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We argue that statistical practice in the social and behavioural sciences benefits from transparency, a fair acknowledgement of uncertainty and openness to alternative interpretations. Here, to promote such a practice, we recommend seven concrete statistical procedures: (1) visualizing data; (2) quantifying inferential uncertainty; (3) assessing data preprocessing choices; (4) reporting multiple models; (5) involving multiple analysts; (6) interpreting results modestly; and (7) sharing data and code. We discuss their benefits and limitations, and provide guidelines for adoption. Each of the seven procedures finds inspiration in Merton's ethos of science as reflected in the norms of communalism, universalism, disinterestedness and organized scepticism. We believe that these ethical considerations-as well as their statistical consequences-establish common ground among data analysts, despite continuing disagreements about the foundations of statistical inference.Wagenmakers and colleagues describe seven statistical procedures that increase transparency in data analysis. These procedures highlight common ground among data analysts from different schools and find inspiration in Merton's ethos of science.

Sharing of key evidence on strategies for reducing resources consumption and lowering carbon footprint is essential to alleviating risks of increasing urbanization, population growth and looming climate change impacts. However, finding scientifically robust research and distilling knowledge to draw confident conclusions in a reasonable timeframe is challenging due to the sheer volume of rapidly accumulating research evidence. Primary evidence is aggregated in secondary studies, i.e. various types of reviews, including systematic reviews and meta-analyses. However, the number of secondary studies is also growing rapidly and their quality varies. This work presents the first systematic review of secondary studies which were claimed to be systematic reviews or meta-analyses of literature relevant to reducing carbon footprint of the built environment or its co-benefits (e.g., health and well-being). The resulting searchable and updatable database contains 131 reviews published between 2001 and early 2018. Importantly, the quality of the included reviews was assessed and categorized. The database is available via a dedicated website which includes interactive visualizations and filtering tools. In its current form, the interactive map and database can help discovery and appraisal of secondary evidence for decision-making and research use, supporting transition to low carbon future. This overview aimed to reveal trends and patterns, including gaps, in the publications of research syntheses relevant to sustainable built environment. The results showed that the number of reviews claiming to by systematic reviews or meta-analyses is rapidly increasing in recent years. However, the exact methodology used and the standard of adherence to methodological and reporting guidelines varies widely among reviews. The included reviews span different disciplines, such as environmental sciences, engineering, urban planning, public health, and social sciences. The first authors from USA, UK and Australia contributed the most relevant reviews. Health and well-being, along with closely related environment and nature, are currently the best synthesized subject areas, while there are still very few included reviews related to policy, economy or information technology, indicating synthesis gaps in these areas. Our analysis reveals the lack of standardized definitions of different types of research syntheses across disciplines, as well as poor reporting quality of research syntheses. We encourage detailed descriptions of methods, providing datasets and interactive visualizations as integral components of the future systematic reviews and evidence maps.