The Social Lab is a centre for social indicators research at IPS. It was established in 2013. The centre conducts research on social perceptions, attitudes and behaviours in Singapore using the most robust standards in survey methodology and statistical analyses. Researchers also collect and analyse panel data to complement cross-sectional and time-series data.
The changing social landscape of Singapore means we need reliable data and high-quality analysis to track and evaluate shifts in demographic trends and adaptive processes. Insights gained through objective social science research can enhance our understanding of social attitudes and resilience, and knowledge of emerging socio-economic challenges confronting Singapore. As the sense-making arm of IPS, Social Lab seeks to work closely with researchers from government and academia to support informed decision-making and policy formulation for a new multicultural setting. Its long-term aim is to be a national resource centre for longitudinal data.
Social Lab is headed by IPS Senior Research Fellow Dr Mathew Mathews and Adjunct Senior Research Fellow Mr Freddy Hong. Its Academic Adviser is Associate Professor Tan Ern Ser from the Department of Sociology, National University of Singapore.
INTEGRATED RESEARCH SOLUTIONS
IPS Social Lab works closely with our clients to plan and determine the research goals of each project. Our studies are guided by robust methodological designs and advanced statistical principles and analyses. We have the capability to collect data using multiple platforms depending on the complexity and needs of the research. We constantly explore new technologies to enhance fieldwork efficiency and ensure data integrity.
IPS Social Lab manages the entire lifecycle of a research undertaking. This includes the distribution of research findings and data to relevant stakeholders, and the management of communication tools like press releases, where necessary. Today, Social Lab is the first and the only agency among all universities in Singapore that has attained the ISO certification for fieldwork operations.
EMPHASIS ON DATA QUALITY CONTROL
IPS Social Lab emphasises data integrity and quality control. Quality control in survey research ensures that the survey results are accurate, reliable and valid. Our quality control measures span the entire survey research process.
In general, sampling methods can be differentiated between probability sampling and non-probability sampling. In probability sampling, every element in the population has a known and non-zero probability of being selected into the sample. An example is random household sampling, where each household unit has a known and equal chance of being selected. In non-probability sampling, participants are selected into the sample in a non-random manner, where each element has an unknown probability of being selected. Some examples include quota sampling, snowball sampling and convenience sampling. The choice of sampling method depends on the goals of the research, its context as well as target respondents and the resources available. These factors should also inform choices in the mode of data collection, e.g., face-to-face interviews, Computer Assisted Telephone Interview (CATI), or online surveys.
Interviewers that conduct surveys are adequately trained, especially in terms of their behaviour (e.g., tone, verbal language, body language) when executing the surveys, which plays a significant role in affecting how respondents answer questions. We go a step further to conduct onsite validation and fieldwork observations to ensure that interviewers perform to our required standards. Data verification is also performed to ensure that respondents provided true and accurate data. This is performed by a separate and independent team to ensure objectivity in the process as well as detect and reject any fraudulent data.
IPS applies advanced multivariate data science in all our research. The analyses range from top-line visualisation, to variable-centred analysis, and person-centred studies. Such analysis is adjusted to fit the research objective and combines the latest techniques in survey research.
To make sense of social attitudes, values and behaviours, IPS Social Lab uses a combination of data from individuals, households and their neighbourhoods. By doing this, we integrate the survey data with broader socio-environmental factors. The Geographic Information System (GIS) is the lynchpin to this “smart data” movement, and serves as the foundation of all panel and cross-sectional studies. IPS Social Lab has had notable successes in using GIS for the analysis of crime, residential ethnic clustering, and sentiments towards governance. For example, the study on neighbourhood resilience proposes recommendations to policy makers to reduce emerging fault lines in certain planning areas.