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Notions of research quality are contextual in many respects: they vary between fields of research, between review contexts and between policy contexts. Yet, the role of these co-existing notions in research, and in research policy, is poorly understood. In this paper we offer a novel framework to study and understand research quality across three key dimensions. First, we distinguish between quality notions that originate in research fields (Field-type) and in research policy spaces (Space-type). Second, drawing on existing studies, we identify three attributes (often) considered important for 'good research': its originality/novelty, plausibility/reliability, and value or usefulness. Third, we identify five different sites where notions of research quality emerge, are contested and institutionalised: researchers themselves, knowledge communities, research organisations, funding agencies and national policy arenas. We argue that the framework helps us understand processes and mechanisms through which 'good research' is recognised as well as tensions arising from the co-existence of (potentially) conflicting quality notions. 3Co-existing Notions of Research Quality dimensions of our framework, encompassing: (i) types of quality notions; (ii) attributes of quality; and (iii) sites where notions are established and institutionalised. Third, we combine these three dimensions into an overall framework to study and understand research quality notions. We then discuss ways in which this proposed approach stands to change the research agenda.

This paper provides a detailed analysis of the change process of academic science. The change pressures currently visible in UK science have been conceptualised as the product of three interdependent dynamics: a shift towards neo‐liberal ideologies and discourses of government; a process of reconstitution of the relationship between government and science; and the resulting reshaping of science itself. Focusing on the universities and academic science, we argue that this process of transformation has adverse consequences the end result of which may be a loss of capacity within the science system to maintain knowledge bases.