Skip to content

Births are difficult to predict even with rich survey and full-population register data

E. Sivak Emily M Cantrell Thomas Emery Javier Garcia-Bernardo Flavio Hafner Kasia Karpinska Malte Lüken Adrienne Mendrik J. Mulder Han-Zhang Ren Varun Satish Mark D. Verhagen Angelica Maineri Paulina K. Pankowska Jasmin Abdel Ghany B. Arpino Giovanni Cassani Julia Hellstrand Katya Ivanova Sanni Kuikka Ana Macanovic C. Rahal Felix C. Tropf Roland J. Veen N. Walasek D. V. van Wijk K. Wright Emilio Zagheni Henry Abbink E. Aliverti Matteo Amestoy T. Atav Nicola Barban S. Billingsley Goan J. Booij Louis Boucherie Yael A. Broos L. Chang J. Chiu C. Comolli B. Čule Qixiang Fang D. Feehan Rachel Ganly Erwin Gielens R. G. Gonzales Martinez A. Gradassi Rosember Guerra-Urzola Mario Guerra-Urzola St'ephane Guerrier Enamul Hassan V. Haverhoek Andrew T. Hendrickson Amber L. Howard Yuxuan Jin Sayash Kapoor E. van Kesteren Iris ten Klooster Marie Labussière Lydia T. Liu Tiffany Liu Adam Maghout Simone Meneghello L. Mohr C. Mulder S. Newman Jessica Nisén Janis Norden Mikkel Odgaard Riccardo Omenti Ozancan Ozdemir C. Pao Paige N. Park Gaia Penta J. C. Perdomo Tanzir Pial Alessio Piraccini Federica Querin Zichen Rao Christian Rellama Adrien Remund Frederieke Richert A. van de Rijt Mojtaba Rostami Kandroodi Stijn J. Rotman Lucas Sage Germans Savcisens Katrin Schwanitz S. Skiena Alessandro Spata Yannick D. Stadtfeld Benedikt Stroebl Gaetano Tedesco Mathilde Theelen Gianluca Tori Abigail Tun-Mendicuti Rishabh Tyagi Keyon Vafa L. Vecchietti Linda Vecgaile W. Vermeulen Maria-Pia Victoria Feser Lionel Voirol T. B. Volker Xin-Ran Wang Jia-Nian Yan Xin-Ying Zhao F. Zhou Z. Žilinčíková M. Nissim Matthew J. Salganik Gert Stulp
Sep 2026 · 0 citations
Computer Science

Abstract

Major life events have proven difficult to predict. Does this reflect limits of theory, data, and algorithms, or the large role of chance? We examine one outcome - having a child within three years - through a near-ideal setting for prediction: a data challenge where 147 researchers predicted births for Dutch residents aged 18-45, using survey data and full-population registers. Methods ranged from logistic regression to a large language model and transformers. Predictions were moderately accurate (best F1: register 0.59, survey 0.76); advanced models did not outperform classical ones; and the larger registers did not beat the survey. Simulating the stochastic biology of conception and pregnancy, we estimated a predictive ceiling (survey F1 ~ 0.86-0.94, register 0.88-0.96). Observed performance falls short of this ceiling, implicating imperfect data, methods, and unmodelled chance, while the ceiling itself shows that chance in reproduction alone sets a non-trivial limit on predicting individual lives.

View source

Similar papers

#machine learning Review Open access Oct 2014

Software development in startup companies: A systematic mapping study

The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al. · 394 citations · ⚡54

Diffusion models as plug-and-play priors

The possibility of inferring high-dimensional data inference in a model that consists of a prior and an auxiliary differentiable constraint given some additional information is considered, thereby allowing a range of potential applications in adapting models to new domains and tasks.

Alexandros Graikos, Esmeralda S. Whitammer, N. Jojic et al. · 316 citations · ⚡15

Trajectory Balance: Improved Credit Assignment in GFlowNets

It is proved that any global minimizer of the trajectory balance objective can define a policy that samples exactly from the target distribution, and empirically demonstrate the benefits of the trajectories balance objective for GFlowNet convergence, diversity of generated samples, and robustness to long action sequences and large action spaces.

Esmeralda S. Whitammer, Moksh Jain, Emmanuel Bengio et al. · 302 citations · ⚡60
#machine learning Review Open access Jun 2014

Why Early-Stage Software Startups Fail: A Behavioral Framework

This state-of-practice investigation was performed using a literature review followed by a multiple-case study approach and presents how inconsistency between managerial strategies and execution can lead to failure by means of a behavioral framework.

Carmine Giardino, Xiaofeng Wang, P. Abrahamsson · 175 citations · ⚡19
#artificial intelligence Open access Jul 2024

Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.

Kyra Wilson, Aylin Caliskan · 131 citations · ⚡8
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.

Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al. · 127 citations · ⚡15

Related blog posts

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.