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on Sociology of Economics |
By: | J. Ignacio Conde-Ruiz; Juan José Ganuza; Manu Garcia; Luis A. Puch |
Abstract: | We analyze all the articles published in Top 5 economic journals between 2002 and 2019 in order to find gender differences in their research approach. Using an unsuper vised machine learning algorithm (Structural Topic Model) developed by Roberts et al. (2019) we characterize jointly the set of latent topics that best fits our data (the set of abstracts) and how the documents/abstracts are allocated in each latent topic. This latent topics are mixtures over words were each word has a probability of belonging to a topic after controlling by year and journal. This latent topics may capture research fields but also other more subtle characteristics related to the way in which the articles are written. We find that females are uneven distributed along these latent topics by using only data driven methods. The differences about gender research approaches we found in this paper, are "automatically" generated given the research articles, without an arbitrary allocation to particular categories (as JEL codes, or research areas). |
Keywords: | machine learning, structural topic model, gender, research fields |
JEL: | I20 J16 |
Date: | 2021–02 |
URL: | http://d.repec.org/n?u=RePEc:upf:upfgen:1771&r=all |
By: | Corsini, Alberto (Université Côte d’Azur, CNRS, GREDEG, France); Pezzoni, Michele (Université Côte d’Azur, CNRS, GREDEG, Observatoire des Sciences et Techniques, HCERES, OFCE, SciencePo, France, and ICRIOS, Bocconi University, Italy); Visentin, Fabiana (UNU-MERIT, Maastricht University) |
Abstract: | This paper investigates the impact of the social environment to which a Ph.D. student is exposed on her scientific productivity during the training period. Vertical and horizontal relationships depict the social environment. Vertical relationships are those supervisor-student, while horizontal relationships are those student-peers. We characterize these relationships by assessing how the supervisor's and peers' biographic and academic characteristics relate to the student's productivity as measured by the publication quantity, quality, and scientific network size. Unique to our study, we cover the entire student population of a European country for all the STEM fields. Specifically, we analyse the productivity of 77,143 students who graduated in France between 2000 and 2014. We find that having a female supervisor is associated with a higher student's productivity as well as being supervised by a mid-career scientist and having a supervisor with a high academic reputation. The supervisor's fundraising ability benefits only one specific dimension of the student's productivity, i.e., the student's work quality. Interestingly, the supervisor's mentorship experience negatively associates with student's productivity. Having many peers negatively associates with the student's productivity, especially if peers are senior students. Having female peers positively correlates with the student's productivity, while peers' academic status shows mixed effects according to the productivity dimension considered. We find results heterogeneity when breaking down our sample by field of research. |
Keywords: | French Ph.D. students, Productivity determinants, Social environment, Supervisor, Peers |
JEL: | J24 O30 |
Date: | 2021–03–09 |
URL: | http://d.repec.org/n?u=RePEc:unm:unumer:2021011&r=all |
By: | Pascaline Dupas; Alicia Sasser Modestino; Muriel Niederle; Justin Wolfers; The Seminar Dynamics Collective |
Abstract: | This paper reports the results of the first systematic attempt at quantitatively measuring the seminar culture within economics and testing whether it is gender neutral. We collected data on every interaction between presenters and their audience in hundreds of research seminars and job market talks across most leading economics departments, as well as during summer conferences. We find that women presenters are treated differently than their male counterparts. Women are asked more questions during a seminar and the questions asked of women presenters are more likely to be patronizing or hostile. These effects are not due to women presenting in different fields, different seminar series, or different topics, as our analysis controls for the institution, seminar series, and JEL codes associated with each presentation. Moreover, it appears that there are important differences by field and that these differences are not uniformly mitigated by more rigid seminar formats. Our findings add to an emerging literature documenting ways in which women economists are treated differently than men, and suggest yet another potential explanation for their under-representation at senior levels within the economics profession. |
JEL: | A1 C8 J4 J7 |
Date: | 2021–02 |
URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:28494&r=all |