All Publications


  • Advances in transparency and reproducibility in the social sciences. Social science research Freese, J., Rauf, T., Voelkel, J. G. 2022; 107: 102770

    Abstract

    Worries about a "credibility crisis" besieging science have ignited interest in research transparency and reproducibility as ways of restoring trust in published research. For quantitative social science, advances in transparency and reproducibility can be seen as a set of developments whose trajectory predates the recent alarm. We discuss several of these developments, including preregistration, data-sharing, formal infrastructure in the form of resources and policies, open access to research, and specificity regarding research contributions. We also discuss the spillovers of this predominantly quantitative effort towards transparency for qualitative research. We conclude by emphasizing the importance of mutual accountability for effective science, the essential role of openness for this accountability, and the importance of scholarly inclusiveness in figuring out the best ways for openness to be accomplished in practice.

    View details for DOI 10.1016/j.ssresearch.2022.102770

    View details for PubMedID 36058608

  • The Political Context and Infant Health in the United States AMERICAN SOCIOLOGICAL REVIEW Torche, F., Rauf, T. 2021
  • How College Makes Liberals (or Conservatives) Socius Rauf, T. 2021

    View details for DOI 10.1177/2378023120982435

  • The Transition to Fatherhood and the Health of Men JOURNAL OF MARRIAGE AND FAMILY Torche, F., Rauf, T. 2020

    View details for DOI 10.1111/jomf.12732

    View details for Web of Science ID 000581178700001

  • Measuring the predictability of life outcomes with a scientific mass collaboration. Proceedings of the National Academy of Sciences of the United States of America Salganik, M. J., Lundberg, I., Kindel, A. T., Ahearn, C. E., Al-Ghoneim, K., Almaatouq, A., Altschul, D. M., Brand, J. E., Carnegie, N. B., Compton, R. J., Datta, D., Davidson, T., Filippova, A., Gilroy, C., Goode, B. J., Jahani, E., Kashyap, R., Kirchner, A., McKay, S., Morgan, A. C., Pentland, A., Polimis, K., Raes, L., Rigobon, D. E., Roberts, C. V., Stanescu, D. M., Suhara, Y., Usmani, A., Wang, E. H., Adem, M., Alhajri, A., AlShebli, B., Amin, R., Amos, R. B., Argyle, L. P., Baer-Bositis, L., Buchi, M., Chung, B., Eggert, W., Faletto, G., Fan, Z., Freese, J., Gadgil, T., Gagne, J., Gao, Y., Halpern-Manners, A., Hashim, S. P., Hausen, S., He, G., Higuera, K., Hogan, B., Horwitz, I. M., Hummel, L. M., Jain, N., Jin, K., Jurgens, D., Kaminski, P., Karapetyan, A., Kim, E. H., Leizman, B., Liu, N., Moser, M., Mack, A. E., Mahajan, M., Mandell, N., Marahrens, H., Mercado-Garcia, D., Mocz, V., Mueller-Gastell, K., Musse, A., Niu, Q., Nowak, W., Omidvar, H., Or, A., Ouyang, K., Pinto, K. M., Porter, E., Porter, K. E., Qian, C., Rauf, T., Sargsyan, A., Schaffner, T., Schnabel, L., Schonfeld, B., Sender, B., Tang, J. D., Tsurkov, E., van Loon, A., Varol, O., Wang, X., Wang, Z., Wang, J., Wang, F., Weissman, S., Whitaker, K., Wolters, M. K., Woon, W. L., Wu, J., Wu, C., Yang, K., Yin, J., Zhao, B., Zhu, C., Brooks-Gunn, J., Engelhardt, B. E., Hardt, M., Knox, D., Levy, K., Narayanan, A., Stewart, B. M., Watts, D. J., McLanahan, S. 2020

    Abstract

    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.

    View details for DOI 10.1073/pnas.1915006117

    View details for PubMedID 32229555

  • Getting a Job, Again: New Evidence against Subjective Well-Being Scarring Social Forces Rauf, T. 2020

    View details for DOI 10.1093/sf/soaa086