78 citations · 138 across the 9 of their papers we have counts for
5 papers · 1 filter
Machine Learning Models Trained on a Longitudinal Survey Dataset Poorly Predict Hundreds of Life Outcomes
Emily M. Cantrell, Pranay Anchuri, Hanzhang Ren +1
Understanding the predictability of life outcomes is important for public policy and science, but existing studies focus on a limited number of outcomes and therefore struggle to d…
The origins of unpredictability in life trajectory prediction tasks
Ian Lundberg, Rachel Brown-Weinstock, Susan Clampet-Lundquist +5
Why are life trajectories difficult to predict? We investigated this question through in-depth qualitative interviews with 40 families sampled from a multi-decade longitudinal stud…
The network survival method for estimating adult mortality: Evidence from a survey experiment in Rwanda
Dennis M. Feehan, Mary Mahy, Matthew J. Salganik
Adult death rates are a critical indicator of population health and wellbeing. Wealthy countries have high-quality vital registration systems, but poor countries lack this infrastr…
Generalizing the Network Scale-Up Method: A New Estimator for the Size of Hidden Populations
Dennis M. Feehan, Matthew J. Salganik
The network scale-up method enables researchers to estimate the size of hidden populations, such as drug injectors and sex workers, using sampled social network data. The basic sca…
Wiki surveys: Open and quantifiable social data collection
Matthew J. Salganik, Karen E. C. Levy
In the social sciences, there is a longstanding tension between data collection methods that facilitate quantification and those that are open to unanticipated information. Advance…