Data fabrication and falsification and empiricist philosophy of science

Mastering the scientific peer review process: tips for young authors from a young senior editor

Are you a student at a higher institution or an early-career researcher who is striving to understand and master the peer review process so to increase the odds of getting a paper published in the Journal of Forestry Research or another reputable, peer-reviewed, scientific journal? In this paper, a young, senior editor provides a handbook of the peer review process based on his decadal experience in scientific publishing. He covers major information you need to know during the entire process, from selecting journals to completing the proofing of your accepted paper. He introduces key points for consideration, such as avoidance of predatory journals, dubious research practices and ethics, interaction with peers, reviewers, and editors, and the pursuit of aretê. Finally, he points out some common statistical errors and misconceptions, such as P hacking and incorrect effect size inference. He hopes that this paper will enhance your understanding and knowledge of the peer-review process.

Bayesian Estimation with Informative Priors is Indistinguishable from Data Falsification

Criticism of null hypothesis significance testing, confidence intervals, and frequentist statistics in general has evolved into advocacy of Bayesian analyses with informative priors for strong inference. This paper shows that Bayesian analysis with informative priors is formally equivalent to data falsification because the information carried by the prior can be expressed as the addition of fabricated observations whose statistical characteristics are determined by the parameters of the prior. This property of informative priors makes clear that only the use of non-informative, uniform priors in all types of Bayesian analyses is compatible with standards of research integrity. At the same time, though, Bayesian estimation with uniform priors yields point and interval estimates that are identical or nearly identical to those obtained with frequentist methods. At a qualitative level, frequentist and Bayesian outcomes have different interpretations but they are interchangeable when uniform priors are used. Yet, Bayesian interpretations require either the assumption that population parameters are random variables (which they are not) or an explicit acknowledgment that the posterior distribution (which is thus identical to the likelihood function except for a scale factor) only expresses the researcher's beliefs and not any information about the parameter of concern.

Criminalization of scientific misconduct

This paper discusses the criminalization of scientific misconduct, as discussed and defended in the bioethics literature. In doing so it argues against the claim that fabrication, falsification and plagiarism (FFP) together identify the most serious forms of misconduct, which hence ought to be criminalized, whereas other forms of misconduct should not. Drawing the line strictly at FFP is problematic both in terms of what is included and what is excluded. It is also argued that the criminalization of scientific misconduct, despite its anticipated benefits, is at risk of giving the false impression that dubious practices falling outside the legal regulation "do not count". Some doubts are also raised concerning whether criminalization of the most serious forms of misconduct will lower the burdens for universities or successfully increase research integrity. Rather, with or without criminalization, other measures must be taken and are probably more important in order to foster a more healthy research environment.

What pharmacy practitioners need to know about ethics in scientific publishing

Pharmacy practice is an ever-changing science and profession. We are witnessing many advancement of pharmacy technology, drug-related information and applied clinical pharmacy literature, which influence our every day's life. Thus, new knowledge generated by research and clinical experience widen the knowledge; change the understanding of drugs and their application in therapeutics and every days life. Thus, policy makers, pharmacists, clinicians and researchers must evaluate and use the information existing in the literature to implement in their healthcare delivery. This paper is prepared for pharmacy researchers and pharmacy students and analyzes the major principles of ethical conduct in general science and also closely related topics on ghost authorship, conflict of interest, assigning co-authorship, redundant/repetitive and duplicate publication. Furthermore, the paper provides an insight into fabrication and falsification of data, as the most common form of scientific fraud. Scientific misconduct goes against everything that normal scientific method wants to reach for and pharmacy practitioners as one the first line available health care professionals all round the world should be enough aware of its importance and details when they want to evaluate the medical and pharmaceutical literature and deliver unbiased and ethically published knowledge of drugs both for the research or during consultations for patients care.