Difference between revisions of "Project Groups"
Yjliu.2017 (talk | contribs) |
(logo) |
||
Line 146: | Line 146: | ||
<div style="text-align:center;"> | <div style="text-align:center;"> | ||
[[Group05_Overview|Group05: Social Stratification Mappers ]] | [[Group05_Overview|Group05: Social Stratification Mappers ]] | ||
− | [[File: | + | [[File:SM2.png|230px]] |
</div> | </div> | ||
|| | || |
Revision as of 18:21, 10 June 2018
|
|
|
|
|
Project Groups
Please change Your Team name to your project topic and change student name to your own name
Project Team | Project Title/Description | Project Artifacts | Project Member |
---|---|---|---|
Project title: Provide eyes catching title. However, it should reflect the content or/and the focus of your project Abstract The abstract should not be more than 350 words. |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Exploring Inequality’s Geographic Dimension Across Neighbourhoods in Singapore: Its Driving Forces & Touch Points Amidst the recent debate over growing social inequality in Singapore such as the distinct clustering of elite schools and varying access to resources, the dangers of hardening social mobility can pose as a threat for a culturally diverse nation that has upheld its values of social cohesion and racial harmony. In bridging social divide, Singapore has put in place various programmes in the community and schools to nurture shared experiences and promote inter-communities mixing. More recently however, inequality was highlighted to have a geographic dimension even for a densely populated city like Singapore. Using geospatial techniques in R, the dashboard serves to visualise whether geography is an important driver of inequality, by mapping the extent of social inequality and availability of common spaces across neighbourhoods. This will be done in three approaches. First, we will analyse whether there exist clusters that could point towards social inequality and whether this is more pronounced in certain neighbourhoods, based on ethnic mix, age composition, and housing type. This will be done using spatial points pattern analysis including distance-based and density-based measures. Next, using the Hansen Accessibility Model, we will map out the available touch points within neighbourhoods that could facilitate social mixing, such as the ease of access to common spaces, amenities and opportunities for choice of education. This is because an important aspect of social inequality is having reasonably fair access to different resources. Lastly, we will move into solutioning and explore possible spaces such as vacant state land where upcoming public amenities can be best placed to optimise social class mixing. |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
| ||
Project title Abstract |
|