Turning interest into institutional change: teaching advocacy for sustainable research

• URL: http://arxiv.org/abs/2608.18601v1
• Date: Wed, 19 Aug 2026 06:44:30 GMT
• Title: Turning interest into institutional change: teaching advocacy for sustainable research
• Abstract summary: We present an open-access course that teaches the foundations of advocacy and organisational change.<n> Structured around the UNICEF five-step advocacy cycle, the course covers stakeholder analysis, power mapping, coalition building, storytelling, framing and messaging.<n>It is grounded in the UK policy landscape, including the Concordat for Environmental Sustainability and the UKRI Environmental Sustainability Strategy.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Systemic change across the digital research landscape is required to reduce the environmental impact of digital research, but while many researchers and technical professionals are motivated to act, they often lack the skills required to translate motivation into lasting organisational change. We present an open-access course that teaches the foundations of advocacy and organisational change to researchers, research software engineers, and research technical professionals. Structured around the UNICEF five-step advocacy cycle, the course covers stakeholder analysis, power mapping, coalition building, storytelling, framing and messaging, and evaluation. It is grounded in the UK policy landscape, including the Concordat for Environmental Sustainability and the UKRI Environmental Sustainability Strategy, and uses a fictional case study to make concepts concrete. The course is designed as a dual-layer resource in which workshop slides and extended self-study notes are contained in a single source material. A short pilot was delivered at the NetDRIVE Net Zero DRI Summer School in June 2026. The course is freely available under a CC BY 4.0 licence.

Related papers

• Enabling Organisational Change Through Ground-Up Initiatives: A Case Study from the STFC Scientific Computing Department [0.0]
  We present a case study from the Science and Technology Facilities Council's Scientific Computing Department.<n>This department consists of over 200 staff supporting tens of thousands of researchers.<n>We show how we developed the sustainability strategy for SCD across themes of emissions monitoring, user education, best practice, setting sustainability standards, and providing long-term support to sustainability work.
  arXiv  Detail & Related papers  (2026-08-24T15:20:21Z)
• FAIR+S: A validation study of a framework for sustainable research data and software [0.9449650062296823]
  FAIR principles already structure how digital research artefacts are described, shared, and reused.<n> FAIR+S weaves carbon-footprint and energy-use considerations directly into FAIR-aligned metadata.<n>This creates a foundation for reproducible research that simultaneously advances open science goals and decarbonisation objectives.
  arXiv  Detail & Related papers  (2026-06-17T09:30:47Z)
• Designing a Hardware Reverse Engineering Course: Lessons from Eight Years in a Rapidly Evolving Tech Domain [7.457885600788196]
  Hardware Reverse Engineering (HRE) is essential for detecting supply chain threats.<n>We present our HRE course focusing on digital circuit analysis and digital circuit extraction from ICs.
  arXiv  Detail & Related papers  (2026-06-02T14:18:23Z)
• AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discovery [184.2309450554096]
  AutoResearch is defined as the developmental spectrum of AI-powered scientific workflow automation.<n>We analyze how research systems redistribute control, evidence, execution, validation, and accountability across and organize the field.<n>We propose five evaluation dimensions--novelty, impact, reliability, and provenance--and show that AutoResearch autonomy is domain-conditioned.
  arXiv  Detail & Related papers  (2026-05-22T03:40:30Z)
• WisPaper: Your AI Scholar Search Engine [55.07907253175705]
  textscWisPaper is an intelligent academic retrieval and literature management platform.<n>It provides a closed-loop workflow that seamlessly connects literature discovery, management, and continuous tracking of research frontiers.<n>The platform is publicly accessible and serves researchers across academia and industry.
  arXiv  Detail & Related papers  (2025-12-07T15:10:20Z)
• Real Deep Research for AI, Robotics and Beyond [85.87181330763548]
  We present Real Deep Research (RDR) a comprehensive framework applied to the domains of AI and robotics.<n>The main paper details the construction of the RDR pipeline, while the appendix provides extensive results across each analyzed topic.
  arXiv  Detail & Related papers  (2025-10-23T17:59:05Z)
• Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices [70.24403396375277]
  The "Greening AI with Software Engineering" CECAM-Lorentz workshop was held February 3-7, 2025 in Lausanne, Switzerland.<n>This report presents a research agenda emerging from the workshop.<n>It outlines open research directions and practical recommendations to guide the development of environmentally sustainable AI-enabled systems.
  arXiv  Detail & Related papers  (2025-06-02T15:19:49Z)
• Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation [58.064940977804596]
  A plethora of new AI models and tools has been proposed, promising to empower researchers and academics worldwide to conduct their research more effectively and efficiently.<n>Ethical concerns regarding shortcomings of these tools and potential for misuse take a particularly prominent place in our discussion.
  arXiv  Detail & Related papers  (2025-02-07T18:26:45Z)
• Sustainability concepts for digital research infrastructures developed through ground-level stakeholder empowerment [0.10319088078614562]
  The UK Research and Innovation Digital Research Infrastructure (DRI) needs to operate sustainably in the future. This article presents the results of a research programme to give voice to the ground-level stakeholders of the DRI ecosystem. We find that giving a purposeful voice to the stakeholders for shaping their own future sustainable DRI environment can be achieved by a guided, expert-integrated, interactive and problem-focused workshop series.
  arXiv  Detail & Related papers  (2024-11-21T16:54:04Z)
• On the Opportunities of Green Computing: A Survey [80.21955522431168]
  Artificial Intelligence (AI) has achieved significant advancements in technology and research with the development over several decades. The needs for high computing power brings higher carbon emission and undermines research fairness. To tackle the challenges of computing resources and environmental impact of AI, Green Computing has become a hot research topic.
  arXiv  Detail & Related papers  (2023-11-01T11:16:41Z)
• Computer Science for Future -- Sustainability and Climate Protection in the Computer Science Courses of the HAW Hamburg [0.0]
  Computer Science for Future (CS4F) is an initiative in the Department of Computer Science at HAW Hamburg. The aim of the initiative is a paradigm shift in the discipline of computer science, thus establishing sustainability goals as a primary leitmotif for teaching and research. The change in teaching influences our research, the transfer to business and civil society as well as the change in our own institution.
  arXiv  Detail & Related papers  (2023-01-17T13:43:57Z)
• Deep Learning for Information Systems Research [12.509120097898482]
  Artificial Intelligence (AI) has rapidly emerged as a key disruptive technology in the 21st century. Deep Learning (DL) is an emerging class of algorithms that has enabled today's platforms and organizations to operate at unprecedented efficiency, effectiveness, and scale. Despite significant interest, IS contributions in DL have been limited, which we argue is in part due to issues with defining, positioning, and conducting DL research.
  arXiv  Detail & Related papers  (2020-10-07T15:23:05Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.