Open Science holds the promise to make scientific endeavours more inclusive, participatory, understandable, accessible and re-usable for large audiences. However, making processes open will notper sedrive wide reuse or participation unless also accompanied by the capacity (in terms of knowledge, skills, financial resources, technological readiness and motivation) to do so. These capacities vary considerably across regions, institutions and demographics. Those advantaged by such factors will remain potentially privileged, putting Open Science's agenda of inclusivity at risk of propagating conditions of ‘cumulative advantage’. With this paper, we systematically scope existing research addressing the question: ‘What evidence and discourse exists in the literature about the ways in which dynamics and structures of inequality could persist or be exacerbated in the transition to Open Science, across disciplines, regions and demographics?’ Aiming to synthesize findings, identify gaps in the literature and inform future research and policy, our results identify threats to equity associated with all aspects of Open Science, including Open Access, Open and FAIR Data, Open Methods, Open Evaluation, Citizen Science, as well as its interfaces with society, industry and policy. Key threats include: stratifications of publishing due to the exclusionary nature of the author-pays model of Open Access; potential widening of the digital divide due to the infrastructure-dependent, highly situated nature of open data practices; risks of diminishing qualitative methodologies as ‘reproducibility’ becomes synonymous with quality; new risks of bias and exclusion in means of transparent evaluation; and crucial asymmetries in the Open Science relationships with industry and the public, which privileges the former and fails to fully include the latter.

Open Science (OS) aims, in part, to drive greater societal impact of academic research. Government, funder and institutional policies state that it should further democratize research and increase learning and awareness, evidence-based policy-making, the relevance of research to society's problems, and public trust in research. Yet, measuring the societal impact of OS has proven challenging and synthesized evidence of it is lacking. This study fills this gap by systematically scoping the existing evidence of societal impact driven by OS and its various aspects, including Citizen Science (CS), Open Access (OA), Open/FAIR Data (OFD), Open Code/Software and others. Using the PRISMA Extension for Scoping Reviews and searches conducted in Web of Science, Scopus and relevant grey literature, we identified 196 studies that contain evidence of societal impact. The majority concern CS, with some focused on OA, and only a few addressing other aspects. Key areas of impact found are education and awareness, climate and environment, and social engagement. We found no literature documenting evidence of the societal impact of OFD and limited evidence of societal impact in terms of policy, health, and trust in academic research. Our findings demonstrate a critical need for additional evidence and suggest practical and policy implications.

Open Research aims to make research more accessible, transparent, reproducible, shared and collaborative. Doing so is meant to democratize and diversify access to knowledge and knowledge production, and ensure that research is useful outside of academic contexts. Increasing equity is therefore a key aim of the Open Research movement, yet mounting evidence demonstrates that the practices of Open Research are implemented in ways that undermine this. In response, we convened a diverse community of researchers, research managers and funders to co-create actionable recommendations for supporting the equitable implementation of Open Research. Using a co-creative modified Delphi method, we generated consensus-driven recommendations that address three key problem areas: the resource-intensive nature of Open Research, the high cost of article processing charges, and obstructive reward and recognition practices at funders and research institutions that undermine the implementation of Open Research. In this paper, we provide an overview of these issues, a detailed description of the co-creative process, and present the recommendations and the debates that surrounded them. We discuss these recommendations in relation to other recently published ones and conclude that implementing ours requires ‘global thinking’ to ensure that a systemic and inclusive approach to change is taken.

Many people purchase fair trade certified products because they trust that doing so makes a difference in the lives of small producers around the world. Sociologists Nicki Lisa Cole and Keith Brown discuss how changes to certification policy have modified the meaning of fair trade in a way that has troubling implications for small coffee farmers.

The integrative review presented here examines how reproducibility and replicability are conceptualized and discussed in relation to qualitative research, and which factors and practices enable or undermine them. Both peer-reviewed and grey English-language literature that address reproducibility and/or Open Science in relation to qualitative research were eligible for inclusion. Initial searches were conducted in Scopus, Web of Science, Dimensions, PubMed, APA PsychInfo, and JSTOR, and followed with snowball sampling from included literature. Studies were screened and both quantitative and qualitative data were extracted using the SyRF online platform, with 248 papers included. We found that conceptualizations that stem from quantitative standpoints are overwhelmingly framed as inappropriate practices and epistemic criteria for (most) qualitative research. When conceptualized in alternative ways that are adapted to the epistemic conditions, aims and practices of qualitative research, they can be both applicable and appropriate. Key barriers include the ontological and epistemological misalignment of reproducibility, replicability and Open Science and qualitative research, and ethical and practical concerns surrounding data sharing and reuse. Key enablers include practices that respond to ethical and practical concerns around data sharing and reuse (anonymization, ethical consent practices, context documentation, and ethical access management), adapting expectations and norms of openness, and established qualitative practices including documentation, reflexivity, and considering positionality. We conclude that reproducibility, replicability and Open Science practices must be adapted to the aims and epistemic conditions of qualitative research for them to be applicable and feasible, and that they will not always be both for all qualitative research.

Open Science holds the promise to make scientific endeavours more inclusive, participatory, understandable, accessible, and re-usable for large audiences. However, making processes open will not per se drive wide re-use or participation unless also accompanied by the capacity (in terms of knowledge, skills, financial resources, technological readiness and motivation) to do so. These capacities vary considerably across regions, institutions and demographics. Those advantaged by such factors will remain potentially privileged, putting Open Science’s agenda of inclusivity at risk of propagating conditions of “cumulative advantage”. With this paper, we systematically scope existing research addressing the question: “What evidence and discourse exists in the literature about the ways in which dynamics and structures of inequality could persist or be exacerbated in the transition to Open Science, across disciplines, regions and demographics?” Aiming to synthesise findings, identify gaps in the literature, and inform future research and policy, our results identify threats to equity associated with all aspects of Open Science, including Open Access, Open/FAIR Data, Open Methods, Open Evaluation, Citizen Science, as well as its interfaces with society, industry and policy. Key threats include: stratifications of publishing due to the exclusionary nature of the author-pays model of Open Access; potential widening of the digital divide due to the infrastructure-dependent, highly situated nature of open data practices; risks of diminishing qualitative methodologies as “reproducibility” becomes synonymous with quality; new risks of bias and exclusion in means of transparent evaluation; and crucial asymmetries in the Open Science relationships with industry and the public, which privileges the former and fails to fully include the latter.