to be significantly associated with higher scores when compared with the lowest bracket (< 20,000). The strength of the relationship can be seen to lessen with growing income, the strongest effect being observed with incomes between twenty and forty thousand pounds per annum. One possible explanation for this non-linear relationship is that an income above twenty thousand arguably offers a better possibility to have some disposable income for leisure activities, compared with those from the lower income bracket. However, above a certain threshold the effect of the extra disposable income diminishes, and households with an income of around forty thousand pounds per annum have similar opportunities to wealthier ones to engage with cultural and leisure activities. Another possible interpretation would be that the wealthiest participants do not rely on the ‘local’ provision of cultural resources and are able to participate in cultural activities elsewhere in the city, or in other cities such as Glasgow and London.
The availability of free time was also found to be strongly related to higher than average scores. In this instance, the employment status variable was recoded to reflect economic activity, and the economically inactive category was observed to be more likely to assign higher scores. However, the previous regression found no significant link between free time and the chance of
120
a zero score. This seems to suggest that participants invested some value in cultural resources regardless of the amount of free time they had to enjoy them. In other words, while direct use emerged as an important determinant of how highly cultural resources were valued, the desire for their availability in a residential location cannot be explained without taking non-use elements of valuation into consideration. These observations will be reflected upon further in chapter 6, and will contribute towards answering RQ 4.
Finally, respondents over the age of sixty-five in Edinburgh emerged as more likely to score culture and leisure highly than younger participants. This association was verified even after accounting for the amount of free time respondents had. This finding is important, as an issue of collinearity may arise in terms of the possible correlation between retirement age and a higher availability of free time.
4.4 Conclusions
Drawing from the results of the first two exercises in the questionnaire and on insight from the focus groups, this chapter has investigated the importance assigned to cultural resources in the two case studies. Addressing research question 1, the relative value attributed by participants to the Culture & Leisure bundle compared to four other residential location attributes was assessed, and the results were presented in the context of the qualitative data gathered during the earlier stage of this research. As a result, the two case studies were observed to differ in a number of ways.
The most notable difference was the high valuation given to culture and leisure in Edinburgh, in contrast with Dundee, where cultural resources were ranked and scored last out of the five location attributes. Another key dissimilarity was that, while in Edinburgh the insights derived from the quantitative data confirm what emerged in the focus groups, the results from the Dundee sample appear to be decidedly dissonant. The major role in the city’s life attributed to the local cultural sector by participants to the interviews and focus groups was not matched by the quantitative valuation that emerged from the survey.
Two possibly inter-related explanations have been suggested for these diverging results. The different demographic make-up of the two cities could explain the higher valuation of culture in Edinburgh, as one of the main features attracting the more cosmopolitan population of this city
121
is its vibrant cultural life. As a result, a larger proportion of residents will be people who value and appreciate cultural resources in the first place, thus leading to a high valuation. Secondly, the possibility that the two cities might have two different dominant notions of what culture is and what its functions are was presented. This possibility in particular was related to the observation that respondents in Dundee may have assumed a narrower definition of culture, and as a result they may have only considered museums, heritage resources and performing arts in their scoring process. In order to verify the correctness of this hypothesis, the Culture & Leisure bundle has to be disaggregated, to investigate how cultural preferences are distributed across its main components and what notions of culture are dominant in the two cities. This process will contribute towards research question 2 and the main aim of the research, and the results are presented in the following chapter.
Finally, the relationship between demographic and socio-economic variables and the valuation patterns in both cities was investigated. Once again, the two case studies were found to differ. In Dundee, background variables were found to have no significant influence over the importance attributed to cultural resources, with the exception of the presence of children in the household and, to a limited extent, the respondent’s level of education. Conversely, in Edinburgh higher income and education, age over sixty-five and the availability of free time were all found to be significantly correlated with higher score being attributed to culture and leisure
122