Analysing Grant Peer Review Reports Using Machine Learning
Project Summary: Peer review plays an essential role in grant evaluation. External peer review reports by international experts contribute to assessing the feasibility and quality of grant applications and provide an essential basis for funding decisions. In addition, they help justify rejections and provide feedback, which may help applicants improve their research. Peer review thus has the power to influence which researchers and what kind of research receives funding and can subsequently be conducted. For funding organisations, peer review must fulfil these functions. Peer review reports should also be in line with their understanding of quality. Peer review should also enable fair, transparent, and efficient funding decisions and foster diversity in research (ideas, methodologies, and approaches) and researchers.
This research project is a collaboration between University College Dublin and the
Swiss National Science Foundation. The project will analyse the texts of anonymised grant review reports along several dimensions using human coding and machine learning. We seek to conceptualise characteristics of grant peer review reports and classify a large corpus of review reports. The project investigates whether strategic initiatives and new evaluation procedures have the desired effects on the content and structure of review reports.
Project Funding: €276,000
Assessing and Explaining Environmental and Energy Policies in Comparative Perspective
Project Summary: Political parties, politicians, companies, and interest groups increasingly discuss how to achieve a net-zero carbon emissions future, but systematic evidence that tracks these political debates is still lacking. The project “Assessing and Explaining Environmental and Energy Policies in Comparative Perspective” seeks to identify the problems political actors raise and solutions they offer regarding renewable energy, sustainability, and water treatment. The project will also assess how companies and interest groups aim to reduce greenhouse gas emissions and help mitigate the impacts of climate change. By combining quantitative text analysis, human coding, and supervised machine learning, it will define and map (proposed) policies relating to the environment and sustainability, and provide recommendations for policymakers.
The project is part of
NexSys, a newly established
All Island SFI Strategic Partnership Programme. NexSys focuses on the transition to a net zero carbon energy system. It is a unique partnership bringing together a multidisciplinary research team, industry, and policymakers to tackle fundamental research questions to be addressed as part of the transition to net Zero. Hosted by
UCD Energy Institute, NexSys brings together academics from nine institutions across the Island of Ireland (University College Dublin, Trinity College Dublin, Dublin City University, ESRI, Maynooth University, University College Cork, NUI Galway, Ulster University and Queen’s University Belfast) to work together to meet the unprecedented scale and complexity of the challenges associated with the energy transition.
Project Funding: €183,000 (total funding: €16 million)
