EGEN Prize Application 2024
Announcing the EGEN research prize -- Applications due by 11:59pm EST, February 2nd, 2024.

The Empirical Study of Gender Research Network (EGEN) is pleased to announce that it will award several $5,000 prizes to graduate students or very early career scholars doing cutting edge research on gender and politics. EGEN nourishes empirical scholarship from a variety of methodological approaches, and across subfields, though it is particularly interested in incubating scholarship in comparative politics and international relations.

Submissions must be in English. Co-authorship ok if the co-author is also eligible for the prize.   

To be considered for the prize, a completed application must contain:

A completed cover form (google form)
ANONYMIZED CV in pdf format, “lastname_firstname_CV.pdf”
ANONYMIZED version of most polished piece of writing (uploaded here)  “lastname_firstname_writing sample.pdf”  
Advisor contact information (for graduate students).

Upload link: https://www.dropbox.com/request/Su1QS7Vg1ms98zk8GINp
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Name and Institutional Affiliation
 *
Email *
Advisor name, affiliation (for graduate students)
Advisor/recommender email
Short description of primary research interests
 *
Short description of site of fieldwork, cases, primary data, or key focus
Title of major project/piece of polished research on gender & politics
 *
For graduate students, a timeline for your dissertation completion. When do you plan to go on the job market?
 *
How will this prize benefit your research program? You can tell us about your current funding opportunities, the institutional support for research, and any other relevant factors like interruptions for COVID, family restrictions etc.
 *
Please identify three potential members from among the list of Executive board members (past and present) from the EGEN website to serve as a mentor in the coming year.
Please upload an anonymized version of your CV and your most polished piece of research (also anonymized) here:  https://www.dropbox.com/request/Su1QS7Vg1ms98zk8GINp *
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