Summary of Combining the Strengths Of Dutch Survey and Register Data in a Data Challenge to Predict Fertility (prefer), by Elizaveta Sivak et al.
Combining the Strengths of Dutch Survey and Register Data in a Data Challenge to Predict Fertility (PreFer)
by Elizaveta Sivak, Paulina Pankowska, Adrienne Mendrik, Tom Emery, Javier Garcia-Bernardo, Seyit Hocuk, Kasia Karpinska, Angelica Maineri, Joris Mulder, Malvina Nissim, Gert Stulp
First submitted to arxiv on: 1 Feb 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Databases (cs.DB)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed paper presents two novel datasets that can be used to study the predictability of fertility outcomes in the Netherlands, specifically focusing on determining whether people have children or not, when, and why. The datasets are based on the LISS panel, a longitudinal survey with thousands of variables covering various topics, including individual preferences and values, as well as Dutch register data that includes detailed information about millions of residents’ life courses. By introducing these datasets and outlining their strengths, the paper aims to advance our understanding of fertility behavior and computational social science. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The researchers are creating two new datasets to help scientists study why people have children or not, when, and how many. One dataset is from a big survey that asks questions about what people think and believe. The other dataset is based on information from a government database that shows what happens in people’s lives over time. This will help experts figure out if these datasets can be used to predict when someone might have children. The researchers are also setting up a challenge where people can use the datasets to see how well they can guess fertility outcomes, which could lead to new insights about why people make certain choices. |
