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A heated debate surrounds the significance of reproducibility as an indicator for research quality and reliability, with many commentators linking a “crisis of reproducibility” to the rise of fraudulent, careless, and unreliable practices of knowledge production. Through the analysis of discourse and practices across research fields, I point out that reproducibility is not only interpreted in different ways, but also serves a variety of epistemic functions depending on the research at hand. Given such variation, I argue that the uncritical pursuit of reproducibility as an overarching epistemic value is misleading and potentially damaging to scientific advancement. Requirements for reproducibility, however they are interpreted, are one of many available means to secure reliable research outcomes. Furthermore, there are cases where the focus on enhancing reproducibility turns out not to foster high-quality research. Scientific communities and Open Science advocates should learn from inferential reasoning from irreproducible data, and promote incentives for all researchers to explicitly and publicly discuss (1) their methodological commitments, (2) the ways in which they learn from mistakes and problems in everyday practice, and (3) the strategies they use to choose which research components of any project need to be preserved in the long term, and how.

The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and human resources management researchers, we aim to contribute to the respective bodies of knowledge to provide both employers and employees with a workable foundation to help with those problems they are confronted with. However, what research on research has consistently demonstrated is that the scientific endeavor possesses existential issues including a substantial lack of (a) solid theory, (b) replicability, (c) reproducibility, (d) proper and generalizable samples, (e) sufficient quality control (i.e., peer review), (f) robust and trustworthy statistical results, (g) availability of research, and (h) sufficient practical implications. In this chapter, we first sing a song of sorrow regarding the current state of the social sciences in general and personnel and human resources management specifically. Then, we investigate potential grievances that might have led to it (i.e., questionable research practices, misplaced incentives), only to end with a verse of hope by outlining an avenue for betterment (i.e., open science and policy changes at multiple levels).

It has been discovered that some results published in studies may not be correct because different researchers using the same dataset and analytical methods were unable to create the same results. This dilemma is called the reproducibility crisis. Currently, there has not been a comprehensive examination of the possible existence of this crisis in the field of autism spectrum research. This chapter does not answer the question, ‘Is there a reproducibility crisis occurring in the field of autism spectrum research?’ Rather, it contains an outline of this crisis, explains some of the most influential factors that have contributed to its development and how scholars who study the autism spectrum can change their research practices so that this crisis does not develop.

The original contribution that this chapter makes to autism spectrum research is to explain how some solutions to the reproducibility crisis can be implemented into the field of autism spectrum research.

Efforts in the spirit of this special issue aim at improving the reproducibility of experimental economics, in response to the recent discussions regarding the “research reproducibility crisis.” We put this endeavor in perspective by summarizing the main ways (to our knowledge) that have been proposed – by researchers from several disciplines – to alleviate the problem. We discuss the scope for economic theory to contribute to evaluating the proposals. We argue that a potential key impediment to replication is the expectation of negative reactions by the authors of the individual study, and suggest that incentives for having one’s work replicated should increase.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) is a widely accepted guideline for performing a systematic review (SR) in clinical journals. It not only helps an author to improve the reporting but also assists reviewers and editors in the critical appraisal of available SR. These tools help in achieving reproducibility in research, a major concern in contemporary academic research. But there is a lack of awareness about the approach among management researchers. This chapter attempts to fill this gap using a narrative review of reliable online resources and peer-reviewed articles to discuss the PRISMA guidelines and recent amendments. The chapter further points out the limitations of PRISMA in the review of management literature and suggests measures to overcome that. This piece of literature introduces a reader to the basics of a systematic review using PRISMA as an instrument. One of the significant contributions is to delineate a seven-step strategy to attain reproducibility in the systematic review. The chapter is useful for researchers and academicians in the field of social science and management.

Important research once thought unassailable has failed to replicate. Not just in economics, but in all science. The problem is therefore not in dispute nor are some of the causes, like low power, selective reporting, the file drawer effect, publicly unavailable data and so forth. Some partially worthy solutions have already been offered, like pre-registering hypotheses and data analysis plans.

This is a review paper on the replication crisis, which is by now very well known.

This study offers another partial solution, which is to remind researchers that correlation does not logically imply causation. The effect of this reminder is to eschew “significance” testing, whether in frequentist or Bayesian form (like Bayes factors) and to report models in predictive form, so that anybody can check the veracity of any model. In effect, all papers could undergo replication testing.

The author argues that this, or any solution, will never eliminate all errors.

Scientific research provides a reliable means for developing and accumulating knowledge bases to guide policy and practice. However, evidence from meta-research and large-scale replication projects suggests that the published research base likely reflects bias, which threatens the validity and credibility of research-based recommendations. Moreover, there is limited accessibility to research reports, which limits the impact and application of scientific research. In this chapter, we propose that open-science reforms, which aim to make the research process as open and transparent as possible, can be applied to help address these issues. We describe and discuss four open-science practices – preregistration and Registered Reports, open data and materials, open peer review, and open access and preprints – and propose that they may become one of the next big things in special education research.

Reflections on this special issue draw three themes out of the papers: the problem of fashioning the tools of science; the variability of life that poses challenges to scientific investigation; and the importance of space in myriad different ways to how we think about life. Although these themes may appear disconnected, they are in fact finely woven in various ways into the volume’s discussions, which range over science studies (broadly conceived) as well as economic history.