Message Framing Equality Initiatives 290426 | Newcastle University Business School

About this seminar

This seminar examines how the way equality initiatives are communicated influences engagement, support and resistance within organisations.

Speaker

Dr Zachary Petzel
School of Psychology, Newcastle University
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Zachary W. Petzel is a social psychologist based within the School of Psychology at Newcastle University whose research focuses on behaviour and attitude change, such as increasing support for diversity initiatives within academia and decreasing risky alcohol use among university students. Their work is often experimental, emphasising the use of neuroscience and emerging technologies (e.g., virtual reality).

Zac has very kindly offered to share with us insights from the programme of research he has conducted into EDI initiatives used in organisations. His past projects have included studies into:

how stereotypes and sexism affect mental and physical health of women in science, technology, engineering, and mathematics (STEM)
using virtual reality to improve intervention techniques to promote engagement with diversity initiatives in STEM
the impact of prejudiced large language models (e.g., ChatGPT) on racial minorities

Zac's talk would be relevant to colleagues and students working on (a) EDI-related topics, (b) organisational communication-related topics and (c) GenAI/LLM-related topics (see abstract below)

Abstract

This talk presents a programme of research examining how organisational messaging shapes engagement with EDI initiatives. Experiments test whether external versus internal motivational framing affects engagement with equality programs, in addition to introducing novel interventions (e.g., perspective-taking) which facilitate support for these initiatives. Experiments also focus on mechanisms which promote disengagement from initiatives, such as threat of losing career opportunities and perceived status within an organisation. Ongoing work will also be discussed, such as whether effects of message framing are present within large language models (e.g., ChatGPT) to understand how to maximise their efficiency and quality of outputs.