By Maria Priestley and Gefion Thuermer, King’s College London
Researchers from King’s College London have worked on a study investigating ways to model the factors that can predict the success of applications in innovation programmes like MediaFutures. The growing availability of administrative data from open innovation programmes is creating new opportunities for enhancing and auditing their selection practices. Previous research has explored the use of past data to build predictive models for shortlisting applicants and allocating resources more efficiently during review. Another avenue of research relates to interpreting the model parameters to ensure that the trends detected in past data align with the intended objectives of public funders.
The whitepaper the team is working on presents a quantitative investigation of open call applications and selection decisions from three EU-funded data incubators that operated between the years of 2016 to 2021. a quantitative investigation of open call applications and selection decisions from three EU-funded data incubators that operated between the years of 2016 to 2021. Using data from 725 applications received by the DMS Accelerator, DataPitch and ODINE programmes, it presents a methodological approach for quantifying unstructured aspects of application texts and team characteristics, and for measuring their explanatory power in predicting the acceptance or rejection of an applicant. It also discusses tools for obtaining demographic metrics from applicants’ names where explicit data on equality, diversity and inclusion (EDI) are unavailable. …
