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Impact Rankings 2024: reduced inequalities (SDG 10) methodology

June 5, 2024
SDG 10 reduced inequalities
Source: Sam Chivers (edited)

Browse the full results of the Impact Rankings 2024


This ranking focuses on universities¡¯ research on social inequalities, their policies on discrimination and their commitment to recruiting staff and students from under-represented groups.

View the?methodology for the Impact Rankings 2024?to find out how these data are used in the overall ranking.

Metrics

Research on reduced inequalities (27%)

  • Proportion of papers in the top 10?per cent of?journals as defined by Citescore (10%)
  • Field-weighted citation index of papers produced by?the university (10%)
  • Number of publications (7%)

This focuses on research that is relevant to reduced inequalities. The field-weighted citation index is a subject-normalised score of the citation performance of publications.

The data are provided by Elsevier¡¯s Scopus dataset, based on a query of keywords associated with SDG?10 (reduced inequalities) and supplemented by additional publications identified by artificial intelligence. The data include all indexed publications between 2018 and 2022. The data are normalised across the range using Z-scoring.

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First-generation students (15.5%)

To see how the university is addressing economic inequality, we measure the number of students starting a?degree who identify as being the first person in their immediate family to attend university, divided by the total number of students starting a?degree. 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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Students from developing countries (15.5%)

This is defined as the proportion of international students at all degree levels from low-income and lower-middle-income countries, as defined by the World Bank. To be included, these students must be receiving financial aid that significantly supports them. All data are provided as full-time equivalents.

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

Students and staff with disabilities (23%)

  • Proportion of students with disabilities (11.5%)
  • Proportion of employees with disabilities (11.5%)

The student indicator is defined as the number of students with disabilities at all degree levels, divided by the total number of students at all degree levels. The employee indicator is defined as the number of employees with disabilities, divided by the total number of employees. 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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Measures against discrimination (19%)

  • Non-discriminatory admissions policy (1.9%)
  • Track application and admission rates of under-represented groups (1.9%)
  • Planned action to recruit students and staff from under-represented groups (1.9%)
  • Anti-discrimination and anti-harassment policies for staff and students (1.9%)
  • The existence of a diversity and equality committee or officer (1.9%)
  • Provide mentoring or other support programmes aimed at students and staff from under-represented groups (1.9%)
  • Accessible facilities for people with disabilities (1.9%)
  • Support services for people with disabilities (1.9%)
  • Access schemes for people with disabilities (1.9%)
  • Accommodation policy or strategy for people with disabilities, including adequate funding (1.9%)

In 2022, ¡°newly settled refugees¡± was added to our definition of under-represented groups. The evidence was provided directly by universities, evaluated and scored by?THE?and not normalised.


Evidence

When we ask about policies and initiatives ¨C for example, the existence of mentoring programmes ¨C our metrics require universities to provide the evidence to support their claims. In these cases, we give credit for the evidence, and for the evidence being public. These metrics are not usually size-normalised.

Evidence is evaluated against a set of criteria, and decisions are cross-validated where there is uncertainty. Evidence need not be exhaustive ¨C we are looking for examples that demonstrate best practice at the institutions concerned.

Time frame

In general, the data used refer to the closest academic year to January to December 2022. The date range for each metric is specified in the full methodology document.

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Exclusions

The ranking is open to any university that teaches at undergraduate or postgraduate level. Although research activities form part of the method?ology, there is no?minimum research requirement for participation.

THE?reserves the right to exclude universities that it believes have falsified data, or are no longer in good standing.

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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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