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Article: 2023 Joint Statistical Meetings in Toronto
Released on:21/8/2023 10:30 AM
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​​​ 2023 Joint Statistical ​Meetings in Toronto​​

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M​RSD​​​​​ participated in the Joint Statistical Meetings (JSM) in Toronto, Canada from 5 – 10 August 2023. The JSM is the largest gathering of statisticians and data scientists held in North America. With more than 5,000 attendees including 1,000 students from 52 countries involved, the JSM provided a unique platform for statisticians around the world to exchange ideas and explore opportunities for potential collaboration. Participants took part in engaging dialogues on statistical applications, methodology, and theories. Topics on expanding the boundaries of statistics such as with the use of data science and analytics were also discussed. ​

The JSM programme outline includes poster presentations, roundtable discussions, as well as professional development courses and workshops. Our MRSD team participated in two poster presentations.​

Our first poster presentation, titled ‘Labour Force Statistics: Social Media Content Creators’, highlighted how the pandemic has introduced social media content creators as an increasingly attractive occupation. We explained that this phenomenon could be attributed to factors such as the flexibility of this form of work, the readily available platform for self-expression and passion, and it being a viable source of additional income for the younger generation, also known as Generation Z (Gen Z). On top of that, the rise in active users and daily average time spent on social media in Singapore presents an opportunity for many up-and-coming Gen Z content creators to gain access into this industry. Recognising this new wave, the government has invested more effort into providing training opportunities for content creators to improve relevant skills such as content marketing, audience engagement, and data analytics.

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During this poster sharing session, we managed to have a fruitful discussion with a former employee from Twitter—now known as X—about how the marketing industry is evolving with the increasing trend of social media content creators. He agreed that influencer marketing agencies would be an interesting field to investigate. In addition, as the for​mer X employee did not have the chance to work with related data pertaining to Singapore, he was grateful for our sharing, noting that he has always been interested in learning about the content creator industry in Singapore.

The next poster presentation was on ‘Augmenting Labour Force Survey (LFS) Analysis with Administrative Data’. We explained how administrative data could be utilised to improve the pre- and post-survey stages in our LFS data collection. For instance, merging administrative data in the pre-survey stage can help alleviate the survey burden on both respondents and survey interviewers by reducing the time needed to complete the surveys and validate demographic data respectively. In the post-survey stage, the availability of administrative data would help process data more efficiently by increasing data completeness and improving data quality.​

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On this topic of LFS, we had an insightful exchange with our global counterparts from the Bureau of Labour Statistics and Census Bureau about how the LFS is conducted in the United States. They also shared about their own challenges faced when using administrative datasets that may not be regularly updated, resulting in potential data inaccuracies and inconsistencies. Learning about these limitations was helpful for us as it prompted us to reflect on our own methods and processes back home and be prepared to identify new solutions to tackle these challenges should they surface.

The JSM conference was all in all a great opportunity for the team to gain exposure to new statistical concepts. Conversing with the various participants from across the globe also broadened our horizon and encouraged us to think outside of the usual framework that we have been working with. Gaining such knowledge would enable us to design new ways to further enhance our statistical analysis and research capabilities in future.



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