Context In order to test how gender is linguistically encoded and represented, I have designed a series of studies that involve gender biased and equibiased names. This dataset is designed to help me calculate which names would be most appropriate for stimuli created to display to both US and UK audiences. Content These data contain name frequencies and ranks by year (1996-2013, UK) or decade (2000, US) by binary gender (male or female). I have tried to design these data to provide the most useful metrics for determining the most popular names by gender bias (masculine, feminine) and equibias (unisex). Acknowledgements - Office for National Statistics (2016a). Baby Names Statistics Boys. Live births (datasets). Retrieved 19 Feb 2017 from: [https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/livebirths/datasets/babynamesenglandandwalesbabynamesstatisticsboys][1] - Office for National Statistics (2016b). Baby Names Statistics Girls. Live births (datasets). Retrieved 19 Feb 2017 from: [https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/livebirths/datasets/babynamesenglandandwalesbabynamesstatisticsgirls][2] - U.S. Census Bureau, Population Division, Population Analysis & Evaluation Staff (2000). via Butler, R. (2016). First name search. Retrieved 13 March 2017 from: [http://names.mongabay.com/baby-names/application/][3] [1]: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/livebirths/datasets/babynamesenglandandwalesbabynamesstatisticsboys [2]: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/livebirths/datasets/babynamesenglandandwalesbabynamesstatisticsgirls [3]: http://names.mongabay.com/baby-names/application/ Inspiration I'm looking to identify popular gender-biased and popular gender neutral (equi-biased) names.