This paper considers three common types of claim to research knowledge, and the relative difficulty of making each type of claim in an empirically and logically justified manner. Before this, the paper looks at some more general issues often raised when discussing knowledge in social science, such as the nature of truth and justified belief, the existence of “isms” and paradigms treated like fashion accessories that one can adopt or not at will, and the intrinsic limitations of how we get to know about the “stuff” we might want to make research claims about. The idea of this early section is to remove some potential obstacles, before arguing that none of these issues is relevant to the rest of the paper about the nature of claims in their most generic form, independent of things like specific methods of data collection.   The first type of claim we identify is a fully descriptive one that only summarises the data observed. This is the easiest and safest kind of claim, but even these might suffer from non-random errors and inaccuracies. However, their biggest limitation is their lack of any wider utility. The second kind of claim is a generally descriptive one that makes statements about unobserved data on the basis of a fully descriptive claim. Here we meet Hume’s problem of induction. These claims have two parts, and the inductive part cannot seemingly be justified by logic, inferential statistics (whether Fisher or Neyman-Pearson style), Carnap’s inductive probabilities, or even necessarily by Popper’s falsification process. The third type is a causal claim, which we argue must also be a general claim. We develop a model, based on the work of Mill and Bradford-Hill, of what a plausible causal claim entails. But it still has all of the problems emerging from the first two types of claim, and adds a further problem created by our inability to assess causes directly. The paper concludes by suggesting how social science can proceed most safely in practice.

Background: England has an ethnically diverse population; reflected in the teacher workforce, and the student body in schools. However, it is not clear that these figures are in proportion to each other. This paper examines the ethnic profile of students and their teachers and considers their geographical distribution. Methods: This paper uses existing aggregated official publicly available datasets to describe the patterns and trends in the proportion of ethnic minority teachers compared to ethnic minority pupils in England 2015-2021. Data comes from the Department for Education (DfE), the University and Colleges Admissions Service (UCAS), the Organisation for Economic Co-operation and development (OECD/TALIS), and the Office for National Statistics (ONS). Results: Compared to the student intakes to schools, we found that there are more White British teachers than expected. This disproportion (where there are more White British teachers among teachers than there are White British pupils among pupils) is worse for promoted school leaders like deputies and headteachers than it is for classroom teachers. In London, due to the exceptional number of ethnic minority students, the disproportion (or mismatch) is worse in London than anywhere else. Areas with the fewest ethnic minority pupils (and teachers), like the North East, have the most proportionate workforce (in this limited sense). Conclusions: A student lacking any teachers of the same ethnic group might be treated differently at school, and there is some evidence that this might affect their attainment outcomes. The lack of ethnic diversity in some schools and areas, regardless of proportions, may impoverish the diversity of the whole school system. Several possible reasons for these patterns are noted in the paper, but it is clear that ethnic minority applicants to teacher training are less likely to be accepted, and less likely to obtain qualified teacher status or an eventual teaching post.

Background: England has an ethnically diverse population; reflected in the teacher workforce, and the student body in schools. However, it is not clear that these figures are in proportion to each other. This paper examines the ethnic profile of students and their teachers and considers their geographical distribution. Methods: This paper uses existing aggregated official publicly available datasets to describe the patterns and trends in the proportion of ethnic minority teachers compared to ethnic minority pupils in England 2015-2021. Data comes from the Department for Education (DfE), the University and Colleges Admissions Service (UCAS), the Organisation for Economic Co-operation and development (OECD/TALIS), and the Office for National Statistics (ONS). Results:  We found that there are proportionately more White British teachers than in the student intakes to schools. This disproportion (where there are more White British teachers among teachers than there are White British pupils among pupils) is worse for promoted school leaders like deputies and headteachers than it is for classroom teachers. In London, due to the exceptional number of ethnic minority students, the disproportion (or mismatch) is worse in London than anywhere else. Areas with the fewest ethnic minority pupils (and teachers), like the North East, have the most proportionate workforce (in this limited sense). Conclusions: A student lacking any teachers of the same ethnic group might be treated differently at school, and there is some evidence that this might affect their attainment outcomes. The lack of ethnic diversity in some schools and areas, regardless of proportions, may impoverish the diversity of the whole school system. Several possible reasons for these patterns are noted in the paper, but it is clear that ethnic minority applicants to teacher training are less likely to be accepted, and less likely to obtain qualified teacher status or an eventual teaching post.

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