Discovering Gender Discrimination in Project Funding
By Andrea Romei, Salvatore Ruggieri, Franco Turini. 2012
11 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Political Science and International Relations, Safety Research
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Indrė Žliobaitė
- Vrushali Kulkarni
- Asmita Kashid
- Ruhi Patankar
- Andrea Romei
- Salvatore Ruggieri
- Sara Hajian
- Faisal Kamiran
In Political Science and International Relations
- Vrushali Kulkarni
- Asmita Kashid
- Ruhi Patankar
- Andrea Romei
- Indrė Žliobaitė
- Salvatore Ruggieri
- Sara Hajian
In Safety Research
- Indrė Žliobaitė
- Vrushali Kulkarni
- Asmita Kashid
- Ruhi Patankar
- Andrea Romei
- Salvatore Ruggieri
- Nisheeth K. Vishnoi
- Lingxiao Huang
Citations in the corpus
- A survey on measuring indirect discrimination in machine learning (2015, background): “ng approach for discrimination discovery typically mines association and classifi- cation rules from the data, and then assesses those rules in terms of potential discrimination [Ruggieri et al. 2010; Romei et al. 2012; Hajian and Domingo-Ferrer 2013; Pedreschi et al. 2012; Luong et al. 2011; Mancuha”
- Discrimination-aware data mining: a survey (2017, background): “Romei et al. (2012) have presented a real-life application (case-study) to discover gender discrimination in project funding.”
- A multidisciplinary survey on discrimination analysis (2013, background): “A real case study in the context of the evaluation of scientific projects for funding is presented by Romei et al. (2012).”
- Discrimination Prevention using Privacy Preserving Techniques (2015, methodology): “The case studies to discover and prevent discrimination using the existing DADM methods are presented in [13] [14].”