Reproducible science requires transparent reporting. The ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour, and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved. Here, we introduce ARRIVE 2.0. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise and divide the items of the guidelines into 2 sets, the “ARRIVE Essential 10,” which constitutes the minimum requirement, and the “Recommended Set,” which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration document, which serves (1) to explain the rationale behind each item in the guidelines, (2) to clarify key concepts, and (3) to provide illustrative examples. We aim, through these changes, to help ensure that researchers, reviewers, and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.

https://openscience.bmj.com/content/bmjos/4/1/e100115.full.pdf

The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research

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The Uses Of Argument

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The Scientific Image

One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.

Reproducibility and Replicability in Science

Bayes or Bust?-A Critical Examination of Bayesian Confirmation Theory.

We surveyed 807 researchers (494 ecologists and 313 evolutionary biologists) about their use of Questionable Research Practices (QRPs), including cherry picking statistically significant results, p hacking, and hypothesising after the results are known (HARKing). We also asked them to estimate the proportion of their colleagues that use each of these QRPs. Several of the QRPs were prevalent within the ecology and evolution research community. Across the two groups, we found 64% of surveyed researchers reported they had at least once failed to report results because they were not statistically significant (cherry picking); 42% had collected more data after inspecting whether results were statistically significant (a form of p hacking) and 51% had reported an unexpected finding as though it had been hypothesised from the start (HARKing). Such practices have been directly implicated in the low rates of reproducible results uncovered by recent large scale replication studies in psychology and other disciplines. The rates of QRPs found in this study are comparable with the rates seen in psychology, indicating that the reproducibility problems discovered in psychology are also likely to be present in ecology and evolution.

/pdf/questionable-research-practices-in-ecology-and-evolution-45fvs4vxdr.pdf

Questionable Research Practices in Ecology and Evolution

Recent large-scale projects in other disciplines have shown that results often fail to replicate when studies are repeated. The conditions contributing to this problem are also present in ecology, but there have not been any equivalent replication projects. Here, we survey ecologists' understanding of and opinions about replication studies. The majority of ecologists in our sample considered replication studies to be important (97%), not prevalent enough (91%), worth funding even given limited resources (61%), and suitable for publication in all journals (62%). However, there is a disconnect between this enthusiasm and the prevalence of direct replication studies in the literature which is much lower (0.023%: Kelly 2019) than our participants' median estimate of 10%. This may be explained by the obstacles our participants identified including the difficulty of conducting replication studies and of funding and publishing them. We conclude by offering suggestions for how replications could be better integrated into ecological research.

/pdf/the-role-of-replication-studies-in-ecology-2mxmh7y1wt.pdf

The role of replication studies in ecology.

There is evidence suggesting that to the extent that scientists subscribe to a philosophy of science, most are likely to cite Popper’s falsificationism as their practiced methodology (e.g., Mulkay & Gilbert, 1981; Sovacool, 2005). At the same time, well-known lessons from the history of science demonstrate that real scientific practice bears little resemblance to Popperian prescriptions (e.g., Kuhn, 1962/2012), and that this has almost certainly benefited scientific progress (e.g., Lakatos, 1978). In this Commentary, we provide a brief outline of the four main models for establishing epistemic justification in science and explain the essential role that establishing null results plays in each. Popper’s falsificationist version of the hypothetico-deductive (HD) model of science is one of the models we discuss. We argue that although strict adherence to Popper’s HD model would not solve all the problems the “replication crisis” has thrown at the scientific community, scientists could do worse than follow his advice about bold conjectures and risky tests in establishing the absence (or presence) of effects. Null-hypothesis significance testing (NHST) as it is typically practiced is neither bold nor risky. We also add a plea for recognition of scientific activity outside of the HD model, which will help solve some of the deeper problems that have led to neglect of negative results.

The Epistemic Importance of Establishing the Absence of an Effect

Argument mapping is a way of diagramming the logical structure of an argument to explicitly and concisely represent reasoning. The use of argument mapping in critical thinking instruction has increased dramatically in recent decades. A brief history of argument mapping is provided at the end of this paper.

Using Computer-Aided Argument Mapping to Teach Reasoning

This paper explores the significance of narrative in collaborative reasoning using a qualitative case study of two teams of intelligence analysts who took part in an exercise using an online collaborative platform. Digital ethnographic methods were used to analyze the chat transcripts of analysts as they reasoned with evidence provided in a difficult, fictional intelligence-type problem and produced a final intelligence report. These chat transcripts provided a powerful "microscope" into the reasoning processes and interactions involved in complex, collaborative reasoning. We found that Individuals and teams used narrative to solve the kinds of complex problems organizations and intelligence agencies face daily. We observed that team members generated what we term "micro-narratives", which provided a means for testing, assessing and weighing alternative hypotheses through mental simulation in the context of collaborative reasoning. The creation of micro-narratives assisted in the teams' reasoning with evidence, an integral part of collaborative reasoning and intelligence analysis. Micro-narratives were combined into, and compared with, an ideal or 'virtual' narrative which informed the judgements the team came to in their final intelligence report. The case study developed in this paper provides evidence that narrative thought processes play an important role in complex collaborative problem-solving, reasoning with evidence and problem-solving. This is contrary to a widespread perception that narrative thinking is fundamentally distinct from formal, logical reasoning.

/pdf/the-role-of-narrative-in-collaborative-reasoning-and-27vg6ud59w.pdf

Ashley Barnett

Papers

Questionable Research Practices in Ecology and Evolution

The role of replication studies in ecology.

The Epistemic Importance of Establishing the Absence of an Effect

Using Computer-Aided Argument Mapping to Teach Reasoning

The role of narrative in collaborative reasoning and intelligence analysis: A case study