Identifying Words in Job Advertisements Responsible for Gender Bias in Candidate Ranking Systems via Counterfactual Learning

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Original language	English
Title of host publication	Proceedings of the 3rd Workshop on Recommender Systems for Human Resources (RecSys in HR @ RecSys 2023),
Number of pages	10
Publication status	Published - 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

@inproceedings{889d8f8b79174f8a80a52488008f2c66,

title = "Identifying Words in Job Advertisements Responsible for Gender Bias in Candidate Ranking Systems via Counterfactual Learning",

author = "Deepak Kumar and Tessa Grosz and Elisabeth Greif and Navid Rekabsaz and Markus Schedl",

year = "2023",

language = "English",

booktitle = "Proceedings of the 3rd Workshop on Recommender Systems for Human Resources (RecSys in HR @ RecSys 2023),",

}

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

TY - GEN

T1 - Identifying Words in Job Advertisements Responsible for Gender Bias in Candidate Ranking Systems via Counterfactual Learning

AU - Kumar, Deepak

AU - Grosz, Tessa

AU - Greif, Elisabeth

AU - Rekabsaz, Navid

AU - Schedl, Markus

PY - 2023

Y1 - 2023

M3 - Conference proceedings

BT - Proceedings of the 3rd Workshop on Recommender Systems for Human Resources (RecSys in HR @ RecSys 2023),

ER -