Browse the full Impact Rankings 2020 results

This ranking focuses on universities¡¯ role as an engine for economic growth and their responsibilities as employers. It explores institutions¡¯ economics research, their employment practices and the share of students taking work placements.

Please view the methodology?for the Impact Rankings 2020 to find out how these data are used in the overall ranking.?

Metrics

Research on economic growth and employment (27%)

• Proportion of papers in the top 10 per cent of journals as defined by Citescore (14%)
• Number of publications (13%)

This focuses on research that is relevant to economic growth and employment, measuring the proportion of publications in the top 10 per cent of journals and the volume of research produced.

The data are provided by Elsevier¡¯s Scopus dataset, based on a query of keywords associated with SDG 8 (decent work and economic growth). The dataset includes all indexed publications between 2014 and 2018. The data are normalised across the range using Z-scoring.

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Employment practices (19.6%)

• Payment of a living wage to staff and faculty (2.45%)
• Recognition of union and labour rights (2.45%)
• Policy on ending discrimination in the workplace (2.45%)
• Policy against modern slavery, forced labour, human trafficking and child labour (2.45%)
• Guarantees of equal rights for outsourced labour workers (2.45%)
• Policy on pay scale equity, including commitment to measure and eliminate gender pay gaps (2.45%)
• Measure or track pay scale gender equity (2.45%)
• Process for employees to appeal decisions on rights and pay (2.45%)

The data and evidence for these metrics were provided directly by universities. The evidence was evaluated and scored by Times ÖйúAƬ and is not normalised.

Expenditure per employee (15.4%)

This metric is calculated by dividing the university expenditure by the number of employees. It is then normalised by the regional GDP per capita. It aims to explore the extent to which the university is a significant economic driver locally.

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The data were provided directly by universities and normalised across the range using Z-scoring.

Proportion of students taking work placements (19%)

In order to understand if universities are preparing students for the world of work, we asked for the number of students with an employment placement of more than a month required as part of their studies, divided by the total number of students. All data are provided as full-time equivalents.

The data were provided directly by universities and normalised across the range using Z-scoring.

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Proportion of employees on secure contracts (19%)

The casualisation of the university workforce is a growing concern so we asked universities to supply the number of employees (both academic and non-academic) on contracts of more than 24 months, divided by the total number of employees. All numbers are provided as full-time equivalents. This explicitly excludes short-term contracts required to cover for maternity or paternity leave.

The data and evidence were provided directly by universities. The data are normalised across their range using Z-scoring.

Evidence

When we ask about policies and initiatives, our metrics require universities to provide the evidence to support their claims. Evidence is evaluated against a set of criteria and decisions are cross validated where there is uncertainty. Evidence is not required to be exhaustive ¨C we are looking for examples that demonstrate best practice at the institutions concerned.

Timeframe

Unless otherwise stated, the data used refer to the closest academic year to January to December 2018.

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Exclusions

Universities must teach undergraduates and be validated by a recognised accreditation body to be included in the ranking.

Data collection

Institutions provide and sign off their institutional data for use in the rankings. On the rare occasions when a particular data point is not provided, we enter a value of zero.

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