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Is it possible to evaluate the risks regarding social inclusion in a municipality where this risk needs to be measured periodically with a definition of critical points, identifying those which are managed well and those which require further action?
Yes, these tasks can be performed using Qualitative Engine. We are proposing a specific model for the calculation of the degree of social inclusion for a municipality. Within this, as you can see in the representation of the model, there are partial indicators defining areas or critical points.
Social inclusion
Social inclusion (Zeros)
Economic area (Direct)
1-Gross disposable household income index (Direct extreme modified)
2-Rate of persons using social bodies (Inverse extreme)
3-Perception of economic precariousness (Inverse extreme)
4-Fee for persons without subsidies/benefits (Inverse extreme)
Employment area (Direct)
5-Unemployment rate (Inverse extreme)
6-Rate of part-time contracts (Inverse extreme)
7-Perception of the difficulty to find work (Inverse extreme)
Training area (Direct)
8-Rate of population without obligatory schooling (Inverse extreme)
9-Rate of population with university studies (Inverse extreme)
10-Rate of illiteracy (Inverse extreme)
11-Rate of population with knowledge of Catalan (Inverse extreme)
Socio-health area (Direct)
12-Perceived morbidity (Inverse)
13-Persons with addictions (Inverse)
14-Persons with infectious diseases (Inverse)
15-Index for superannuation (Inverse average indeterminate)
16-Index for senile dependence (Inverse average indeterminate)
17-Index for persons with a disability (Inverse extreme modified)
Residential housing area (Direct average indeterminate)
18-Population owning residence (Inverse extreme)
19-Rate of residences under 50m2 (Inverse extreme)
20-Average number persons/household (Inverse extreme)
21-Rate of households with all members over 65 (Inverse extreme)
Residential environment area (Direct high indeterminate)
22- Perception of degradation of the urban environment (Inverse extreme)
23-Rate of residences lacking household equipment (Inverse extreme)
24-Rate of residences with external noise (Inverse extreme)
25-Rate of residences with pollution or bad odours (Inverse extreme)
26-Rate of residences with poor connections (Inverse average indeterminate)
27-Rate of residences suffering delinquency/vandalism (Inverse average indeterminate)
Relational area (Direct average indeterminate)
28-Population density (Inverse extreme)
29-Perception of family conflictiveness (Inverse average indeterminate)
30-Rate of one-person households (Inverse average indeterminate)
31-Degree of participation with social bodies (Inverse average indeterminate)
32-Perception of the degree of social conflict (Inverse extreme modified)
Social quality area (Direct average indeterminate)
33-Rate of persons without documentation in order (Inverse average indeterminate)
34-Total rate of foreigners (Inverse average indeterminate)
35-Rate of persons in prison (Inverse average indeterminate)
36-Rate of participation in elections (Inverse average indeterminate)
In addition, we have the same model separated by indicators, in order to be able to analyse the areas more widely and precisely. Here is an example of an analysis using the model:
Inclusión social
(TO SEE IN Q-ENGINE)
USER: Demo3EN
PASS: Q-engine3EN
GESTIÓ DE
CONEIXEMENT SOCIAL
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