Cranfield Online Research Data (CORD)
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The EPSRC's responsible innovation framework: to what extent does it influence research practice?. Survey data

posted on 2023-04-05, 09:24 authored by David Rose, Faye Shortland, Rachel Smith, Juliette Schillings

Method: We also undertook an online Qualtrics survey of UK EPSRC-funded researchers and PhD students between September and November 2022. The survey was circulated via social media, by emailing interviewees, and by contacting CDT/DTP leads or administrators. Questions are shown in Appendix B. We received 138 responses (103 PhD students, 35 researchers/academics). In total, 30 institutions were represented in the responses with the top five institutions accounting for 76 responses and no more than 20 responses from any one single institution. At least 43[1] disciplines were covered. The gender response split was 87 Male, 43 Female, 2 Non-binary/non-conforming, with 5 preferring not to say or selecting other (no further detail provided). Descriptive statistics are provided for close-ended questions and open-ended answers were thematically coded.

Software used: Qualtrics

Format: Excel spreadsheet. Q1 and 2 were administrative questions and are not included.

Anonymisation: Some open-ended question responses are removed or edited due to the possibility of identification. Where edits have been made, they are marked with xxx. 

· Q11: part anonymisation due to one answer giving identifiable information. 

· Q12_2: part anonymisation due to one answer giving identifiable information.

· Q14: on training, fully removed as many answers identified their university or CDT.

· Q20: giving further information, fully removed as many answers contained identifiable information.

Q21: asked to name university. One respondent asked for this to be removed as it was too easy to identify themselves from a combination of discipline and university. Hence, the answers to this were fully removed for all.

[1] Taking the first discipline given, as described by respondents (136 gave responses): Aeronautical engineering (1), Aerosol science (1), AI (2), Atmospheric Science (1), Automotive Engineering (1), Behavioural Science (1), Biochemical engineering (5), Biology (2), Biomaterials Science (1), Biomedical Science (4), Chemical Biology (1), Chemical Engineering (1), Chemistry (12), Computational Materials Modelling (1), Computer Science (13), Computing (5), Cybersecurity (2), Data Science (1), Economics (1), Electronic Engineering (3), Engineering (10), Environmental Science (1), Geography (1), Geospatial engineering (1), HCI (2), Health technology (2), Immunology (2), International relations (1), Machine Learning (3), Materials Science (6), Mathematical sciences (1), Mathematics (11), Mechanical engineering (2), Medical imaging (1), Neuroscience (3), Pharmaceutical Sciences (2), Physics (8), Psychology (9), Risk Analysis (1), Robotics (5), Social sciences (1), Sociology (1), Statistics (3).


British Academy/Leverhulme Small Research Grant: SRG20\200074


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