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Wildfire evacuations have become a persistent challenge all over the world in recent years. Studies have proposed various evacuation strategies, such as vehicle reduction, phased evacuation, and prohibition of on-street parking, which have demonstrated effectiveness in specific communities. However, a comprehensive study that generalizes the effectiveness and applicability of these strategies across different types of communities is lacking. This generalization could hold significant value for small, resource-strapped communities situated in wildland–urban interface zones (i.e., comprising a mix of residences and flammable vegetation) that lack the resources to conduct dedicated evacuation studies. In this study, two indicators, the ratio of background traffic volume to the number of evacuees (RBE), and the ratio of the capacity of the main evacuation roads to the number of evacuees (RCE) were derived to categorize communities into specific groups based on their characteristics during wildfire events. Through evacuation simulations of some typical real-world communities, the applicability and effectiveness of each strategy for each group was assessed. For the given scenarios considered, the findings revealed that for communities with high a RBE and low RCE, promoting carpooling with more than two people per vehicle, extending phased evacuation intervals with safety assurance for evacuees, and enforcing on-street parking prohibition made evacuations more effective. For other communities, encouraging families to use fewer vehicles and implementing a 15-min phased interval, if possible, could potentially be useful. 

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.