Contact: Ricardo Twumasi
Department: Psychosis Studies
Institution: King’s College London
Project timeline: January to March 2024
Project duration: 12 Weeks
Closing date: 15th December 2023
Expertise required: Qualitative data analysis, (Knowledge of Discourse Theory), Some basic experience of Python or another programming language.
Project description: The rhetoric which unions and employers use to discuss age and to defend their positions is relatively similar and unions use ageist stereotypes to defend early retirement and fight against raising pension ages. Based on the framework proposed by Collien, Sieben & Müller-Camen (2016) we are analysing the language that both employers and unions use to describe workers for ageist bias.
We have a large dataset based on interviews and responses to public consultations, using this data we are training a machine learning model to identify potentially ageist language.
Description of work involved: Data cleaning, qualitative analysis, Word2Vec deep learning
Student benefits: The benefits to the student would be authorship of a British Journal of Management paper. Attentance at the 7th International Conference of REIACTIS in Montréal in June 2024, and the opportunity to work with the Artificial Intelligence in Mental Health lab at King’s College London.