This work is licensed under the Creative Commons Attribution 4.0 International License.
Bojanowski, M. and Czerniawska, D. 2020. Reaching for unique resources: Structural holes and specialization in scientific collaboration networks. Journal of Social Structure. Forthcoming. Preprint available on-line, available at: http://recon.icm.edu.pl/wp-content/uploads/2019/05/exchange_networks.pdf.BojanowskiM.CzerniawskaD.2020Reaching for unique resources: Structural holes and specialization in scientific collaboration networksJournal of Social StructureForthcoming. Preprint available on-lineavailable athttp://recon.icm.edu.pl/wp-content/uploads/2019/05/exchange_networks.pdf10.21307/joss-2020-001Search in Google Scholar
Coleman, J. S. 1994. Foundations of Social Theory, Harvard University Press, Cambridge, MA.ColemanJ. S.1994Foundations of Social Theory,Harvard University PressCambridge, MASearch in Google Scholar
Czerniawska, D. 2018. Sieci współpracy i wymiany w centrach i na peryferiach. Przypadek polskiej nauki (PhD thesis). University of Warsaw, Warsaw, Poland.CzerniawskaD.2018Sieci współpracy i wymiany w centrach i na peryferiach. Przypadek polskiej nauki (PhD thesis)University of Warsaw, Warsaw, PolandSearch in Google Scholar
Czerniawska, D., Fenrich, W. and Bojanowski, M. 2018. Actors, relations, and networks: Scholarly collaboration beyond bibliometric measures. Polish Sociological Review, 202: 167–185.CzerniawskaD.FenrichW.BojanowskiM.2018Actors, relations, and networks: Scholarly collaboration beyond bibliometric measuresPolish Sociological Review202167185Search in Google Scholar
Krivitsky, P. N. and Morris, M. 2017. Inference for social network models from egocentrically sampled data, with application to understanding persistent racial disparities in HIV prevalence in the US. The Annals of Applied Statistics, 11(1): 427–455.KrivitskyP. N.MorrisM.2017Inference for social network models from egocentrically sampled data, with application to understanding persistent racial disparities in HIV prevalence in the USThe Annals of Applied Statistics11(1)42745510.1214/16-AOAS1010Search in Google Scholar
Krivitsky, P. N., Koehly, L. M. and Marcum, C. S. 2019. Exponential-family random graph models for multi-layer networks. SocArXiv, available at: https://doi.org/10.31235/osf.io/dqe9b (accessed August 14, 2019).KrivitskyP. N.KoehlyL. M.MarcumC. S.2019Exponential-family random graph models for multi-layer networksSocArXivavailable at:https://doi.org/10.31235/osf.io/dqe9b(accessed August 14, 2019)10.1007/s11336-020-09720-7Search in Google Scholar
Kwiek, M. 2018. Changing European Academics: A Comparative Study of Social Stratification, Work Patterns and Research Productivity. Routledge, London.KwiekM.2018Changing European Academics: A Comparative Study of Social Stratification, Work Patterns and Research ProductivityRoutledgeLondon10.4324/9781351182041Search in Google Scholar
Kwiek, M. and Szadkowski, K. 2018. Higher education systems and institutions, Poland. In Teixeira, P., Shin, J. C., Amaral, A., Bernasconi, A., Magalhaes, A., Kehm, B. M. and Nokkala, T. (Eds), Encyclopedia of International Higher Education Systems and Institutions, Springer, pp. 1–10, available at: https://doi.org/10.1007/978-94-017-9553-1_375-1.KwiekM.SzadkowskiK.2018Higher education systems and institutions, PolandInTeixeiraP.ShinJ. C.AmaralA.BernasconiA.MagalhaesA.KehmB. M.NokkalaT.(Eds)Encyclopedia of International Higher Education Systems and Institutions,Springerpp.110available at:https://doi.org/10.1007/978-94-017-9553-1_375-110.1007/978-94-017-9553-1_375-1Search in Google Scholar
Laudel, G. 2001. Collaboration, creativity and rewards: why and how scientists collaborate. International Journal of Technology Management, 22(7–8): 762–781.LaudelG.2001Collaboration, creativity and rewards: why and how scientists collaborateInternational Journal of Technology Management22(7–8)76278110.1504/IJTM.2001.002990Search in Google Scholar
Lewis, J. M., Ross, S. and Holden, T. 2012. The how and why of academic collaboration: disciplinary differences and policy implications. Higher Education, 64(5): 693–708.LewisJ. M.RossS.HoldenT.2012The how and why of academic collaboration: disciplinary differences and policy implicationsHigher Education64(5)69370810.1007/s10734-012-9521-8Search in Google Scholar
Leydesdorff, L., Wagner, C., Park, H. W. and Adams, J. 2013. International collaboration in science: the global map and the network, available at: http://arxiv.org/abs/1301.0801 (accessed August 10, 2019).LeydesdorffL.WagnerC.ParkH. W.AdamsJ.2013International collaboration in science: the global map and the networkavailable at:http://arxiv.org/abs/1301.0801(accessed August 10, 2019)Search in Google Scholar
Moody, J. 2004. The structure of a social science collaboration network: disciplinary cohesion from 1963 to 1999. American Sociological Review, 69(2): 213–238.MoodyJ.2004The structure of a social science collaboration network: disciplinary cohesion from 1963 to 1999American Sociological Review69(2)21323810.1177/000312240406900204Search in Google Scholar
OECD. 2019. OECD science, technology and R&D statistics: main science and technology indicators, available at: https://data.oecd.org (accessed August 10, 2019).OECD2019OECD science, technology and R&D statistics: main science and technology indicatorsavailable at:https://data.oecd.org(accessed August 10, 2019)Search in Google Scholar
Qin, J., Lancaster, F. W. and Allen, B. 1997. Types and levels of collaboration in interdisciplinary research in the sciences. Journal of the American Society for Information Science, 48(10): 893–916.QinJ.LancasterF. W.AllenB.1997Types and levels of collaboration in interdisciplinary research in the sciencesJournal of the American Society for Information Science48(10)89391610.1002/(SICI)1097-4571(199710)48:10<893::AID-ASI5>3.0.CO;2-XSearch in Google Scholar
