How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.

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Government agencies must make rapid and informed decisions in wildfires to evacuate people safely. However, current evacuation simulation tools for resource-strapped agencies largely fail to compare possible transportation responses or incorporate empirical evidence from past wildfires. Consequently, this study employs online survey data from evacuees of the 2017 Northern California Wildfires ( n = 37), the 2017 Southern California Wildfires ( n = 175), and the 2018 Carr Wildfire ( n = 254) to inform a policy-oriented traffic evacuation simulation model. The simulation is tested for a hypothetical wildfire evacuation in the wildland-urban interface of Berkeley, California. The study focuses on variables including fire speed, departure time distribution, towing of items, transportation mode, GPS-enabled rerouting, phased evacuations (i.e., allowing higher-risk residents to leave earlier), and contraflow (i.e., switching all lanes away from danger). It was found that reducing evacuating household vehicles (i.e., to one vehicle per household) and increasing GPS-enabled rerouting (e.g., 50% participation) lowered exposed vehicles (i.e., total vehicles in the fire frontier) by over 50% and evacuation time estimates (ETEs) by about 30% from baseline. Phased evacuations with a suitable time interval reduced exposed vehicles most significantly (over 90%) but produced slightly longer ETEs. Both contraflow (on limited links because of resource constraints) and slowing fire speed were effective in lowering number of exposed vehicles (around 50%), but not ETEs. Extended contraflow can reduce both exposed vehicles and ETEs. It is recommended that agencies develop a communication and parking plan to reduce the number of evacuating vehicles, create and communicate a phased evacuation plan, and build partnerships with GPS-routing services.

The rational allocation of functional areas is the foundation for addressing the sustainable development of cities. Efficient and accurate identification methods of urban functional areas are of great significance to the adjustment and testing of urban planning and industrial layout optimization. Firstly, by employing multisource geographic data, an identification method of urban functional areas was developed. A quantitative measurement approach of the urban functional area was then established considering the comprehensive effects of human-land, space-time, and thematic information to present the covering area of ground objects, public awareness, and empirical research. Finally, the Zhengzhou city, which locates in Henan province of central China, was used to test the method. The results show that the developed method is efficient, accurate, and universal and can identify urban functional areas quickly and accurately. We found that the overall distribution of Zhengzhou’s functional areas presents a spatial pattern of single and multimixed coordinated development. The city’s commercial functional areas and commercial-based mixed functional areas are located in the city’s central area. The green square’s function area occupies relatively low and is mainly distributed in the city’s fringe.