University of Central Lancashire Responsible Research ..., Study notes of Innovation

Download University of Central Lancashire Responsible Research ... and more Study notes Innovation in PDF only on Docsity! University of Central Lancashire Responsible Research Metrics Policy Document type Policy Document owner Research Services Approved by University Research & Innovation Committee Approval date 14th October 2020 Review date October 2021 Version 2020.01 Summary of changes Responsible Use of Research Metrics In consultation with the academic body, the University of Lancashire has launched a policy statement on the Responsible Use of Research Metrics. Responsible use of research metrics is a policy area that has been rapidly rising up the Higher Education agenda in recent years with increasing pressure from policy makers and funders for institutions to develop responsible metric statements. Research metrics in our statement encompasses the full range of quantitative indicators that might be used to measure research activity, including but not limited to indicators of output volume/quality, income generation and doctoral supervision. The statement is intended to apply to all disciplines, from STEM to Arts and Humanities. Research metrics are already in use across the sector both formally and informally, for example in supporting recruitment and promotion decisions. However, metrics alone are often inadequate or may be used incorrectly, unfairly disadvantaging researchers depending on their career stage, discipline or protected characteristics. This Responsible Use of Research Metrics statement sets out ten key principles based on the Leiden Manifesto1 that we will use to inform how metrics are used in measurement of research activity across the University. An Action Plan and Monitoring Framework are being developed to support our implementation of the Responsible Use of Research Metrics. The principles have been revisited to reflect the comments received in the Responsible Use of Research Metrics survey of our research staff. Any questions or comments can be addressed to Annette Ramsden (Scholarly Communications Unit) or Allison McCaig (Research Excellence Unit). 1 See www.leidenmanifesto.org/ 5. Allow those evaluated to verify data and analysis. Our ambition is that tools used to collect and monitor research activity at the University will be made openly available and researchers encouraged to question indicators used in relation to their research activity, verify the accuracy of data relating to themselves and make corrections if required. Staff managing data collection and evaluation will aim to ensure accuracy and robustness of the data. Researchers should register for an ORCID ID to ensure consistent, reliable attribution of their work and are encouraged to work with the relevant Professional Service to ensure their details on systems such as CLoK, UCLanData and iTrent, and external sources are accurate. 6. Account for variation by field in publication and citation practices. We recognise that publication and citation practices vary between disciplines and develop on a range of timescales. and that certain research indicators and sources of data underpinning those practices may work well for some forms of research outputs whilst being unsuitable for others. We will not promote the use of one measure over another and will follow best practice through working with the research community to select research quality indicators and data sources. The availability of research metrics will not drive our decision making about research activities and priorities, and metrics will play a supporting role only in that decision making. There may be certain circumstances where the use of metrics is not appropriate in relation to decision making. 7. Base assessment of individuals on qualitative judgement of their portfolio. We recognise that research quality indicators such as the h-index are affected by career stage, FTE/workload, gender and other protected characteristics, as well as discipline and database/source, and will seek to take these factors into account when interpreting metrics. Reading and judging a researcher's work is much more appropriate than relying on a single figure. It is also recognised that academics undertake a wide range of research activities, not all of which can be easily measured or benchmarked. We recognise that consideration must be given to the full range of activities, expertise, experience, influence and engagement of individual researchers when assessing an individual’s performance. 8. Avoid misplaced concreteness and false precision. Considering the wide variations in the quality and scope of available data, the University will undertake the practice of using multiple indicator sources (where available) to provide a contextualised, robust and accurate picture of research quality. We will avoid using over precise numbers that give an illusion of accuracy. 9. Recognise the systemic effects of assessment and indicators. It is accepted that the process of measurement can itself affect the system being measured through the incentives that are created, especially if a single indicator is used These effects should be anticipated, and to minimise such effects, a suite of possible indicators or basket of metrics will be utilised where practical. 10. Scrutinise indicators regularly and update them. As the range and availability of quantitative research indicators evolves, the University commits to the regular review and, where appropriate, the revision of indicators used. Annex A Responsible metrics can be understood in terms of the following dimensions: • Robustness: basing metrics on the best possible data in terms of accuracy and scope; • Humility: recognising that quantitative evaluation should support – but not supplant – qualitative, expert assessment; • Transparency: keeping data collection and analytical processes open and transparent, so that those being evaluated can test and verify the results; • Diversity: accounting for variation by field, and using a range of indicators to reflect and support a plurality of research and researcher career paths across the system; • Reflexivity: recognising and anticipating the systemic and potential effects of indicators, and updating them in response.