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Predicting the future impact of Computer Science researchers: Is there a gender bias?. (2022). Kuppler, Matthias.
In: Scientometrics.
RePEc:spr:scient:v:127:y:2022:i:11:d:10.1007_s11192-022-04337-2.

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  1. Coping with the Inequity and Inefficiency of the H-Index: A Cross-Disciplinary Empirical Analysis. (2024). Foschi, Paolo ; Zagonari, Fabio.
    In: Publications.
    RePEc:gam:jpubli:v:12:y:2024:i:2:p:12-:d:1380265.

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  2. An editorial of “AI + informetrics”: multi-disciplinary interactions in the era of big data. (2022). Zhang, YI ; Mayr, Philipp ; Suominen, Arho.
    In: Scientometrics.
    RePEc:spr:scient:v:127:y:2022:i:11:d:10.1007_s11192-022-04561-w.

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  1. Abramo, G., Cicero, T., & D’Angelo, C. A. (2015). Should the research performance of scientists be distinguished by gender? Journal of Informetrics, 9(1), 25–38.

  2. Abramo, G., D’Angelo, C. A., & Murgia, G. (2013). Gender differences in research collaboration. Journal of Informetrics, 7(4), 811–822.

  3. Acuna, D. E., Allesina, S., & Kording, K. P. (2012). Predicting scientific success. Nature, 489(7415), 201–202.

  4. Aigner, D. J., & Cain, G. G. (1977). Statistical Theories of Discrimination in Labor Markets. Industrial and Labor Relations Review, 30(2), 175.
    Paper not yet in RePEc: Add citation now
  5. Alonso, S., Cabrerizo, F., Herrera-Viedma, E., & Herrera, F. (2009). h-Index: A review focused in its variants, computation and standardization for different scientific fields. Journal of Informetrics, 3(4), 273–289.

  6. AlShebli, B. K., Rahwan, T., & Woon, W. L. (2018). The preeminence of ethnic diversity in scientific collaboration. Nature Communications, 9(1), 5163.

  7. Ayaz, S., Masood, N., & Islam, M. A. (2018). Predicting scientific impact based on h-index. Scientometrics, 114(3), 993–1010.

  8. Barocas, S., & Selbst, A. D. (2016). Big Data’s Disparate Impact. California Law Review, 104(3), 671–732.
    Paper not yet in RePEc: Add citation now
  9. Beaudry, C., & Larivière, V. (2016). Which gender gap? Factors affecting researchers’ scientific impact in science and medicine. Research Policy, 45(9), 1790–1817.

  10. Bendels, M. H. K., Müller, R., Brueggmann, D., & Groneberg, D. A. (2018). Gender disparities in high-quality research revealed by Nature Index journals. PLOS ONE, 13(1), e0189136.
    Paper not yet in RePEc: Add citation now
  11. Bertsimas, D., Brynjolfsson, E., Reichman, S., & Silberholz, J. (2015). OR forum-tenure analytics: Models for predicting research impact. Operations Research, 63(6), 1246–1261.

  12. Blau, F. D., Currie, J. M., Croson, R. T. A., & Ginther, D. K. (2010). Can mentoring help female assistant professors? Interim results from a randomized trial. American Economic Review, 100(2), 348–352.

  13. Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5–32.
    Paper not yet in RePEc: Add citation now
  14. Brin, S., & Page, L. (1998). The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems, 30(1–7), 107–117.
    Paper not yet in RePEc: Add citation now
  15. Burton, J. W., Stein, M., & Jensen, T. B. (2020). A systematic review of algorithm aversion in augmented decision making. Journal of Behavioral Decision Making, 33(2), 220–239.
    Paper not yet in RePEc: Add citation now
  16. Carli, L. L., Alawa, L., Lee, Y., Zhao, B., & Kim, E. (2016). Stereotypes about gender and science: Women scientists. Psychology of Women Quarterly, 40(2), 244–260.
    Paper not yet in RePEc: Add citation now
  17. Caton, S., & Haas, C. (2020). Fairness in machine learning: A survey. arXiv: 2010.04053 .
    Paper not yet in RePEc: Add citation now
  18. Ceci, S. J., Ginther, D. K., Kahn, S., & Williams, W. M. (2014). Women in academic science: A changing landscape. Psychological Science in the Public Interest, 15(3), 75–141.
    Paper not yet in RePEc: Add citation now
  19. Chen, T., & Guestrin, C. (2016). XGBoost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining (pp. 785–794). ACM.
    Paper not yet in RePEc: Add citation now
  20. Chouldechova, A. (2016). Fair prediction with disparate impact: A study of bias in recidivism prediction instruments. arXiv:1610.07524 [cs, stat].
    Paper not yet in RePEc: Add citation now
  21. Daud, A., Aljohani, N. R., Abbasi, R. A., Rafique, Z., Amjad, T., Dawood, H., & Alyoubi, K. H. (2017). Finding rising stars in co-author networks via weighted mutual influence. In Proceedings of the 26th international conference on World Wide Web Companion—WWW ’17 Companion (pp. 33–41). ACM.
    Paper not yet in RePEc: Add citation now
  22. Daud, A., Song, M., Hayat, M. K., Amjad, T., Abbasi, R. A., Dawood, H., & Ghani, A. (2020). Finding rising stars in bibliometric networks. Scientometrics, 124(1), 633–661.

  23. Demetrescu, C., Finocchi, I., Ribichini, A., & Schaerf, M. (2020). On bibliometrics in academic promotions: A case study in computer science and engineering in Italy. Scientometrics, 124(3), 2207–2228.

  24. Dong, Y., Johnson, R. A., & Chawla, N. V. (2016). Can scientific impact be predicted? IEEE Transactions on Big Data, 2(1), 18–30.
    Paper not yet in RePEc: Add citation now
  25. Dwork, C., Hardt, M., Pitassi, T., Reingold, O., & Zemel, R. (2012). Fairness through awareness. In Proceedings of the 3rd innovations in theoretical computer science conference—ITCS ’12 (pp. 214–226). ACM.
    Paper not yet in RePEc: Add citation now
  26. Eaton, A. A., Saunders, J. F., Jacobson, R. K., & West, K. (2020). How gender and race stereotypes impact the advancement of scholars in STEM: Professors’ biased evaluations of physics and biology post-doctoral candidates. Sex Roles, 82(3–4), 127–141.
    Paper not yet in RePEc: Add citation now
  27. European Commission. (2019). She figures 2018. Publications Office.
    Paper not yet in RePEc: Add citation now
  28. Flanagin, A. (1998). Prevalence of articles with honorary authors and ghost authors in peer-reviewed medical journals. JAMA, 280(3), 222.
    Paper not yet in RePEc: Add citation now
  29. Friedman, J. H. (2001). Greedy function approximation: A Gradient Boosting Machine. The Annals of Statistics, 29(5), 1189–1232.
    Paper not yet in RePEc: Add citation now
  30. Heilman, M. E. (2012). Gender stereotypes and workplace bias. Research in Organizational Behavior, 32, 113–135.
    Paper not yet in RePEc: Add citation now
  31. Hicks, D., Wouters, P., Waltman, L., de Rijcke, S., & Rafols, I. (2015). Bibliometrics: The Leiden Manifesto for research metrics. Nature, 520(7548), 429–431.

  32. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102(46), 16569–16572.
    Paper not yet in RePEc: Add citation now
  33. Hirsch, J. E. (2007). Does the h index have predictive power? Proceedings of the National Academy of Sciences of the United States of America, 104(49), 19193–19198.
    Paper not yet in RePEc: Add citation now
  34. Hofstra, B., Kulkarni, V. V., Munoz-Najar Galvez, S., He, B., Jurafsky, D., & McFarland, D. A. (2020). The diversity-innovation paradox in science. Proceedings of the National Academy of Sciences of the United States of America, 117(17), 9284–9291.
    Paper not yet in RePEc: Add citation now
  35. Holman, L., Stuart-Fox, D., & Hauser, C. E. (2018). The gender gap in science: How long until women are equally represented? PLOS Biology, 16(4), e2004956.

  36. Huang, J., Gates, A. J., Sinatra, R., & Barabási, A.-L. (2020). Historical comparison of gender inequality in scientific careers across countries and disciplines. Proceedings of the National Academy of Sciences of the United States of America, 117(9), 4609–4616.
    Paper not yet in RePEc: Add citation now
  37. Jadidi, M., Karimi, F., Lietz, H., & Wagner, C. (2018). Gender disparities in science? Dropout, productivity, collaborations and success of male and female computer scientists. Advances in Complex Systems, 21(03n04), 1750011.

  38. James, G., Witten, D., Hastie, T., & Tibshirani, R. (Eds.). (2013). An introduction to statistical learning: With applications in R. Springer texts in statistics, vol. 103. Springer.
    Paper not yet in RePEc: Add citation now
  39. Kessels, U., Rau, M., & Hannover, B. (2006). What goes well with physics? Measuring and altering the image of science. British Journal of Educational Psychology, 76(4), 761–780.
    Paper not yet in RePEc: Add citation now
  40. Knobloch-Westerwick, S., Glynn, C. J., & Huge, M. (2013). The Matilda effect in science communication: An experiment on gender bias in publication quality perceptions and collaboration interest. Science Communication, 35(5), 603–625.
    Paper not yet in RePEc: Add citation now
  41. Koch, A. J., D’Mello, S. D., & Sackett, P. R. (2015). A meta-analysis of gender stereotypes and bias in experimental simulations of employment decision making. Journal of Applied Psychology, 100(1), 128–161.
    Paper not yet in RePEc: Add citation now
  42. Lane, K. A., Goh, J. X., & Driver-Linn, E. (2012). Implicit science stereotypes mediate the relationship between gender and academic participation. Sex Roles, 66(3–4), 220–234.
    Paper not yet in RePEc: Add citation now
  43. Larivière, V., Ni, C., Gingras, Y., Cronin, B., & Sugimoto, C. R. (2013). Bibliometrics: Global gender disparities in science. Nature, 504(7479), 211–213.

  44. Leavy, S., Meaney, G., Wade, K., & Greene, D. (2020). Mitigating gender bias in machine learning data sets. In L. Boratto, S. Faralli, M. Marras, & G. Stilo (Eds.), Bias and social aspects in search and recommendation (Vol. 1245, pp. 12–26). Communications in Computer and Information Science: Springer.
    Paper not yet in RePEc: Add citation now
  45. Lepri, B., Oliver, N., Letouzé, E., Pentland, A., & Vinck, P. (2018). Fair, transparent, and accountable algorithmic decision-making processes: The premise, the proposed solutions, and the open challenges. Philosophy & Technology, 31(4), 611–627.
    Paper not yet in RePEc: Add citation now
  46. Leslie, S.-J., Cimpian, A., Meyer, M., & Freeland, E. (2015). Expectations of brilliance underlie gender distributions across academic disciplines. Science, 347(6219), 262–265.
    Paper not yet in RePEc: Add citation now
  47. Li, X.-L., Foo, C. S., Tew, K. L., & Ng, S.-K. (2009). Searching for rising stars in bibliography networks. In X. Zhou, H. Yokota, K. Deng, & Q. Liu (Eds.), Database systems for advanced applications (Vol. 5463, pp. 288–292). Lecture notes in computer science. Springer.
    Paper not yet in RePEc: Add citation now
  48. Long, J. S. (1992). Measures of sex differences in scientific productivity. Social Forces, 71(1), 159.
    Paper not yet in RePEc: Add citation now
  49. Mazloumian, A. (2012). Predicting scholars’ scientific impact. PLoS ONE, 7(11), e49246.

  50. Merton, R. K. (1968). The Matthew Effect in Science: The reward and communication systems of science are considered. Science, 159(3810), 56–63.
    Paper not yet in RePEc: Add citation now
  51. Miller, D. I., & Wai, J. (2015). The bachelor’s to Ph.D. STEM pipeline no longer leaks more women than men: A 30-year analysis. Frontiers in Psychology, 6, 37.
    Paper not yet in RePEc: Add citation now
  52. Mitchell, S., Potash, E., Barocas, S., D’Amour, A., & Lum, K. (2021). Algorithmic fairness: Choices, assumptions, and definitions. Annual Review of Statistics and Its Application, 8(1), 141–163.
    Paper not yet in RePEc: Add citation now
  53. Moss-Racusin, C. A., Dovidio, J. F., Brescoll, V. L., Graham, M. J., & Handelsman, J. (2012). Science faculty’s subtle gender biases favor male students. Proceedings of the National Academy of Sciences of the United States of America, 109(41), 16474–16479.
    Paper not yet in RePEc: Add citation now
  54. National Science Board. (2018). Science and Engineering Indicators 2018. Technical Report NSB-2018-1. National Science Foundation.
    Paper not yet in RePEc: Add citation now
  55. NCSES. (2019). Survey of Doctorate Recipients 2019. Technical Report NSF 21-320. National Center for Science and Engineering Statistics. National Science Foundation.
    Paper not yet in RePEc: Add citation now
  56. NCSES. (2021). Women, minorities, and persons with disabilities in science and engineering: 2021. Technical Report Special Report NSF 21-321. National Center for Science and Engineering Statistics. National Science Foundation.
    Paper not yet in RePEc: Add citation now
  57. Nie, Y., Zhu, Y., Lin, Q., Zhang, S., Shi, P., & Niu, Z. (2019). Academic rising star prediction via scholar’s evaluation model and machine learning techniques. Scientometrics, 120(2), 461–476.

  58. Nielsen, M. W., Alegria, S., Börjeson, L., Etzkowitz, H., Falk-Krzesinski, H. J., Joshi, A., Leahey, E., Smith-Doerr, L., Woolley, A. W., & Schiebinger, L. (2017). Opinion: Gender diversity leads to better science. Proceedings of the National Academy of Sciences of the United States of America, 114(8), 1740–1742.
    Paper not yet in RePEc: Add citation now
  59. Nosek, B. A., Banaji, M. R., & Greenwald, A. G. (2002). Math = male, me = female, therefore math me. Journal of Personality and Social Psychology, 83(1), 44–59.
    Paper not yet in RePEc: Add citation now
  60. Panagopoulos, G., Tsatsaronis, G., & Varlamis, I. (2017). Detecting rising stars in dynamic collaborative networks. Journal of Informetrics, 11(1), 198–222.

  61. Penner, O., Petersen, A. M., Pan, R. K., & Fortunato, S. (2013). Commentary: The case for caution in predicting scientists’ future impact. Physics Today, 66(4), 8–9.
    Paper not yet in RePEc: Add citation now
  62. Reskin, B. F. (2000). The proximate causes of employment discrimination. Contemporary Sociology, 29(2), 319.
    Paper not yet in RePEc: Add citation now
  63. Reskin, B. F., & McBrier, D. B. (2000). Why not ascription? Organizations’ employment of male and female managers. American Sociological Review, 65(2), 210.
    Paper not yet in RePEc: Add citation now
  64. Reymert, I. (2021). Bibliometrics in academic recruitment: A screening tool rather than a game changer. Minerva, 59(1), 53–78.
    Paper not yet in RePEc: Add citation now
  65. Santamaría, L., & Mihaljević, H. (2018). Comparison and benchmark of name-to-gender inference services. PeerJ Computer Science, 4, e156.
    Paper not yet in RePEc: Add citation now
  66. Sanyal, D. K., Bhowmick, P. K., & Das, P. P. (2021). A review of author name disambiguation techniques for the PubMed bibliographic database. Journal of Information Science, 47(2), 227–254.
    Paper not yet in RePEc: Add citation now
  67. Sarsons, H. (2017). Recognition for group work: Gender differences in academia. American Economic Review, 107(5), 141–145.

  68. Seeber, M., Cattaneo, M., Meoli, M., & Malighetti, P. (2019). Self-citations as strategic response to the use of metrics for career decisions. Research Policy, 48(2), 478–491.

  69. Sheltzer, J. M., & Smith, J. C. (2014). Elite male faculty in the life sciences employ fewer women. Proceedings of the National Academy of Sciences of the United States of America, 111(28), 10107–10112.
    Paper not yet in RePEc: Add citation now
  70. Symonds, M. R., Gemmell, N. J., Braisher, T. L., Gorringe, K. L., & Elgar, M. A. (2006). Gender differences in publication output: Towards an unbiased metric of research performance. PLoS ONE, 1(1), e127.

  71. Tekles, A., & Bornmann, L. (2019). Author name disambiguation of bibliometric data: A comparison of several unsupervised approaches. arXiv:1904.12746 [cs].
    Paper not yet in RePEc: Add citation now
  72. van Anders, S. M. (2004). Why the academic pipeline leaks: Fewer men than women perceive barriers to becoming professors. Sex Roles, 51(9–10), 511–521.
    Paper not yet in RePEc: Add citation now
  73. van Arensbergen, P., van der Weijden, I., & van den Besselaar, P. (2012). Gender differences in scientific productivity: A persisting phenomenon? Scientometrics, 93(3), 857–868.

  74. van der Lee, R., & Ellemers, N. (2015). Gender contributes to personal research funding success in The Netherlands. Proceedings of the National Academy of Sciences of the United States of America, 112(40), 12349–12353.
    Paper not yet in RePEc: Add citation now
  75. Wang, D., & Barabási, A.-L. (2021). The science of science (1st ed.). Cambridge University Press.
    Paper not yet in RePEc: Add citation now
  76. Weihs, L., & Etzioni, O. (2017). Learning to predict citation-based impact measures. In 2017 ACM/IEEE joint conference on digital libraries (JCDL) (pp. 1–10). IEEE.
    Paper not yet in RePEc: Add citation now
  77. Wennerås, C., & Wold, A. (1997). Nepotism and sexism in peer-review. Nature, 387(6631), 341–343.

  78. West, J. D., Jacquet, J., King, M. M., Correll, S. J., & Bergstrom, C. T. (2013). The role of gender in scholarly authorship. PLoS ONE, 8(7), e66212.

  79. Wilhite, A. W., & Fong, E. A. (2012). Coercive citation in academic publishing. Science, 335(6068), 542–543.
    Paper not yet in RePEc: Add citation now
  80. Witteman, H. O., Hendricks, M., Straus, S., & Tannenbaum, C. (2019). Are gender gaps due to evaluations of the applicant or the science? A natural experiment at a national funding agency. The Lancet, 393(10171), 531–540.
    Paper not yet in RePEc: Add citation now
  81. Zhang, C., Liu, C., Yu, L., Zhang, Z.-K., & Zhou, T. (2016a). Identifying the academic rising stars. arXiv: 1606.05752 .
    Paper not yet in RePEc: Add citation now
  82. Zhang, J., Ning, Z., Bai, X., Wang, W., Yu, S., & Xia, F. (2016b). Who are the Rising Stars in Academia? In Proceedings of the 16th ACM/IEEE-CS on joint conference on digital libraries (pp. 211–212). ACM.
    Paper not yet in RePEc: Add citation now
  83. Zhu, X., Turney, P., Lemire, D., & Vellino, A. (2015). Measuring academic influence: Not all citations are equal. Journal of the Association for Information Science and Technology, 66(2), 408–427.

  84. Zuo, Z., & Zhao, K. (2021). Understanding and predicting future research impact at different career stages—A social network perspective. Journal of the Association for Information Science and Technology, 72(4), 454–472.

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  23. Gender differences in scientific performance: A bibliometric matching analysis of Danish health sciences Graduates. (2015). Frandsen, Tove Faber ; Jacobsen, Rasmus Hojbjerg ; Brixen, Kim ; Wallin, Johan A ; Ousager, Jakob.
    In: Journal of Informetrics.
    RePEc:eee:infome:v:9:y:2015:i:4:p:1007-1017.

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