Scientists have rules pertaining to data fabrication and falsification that are enforced with significant punishments, such as loss of funding, termination of employment, or imprisonment. These rules pertain to data that describe observable and unobservable entities. In this commentary I argue that scientists would not adopt rules that impose harsh penalties on researchers for data fabrication or falsification unless they believed that an aim of scientific research is to develop true theories and hypotheses about entities (...) that exist, including unobservable ones. This argument presents a challenge for constructive empiricists, such as van Fraassen. Constructive empiricists need to be able to explain why rules pertaining to data fabrication and falsification do not threaten their philosophy of science. (shrink)

This paper reconsiders the possibility of applying the procedure of falsification, which consists in testing a theory by confronting hypotheses derived from the theory with empirical data, in the studies of culture, in particular when evaluating interpretive hypotheses. Falsification, to which, according to Popper and his followers, the natural sciences owe their success, is viewed with strong suspicion when the object of investigation is meanings and values rather than material phenomena. If by interpretation one understands reconstruction of (...) the artefact’s meaning, obvious challenges when falsifying interpretive hypotheses include: the multiplicity, instability and ambiguity (indefiniteness or self-contradictory character) of meanings inherent in artefacts. All of this does not seem to exclude the possibility of identifying as misreadings interpretive hypotheses which clearly contradict relevant (non-contradictory) artefactual evidence. Falsification thus understood seems indispensable in educational contexts. At the same time, it must be admitted that in practice (as contrasted with the logical formula which underlies the procedure) falsification is inconclusive, and the application of the procedure is further complicated when meanings and values are the object of research. This is one of the reasons why falsification in the humanities (as elsewhere) needs to be complemented by other epistemic procedures while the status of literary studies or history of philosophy might best be perceived as partly cognitive (and in so far as the research conducted in these disciplines is empirically testable, also scientific) and partly creative (artistic). (shrink)

In this paper we try to make a clear distinction between quantum mysticism and quantum mind theory. Quackery always accompanies science especially in controversial and still under development areas and since the quantum mind theory is a science youngster it must clearly demarcate itself from the great stuff of pseudo-science currently patronized by the term "quantum mind". Quantum theory has attracted a big deal of attention and opened new avenues for building up a physical theory of mind because its principles (...) and experimental foundations are as strange as the phenomenon of consciousness itself. Yet, the unwarranted recourse to paranormal phenomena as supporting the quantum mind theory plus the extremely bad biological mismodeling of brain physiology lead to great scepticism about the viability of the approach. We give as an example the Hameroff-Penrose Orch OR model with a list of twenty four problems not being repaired for a whole decade after the birth of the model in 1996. In the exposition we have tried not only to pesent critique of the spotted flaws, but to provide novel possibilities towards creation of neuroscientific quantum model of mind that incorporates all the available data from the basic disciplines (biochemistry, cell physiology, etc.) up to the clinical observations (neurology, neurosurgery, molecular psychiatry, etc.). Thus in a concise fashion we outline what can be done scientifically to improve the Q-mind theory and start a research programme (in Lakatos sense) that is independent on the particular flaws in some of the existing Q-mind models. (shrink)

SummaryOn purely logical grounds, if hypothesis H can be eliminated, then so too must its logical complement, H', be confirmed. The Asymmetry Theory, if true, must therefore be not formal but substantial. This cannot be established by the “two‐tier” view which requires symmetrical generalisation of theory terms and observation data. Even singular observations before being usable require a theory of accidents, a theory of errors, already built in to them before they can falsify hypotheses. This explains the inconsistency of (...) Popper's Simplicity criterion and his notion of a priori probability. Conclusion: Falsificationists cannot condemn verifiability without condemning themselves at the same time. (shrink)

Openness and transparency are becoming hallmarks of responsible data practice in science and governance. Concerns about data falsification, erroneous analysis, and misleading presentation of research results have recently strengthened the call for new procedures that ensure public accountability for data-driven decisions. Though we generally count ourselves in favor of increased transparency in data practice, this Commentary highlights a caveat. We suggest that legislative efforts that invoke the language of data transparency can sometimes function as (...) “Trojan Horses” through which other political goals are pursued. Framing these maneuvers in the language of transparency can be strategic, because approaches that emphasize open access to data carry tremendous appeal, particularly in current political and technological contexts. We illustrate our argument through two examples of pro-transparency policy efforts, one historical and one current: industry-backed “sound science” initiatives in the 1990s, and contemporary legislative efforts to open environmental data to public inspection. Rules that exist mainly to impede science-based policy processes weaponize the concept of data transparency. The discussion illustrates that, much as Big Data itself requires critical assessment, the processes and principles that attend it—like transparency—also carry political valence, and, as such, warrant careful analysis. (shrink)

To explain the origin of thorium, the Austrian geophysicist Kirsch in 1922 postulated a hypothetical isotope, thoruranium , by analogy with actinouranium. The theoretical life-time of thoruranium was predicted as being too short for it to have survived in the recent geological past. Available geological data was not inconsistent with this hypothesis, but neither did it confirm it. Within five years one new piece of geological evidence, which appeared not to conform with predictions based upon this alleged U-236, was (...) accepted even by Kirsch as sufficient to falsify his theory. However, during the 1940s, U-236 was produced artificially, and its characteristics were found to conform with those postulated for thoruranium. Subsequent research on the origin of the universe has confirmed that indeed a natural endowment of U-236 did once exist in considerable abundance. (shrink)

Philosophical accounts of altruism that purport to explain helping behavior are vulnerable to empirical falsification. John Campbell argues that the Good Samaritan study adds to a growing body of evidence that helping behavior is not best explained by appeal to altruism, thus jeopardizing those accounts. I propose that philosophical accounts of altruism can be empirically challenged only if it is shown that altruistic motivations are undermined by normative conflict in the agent, and that the relevant studies do not provide (...) this sort of evidence. Non-normative, purely causal, psychological factors would be empirically relevant only if the notion of altruism is broadened to include the requirement that one recognize certain situations as calling for altruism. But even in that case, the relevant studies are not designed in such a way that could threaten philosophical theories of altruism. (shrink)

The aim of the article is to propose a way to determine to what extent a hypothesis H is confirmed if it has successfully passed a classical significance test. Bayesians have already raised many serious objections against significance testing, but in doing so they have always had to rely on epistemic probabilities and a further Bayesian analysis, which are rejected by classical statisticians. Therefore, I will suggest a purely frequentist evaluation procedure for significance tests that should also be accepted by (...) a classical statistician. This procedure likewise indicates some additional problems of significance tests. In some situations, such tests offer only a weak incremental support of a hypothesis, although an absolute confirmation is necessary, and they overestimate positive results for small effects, since the confirmation of H is often rather marginal in these cases. In specific cases, for example, in cases of ESP-hypotheses, such as precognition, this phenomenon leads too easily to a significant confirmation and can be regarded as a form of the probabilistic falsification fallacy. (shrink)

Background Since 2010 the People’s Republic of China has been engaged in an effort to reform its system of organ transplantation by developing a voluntary organ donation and allocation infrastructure. This has required a shift in the procurement of organs sourced from China’s prison and security apparatus to hospital-based voluntary donors declared dead by neurological and/or circulatory criteria. Chinese officials announced that from January 1, 2015, hospital-based donors would be the sole source of organs. This paper examines the availability, transparency, (...) integrity, and consistency of China’s official transplant data. Methods Forensic statistical methods were used to examine key deceased organ donation datasets from 2010 to 2018. Two central-level datasets — published by the China Organ Transplant Response System and the Red Cross Society of China — are tested for evidence of manipulation, including conformance to simple mathematical formulae, arbitrary internal ratios, the presence of anomalous data artefacts, and cross-consistency. Provincial-level data in five regions are tested for coherence, consistency, and plausibility, and individual hospital data in those provinces are examined for consistency with provincial-level data. Results COTRS data conforms almost precisely to a mathematical formula while Central Red Cross data mirrors it, albeit imperfectly. The analysis of both datasets suggests human-directed data manufacture and manipulation. Contradictory, implausible, or anomalous data artefacts were found in five provincial datasets, suggesting that these data may have been manipulated to enforce conformity with central quotas. A number of the distinctive features of China’s current organ procurement and allocation system are discussed, including apparent misclassification of nonvoluntary donors as voluntary. Conclusion A variety of evidence points to what the authors believe can only be plausibly explained by systematic falsification and manipulation of official organ transplant datasets in China. Some apparently nonvoluntary donors also appear to be misclassified as voluntary. This takes place alongside genuine voluntary organ transplant activity, which is often incentivized by large cash payments. These findings are relevant for international interactions with China’s organ transplantation system. (shrink)

Surveys of almost 1,500 members of three professional societies that do risk analysis found that 3 in 10 respondents had observed a biased research design, 2 in 10 had observed plagiarism, and 1 in 10 observed data fabrication or falsification. Respondents with many years in risk analysis, business consultants, and industrial hygienists reported the greatest prevalence of misconduct. These respondents perceived poor science, economic implications of the research, and lack of training in ethics as causes of misconduct. They (...) supported the teaching of ethics but the vast majority did not support government auditing of their work. (shrink)

We conducted a systematic review and meta-analysis of anonymous surveys asking scientists whether they ever committed various forms of plagiarism. From May to December 2011 we searched 35 bibliographic databases, five grey literature databases and hand searched nine journals for potentially relevant studies. We included surveys that asked scientists if, in a given recall period, they had committed or knew of a colleague who committed plagiarism, and from each survey extracted the proportion of those who reported at least one case. (...) Studies that focused on academic plagiarism were excluded. Literature searches returned 12,460 titles from which 17 relevant survey studies were identified. Meta-analysis of studies reporting committed and witnessed plagiarism yielded a pooled estimate of, respectively, 1.7 % and 30 %. Basic methodological factors, including sample size, year of survey, delivery method and whether survey questions were explicit rather than indirect made a significant difference on survey results. Even after controlling for these methodological factors, between-study differences in admission rates were significantly above those expected by sampling error alone and remained largely unexplained. Despite several limitations of the data and of this meta-analysis, we draw three robust conclusions: The rate at which scientists report knowing a colleague who committed plagiarism is higher than for data fabrication and falsification; The rate at which scientists report knowing a colleague who committed plagiarism is correlated to that of fabrication and falsification; The rate at which scientists admit having committed either form of misconduct in surveys has declined over time. (shrink)

Philosophy of dialectical materialism and logic.

Among the many forms of research misconduct, publishing fraudulent data is considered to be serious where the confidence and validity of the research is detrimentally undermined. In this study, the trend of 303 retracted publications from 44 authors (with more than three retracted publications each) was analysed. The results showed that only 6.60% of the retracted publications were single-authored and the discovery of fraudulent publications had reduced from 52.24 months (those published before the year 2000) to 33.23 months (those (...) published on the year 2000 and onwards). It appears that with the widely accessible public databases like PubMed, fraudulent publications can be detected more easily. The different approaches adopted by authors who had previous publications retracted are also discussed herein. (shrink)

The historical background of the discovery of adverse health effects of medicines, food additives, pesticides, and other chemicals is reviewed, and the development of national and international regulations and testing procedures to protect the public against the toxic effects of these drugs and chemicals is outlined. Ethical considerations of the safety evaluation of drugs and chemicals by human experimentation and animal toxicity studies, ethical problems associated with clinical trials, with the falsification of clinical and toxicological data, and with (...) inadequate experimental methodology, are reviewed, and the ethics of the marketing of drugs and their post-marketing surveillance, are similarly considered. These ethical problems are illustrated with many specific examples, including the drugs neoarsphenamine, chloramphenicol, thalidomide, diethyl stilboestrol and benoxaprofen. (shrink)

In the management academic research, academic advancement, job security, and the securing of research funds at one’s university are judged mainly by one’s output of publications in high impact journals. With bogus resumes filled with published journal articles, universities and other allied institutions are keen to recruit or sustain the appointment of such academics. This often places undue pressure on aspiring academics and on those already recruited to engage in research misconduct which often leads to research integrity. This structured review (...) focuses on the ethics and integrity of management research through an analysis of retracted articles published from 2005 to 2016. The study employs a structured literature review methodology whereby retracted articles published between 2005 and 2016 in the field of management science were found using Crossref and Google Scholar. The searched articles were then streamlined by selecting articles based on their relevance and content in accordance with the inclusion criteria. Based on the analysed retracted articles, the study shows evidence of ethical misconduct among researchers of management science. Such misconduct includes data falsification, the duplication of submitted articles, plagiarism, data irregularity and incomplete citation practices. Interestingly, the analysed results indicate that the field of knowledge management includes the highest number of retracted articles, with plagiarism constituting the most significant ethical issue. Furthermore, the findings of this study show that ethical misconduct is not restricted to a particular geographic location; it occurs in numerous countries. In turn, avenues of further study on research misconduct in management research are proposed. (shrink)

In Science and Ethics, Bernard Rollin examines the ideology that denies the relevance of ethics to science. Providing an introduction to basic ethical concepts, he discusses a variety of ethical issues that are relevant to science and how they are ignored, to the detriment of both science and society. These include research on human subjects, animal research, genetic engineering, biotechnology, cloning, xenotransplantation, and stem cell research. Rollin also explores the ideological agnosticism that scientists have displayed regarding subjective experience in humans (...) and animals, and its pernicious effect on pain management. Finally, he articulates the implications of the ideological denial of ethics for the practice of science itself in terms of fraud, plagiarism, and data falsification. In engaging prose and with philosophical sophistication, Rollin cogently argues in favor of making education in ethics part and parcel of scientific training. (shrink)

The prevalence and characteristics of research misconduct have mainly been studied in highly developed countries. In moderately or poorly developed countries such as Croatia, data on research misconduct are scarce. The primary aim of this study was to determine the rates at which scientists report committing or observing the most serious forms of research misconduct, such as falsification, fabrication, plagiarism, and violation of authorship rules in the Croatian scientific community. Additionally, we sought to determine the degree of development (...) and the extent of implementation of the system for defining and regulating research misconduct in a typical scientific community in Croatia. An anonymous questionnaire was distributed among 1232 Croatian scientists at the University of Rijeka in 2012/2013 and 237 returned the survey. Based on the respondents who admitted having committed research misconduct, 9 admitted to plagiarism, 22 to data falsification, 9 to data fabrication, and 60 respondents admitted to violation of authorship rules. Based on the respondents who admitted having observed research misconduct of fellow scientists, 72 observed plagiarism, 69 observed data falsification, 46 observed data fabrication, and 132 respondents admitted having observed violation of authorship rules. The results of our study indicate that the efficacy of the system for managing research misconduct in Croatia is poor. At the University of Rijeka there is no document dedicated exclusively to research integrity, describing the values that should be fostered by a scientist and clarifying the forms of research misconduct and what constitutes a questionable research practice. Scientists do not trust ethical bodies and the system for defining and regulating research misconduct; therefore the observed cases of research misconduct are rarely reported. Finally, Croatian scientists are not formally educated about responsible conduct of research at any level of their formal education. All mentioned indicate possible reasons for higher rates of research misconduct among Croatian scientists in comparison with scientists in highly developed countries. (shrink)

Background Papers retracted for fraud (data fabrication or data falsification) may represent a deliberate effort to deceive, a motivation fundamentally different from papers retracted for error. It is hypothesised that fraudulent authors target journals with a high impact factor (IF), have other fraudulent publications, diffuse responsibility across many co-authors, delay retracting fraudulent papers and publish from countries with a weak research infrastructure. Methods All 788 English language research papers retracted from the PubMed database between 2000 and 2010 (...) were evaluated. Data pertinent to each retracted paper were abstracted from the paper and the reasons for retraction were derived from the retraction notice and dichotomised as fraud or error. Data for each retracted article were entered in an Excel spreadsheet for analysis. Results Journal IF was higher for fraudulent papers (p<0.001). Roughly 53% of fraudulent papers were written by a first author who had written other retracted papers (‘repeat offender’), whereas only 18% of erroneous papers were written by a repeat offender (χ=88.40; p<0.0001). Fraudulent papers had more authors (p<0.001) and were retracted more slowly than erroneous papers (p<0.005). Surprisingly, there was significantly more fraud than error among retracted papers from the USA (χ2=8.71; p<0.05) compared with the rest of the world. Conclusions This study reports evidence consistent with the ‘deliberate fraud’ hypothesis. The results suggest that papers retracted because of data fabrication or falsification represent a calculated effort to deceive. It is inferred that such behaviour is neither naïve, feckless nor inadvertent. (shrink)

Empirical studies have revealed a disturbing prevalence of research misconduct in a wide variety of disciplines, although not, to date, in the areas of ethics and philosophy. This study aims to provide empirical evidence on perceptions of how serious a problem research misconduct is in these two disciplines in Spain, particularly regarding the effects that the model used to evaluate academics’ research performance may have on their ethical behaviour. The methodological triangulation applied in the study combines a questionnaire, a debate (...) at the annual meeting of scientific association, and in-depth interviews. Of the 541 questionnaires sent out, 201 responses were obtained, with a significant difference in the participation of researchers in philosophy and in ethics ; 26 researchers took part in the debate and 14 interviews were conducted. The questionnaire results reveal that 91.5% of the respondents considered research misconduct to be on the rise; 63.2% considered at least three of the fraudulent practices referred to in the study to be commonplace, and 84.1% identified two or more such practices. The researchers perceived a high prevalence of duplicate publication and self-plagiarism, use of personal influence and citation manipulation, in contrast to a low perceived incidence of data falsification or fabrication. The debate and the interviews corroborated these data. Researchers associated the spread of these misconducts with the research evaluation model applied in Spain. (shrink)

It is commonly hypothesized that scientists are more likely to engage in data falsification and fabrication when they are subject to pressures to publish, when they are not restrained by forms of social control, when they work in countries lacking policies to tackle scientific misconduct, and when they are male. Evidence to test these hypotheses, however, is inconclusive due to the difficulties of obtaining unbiased data. Here we report a pre-registered test of these four hypotheses, conducted on (...) papers that were identified in a previous study as containing problematic image duplications through a systematic screening of the journal PLoS ONE. Image duplications were classified into three categories based on their complexity, with category 1 being most likely to reflect unintentional error and category 3 being most likely to reflect intentional fabrication. We tested multiple parameters connected to the hypotheses above with a matched-control paradigm, by collecting two controls for each paper containing duplications. Category 1 duplications were mostly not associated with any of the parameters tested, as was predicted based on the assumption that these duplications were mostly not due to misconduct. Categories 2 and 3, however, exhibited numerous statistically significant associations. Results of univariable and multivariable analyses support the hypotheses that academic culture, peer control, cash-based publication incentives and national misconduct policies might affect scientific integrity. No clear support was found for the “pressures to publish” hypothesis. Female authors were found to be equally likely to publish duplicated images compared to males. Country-level parameters generally exhibited stronger effects than individual-level parameters, because developing countries were significantly more likely to produce problematic image duplications. This suggests that promoting good research practices in all countries should be a priority for the international research integrity agenda. (shrink)

One of the Commentaries in this issue is something of a departure for the JSE. The paper by Jaime A. Teixeira da Silva concerns retractions in scientific publications, a topic that has been receiving increasing attention in recent years, apparently coinciding with an increasing number of retractions over the same period. Because the SSE and JSE focus not only on specific (usually controversial or neglected) domains of scientific investigation but also on broader issues concerning the practice of science itself, I (...) figured that the cluster of issues surrounding retractions might be of both theoretical and practical interest to JSE readers. The sheer number of retractions is enough to give one pause. A recent survey by R. Grant Steen of the PubMed database from 2000 to 2010 identified 788 retracted papers (Steen 2011). For 46 of those papers, Steen was unable to find formal retraction notices. So his survey dealt with the remaining 742 papers for which he could obtain such notices. The reasons for retraction were broadly identified as fraud and error. The former included data fabrication and data falsification, and the latter included (among other things) plagiarism,1 scientific mistake, and ethical issues (violations of accepted publication practices—for example, IRB [Institutional Review Board] violations). Steen found that the reason for retraction was more often error than fraud—73.5% as compared to 26.5%. (shrink)

Research Ethics in Applied Economics Emphasizing the new challenges posed by the data science revolution, digital media, and changing standards, Research Ethics in Applied Economics examines the ethical issues faced by the applied economics researcher at each stage of the research process. The first section of the book considers project development, including issues of project management, selection bias in asking research questions, and political incentives in the development and funding of research ideas. The second section addresses data collection (...) and analysis, discussing concerns about participant rights, data falsification, data management, specification search, p-hacking, and replicability. The final section focuses on sharing results with academic audiences and beyond, with an emphasis on self-plagiarism, self-promotion, and the importance of achieving policy impact. The discussion and related recommendations highlight emergent issues in research ethics. Featuring case studies from experienced researchers on how they address ethical issues, this book provides practical guidance to both students and experienced practitioners seeking to navigate ethical issues in their applied economics research. (shrink)

Machine learning operates at the intersection of statistics and computer science. This raises the question as to its underlying methodology. While much emphasis has been put on the close link between the process of learning from data and induction, the falsificationist component of machine learning has received minor attention. In this paper, we argue that the idea of falsification is central to the methodology of machine learning. It is commonly thought that machine learning algorithms infer general prediction rules (...) from past observations. This is akin to a statistical procedure by which estimates are obtained from a sample of data. But machine learning algorithms can also be described as choosing one prediction rule from an entire class of functions. In particular, the algorithm that determines the weights of an artificial neural network operates by empirical risk minimization and rejects prediction rules that lack empirical adequacy. It also exhibits a behavior of implicit regularization that pushes hypothesis choice toward simpler prediction rules. We argue that taking both aspects together gives rise to a falsificationist account of artificial neural networks. (shrink)

Education in the responsible conduct of research typically takes the form of online instructions about rules, regulations, and policies. Research Ethics takes a novel approach and emphasizes the art of philosophical decision-making. Part A introduces egoism and explains that it is in the individual's own interest to avoid misconduct, fabrication of data, plagiarism and bias. Part B explains contractualism and covers issues of authorship, peer review and responsible use of statistics. Part C introduces moral rights as the basis of (...) informed consent, the use of humans in research, mentoring, intellectual property and conflicts of interests. Part D uses two-level utilitarianism to explore the possibilities and limits of the experimental use of animals, duties to the environment and future generations, and the social responsibilities of researchers. This book brings a fresh perspective to research ethics and will engage the moral imaginations of graduate students in all disciplines. (shrink)

For applied geologists working in the minerals industry the tasks of problem formulation, observation and data collection, interpretation and modelling invoke various philosophical considerations whether the practitioner is aware of them or not. A primary goal of applied geologists is to build models that accurately predict reality to an acceptable degree. In this paper, we describe the key philosophical frameworks proposed for conducting scientific investigations and relate them to the field of applied geology. We consider the very important differences (...) in the types of problem confronted in experimental sciences compared to the historical sciences, such as geology, where the processes studied are unique and only evidential traces of past events are available. The prediction quality of models is likely to be materially improved if the geologist is firmly and consciously practiced in the scientific method. In addition, if the predictions are framed and presented in terms of the underlying science, the quality of decisions made based on those predictions will likewise be improved. The implications for creating additional value to a project or operation can be very significant when geological models are constructed and used by a practitioner with an understanding of the philosophical basis of the activities constituting a scientific investigation. The method of multiple working hypotheses is particularly important when working in historical sciences. We argue that working within the framework of multiple working hypotheses can provide a valuable insurance against the adoption of, or persistence with, flawed models. (shrink)

Next SectionBackground Scientific papers are retracted for many reasons including fraud (data fabrication or falsification) or error (plagiarism, scientific mistake, ethical problems). Growing attention to fraud in the lay press suggests that the incidence of fraud is increasing. Methods The reasons for retracting 742 English language research papers retracted from the PubMed database between 2000 and 2010 were evaluated. Reasons for retraction were initially dichotomised as fraud or error and then analysed to determine specific reasons for retraction. Results (...) Error was more common than fraud (73.5% of papers were retracted for error (or an undisclosed reason) vs 26.6% retracted for fraud). Eight reasons for retraction were identified; the most common reason was scientific mistake in 234 papers (31.5%), but 134 papers (18.1%) were retracted for ambiguous reasons. Fabrication (including data plagiarism) was more common than text plagiarism. Total papers retracted per year have increased sharply over the decade (r=0.96; p<0.001), as have retractions specifically for fraud (r=0.89; p<0.001). Journals now reach farther back in time to retract, both for fraud (r=0.87; p<0.001) and for scientific mistakes (r=0.95; p<0.001). Journals often fail to alert the naïve reader; 31.8% of retracted papers were not noted as retracted in any way. Conclusions Levels of misconduct appear to be higher than in the past. This may reflect either a real increase in the incidence of fraud or a greater effort on the part of journals to police the literature. However, research bias is rarely cited as a reason for retraction. (shrink)

In computer simulations of physical systems, the construction of models is guided, but not determined, by theory. At the same time simulations models are often constructed precisely because data are sparse. They are meant to replace experiments and observations as sources of data about the world; hence they cannot be evaluated simply by being compared to the world. So what can be the source of credibility for simulation models? I argue that the credibility of a simulation model comes (...) not only from the credentials supplied to it by the governing theory, but also from the antecedently established credentials of the model building techniques employed by the simulationists. In other words, there are certain sorts of model building techniques which are taken, in and of themselves, to be reliable. Some of these model building techniques, moreover, incorporate what are sometimes called “falsifications.” These are contrary-to-fact principles that are included in a simulation model and whose inclusion is taken to increase the reliability of the results. The example of a falsification that I consider, called artificial viscosity, is in widespread use in computational fluid dynamics. Artificial viscosity, I argue, is a principle that is successfully and reliably used across a wide domain of fluid dynamical applications, but it does not offer even an approximately “realistic” or true account of fluids. Artificial viscosity, therefore, is a counter-example to the principle that success implies truth – a principle at the foundation of scientific realism. It is an example of reliability without truth. (shrink)

This paper explores the gray area of questionable research practices (QRPs) between responsible conduct of research and severe research misconduct in the form of fabrication, falsification, and plagiarism (Steneck in SEE 12(1): 53–57, 2006). Up until now, we have had very little knowledge of disciplinary similarities and differences in QRPs. The paper is the first systematic account of variances and similarities. It reports on the findings of a comprehensive study comprising 22 focus groups on practices and perceptions of QRPs (...) across main areas of research. The paper supports the relevance of the idea of epistemic cultures (Knorr Cetina in: Epistemic cultures: how the sciences make knowledge, Harvard University Press, Cambridge, 1999), also when it comes to QRPs. It shows which QRPs researchers from different areas of research (humanities, social sciences, medical sciences, natural sciences, and technical sciences) report as the most severe and prevalent within their fields. Furthermore, it shows where in the research process these self-reported QRPs can be found. This is done by using a five-phase analytical model of the research process (idea generation, research design, data collection, data analysis, scientific publication and reporting). The paper shows that QRPs are closely connected to the distinct research practices within the different areas of research. Many QRPs can therefore only be found within one area of research, and QRPs that cut across main areas often cover relatively different practices. In a few cases, QRPs in one area are considered good research practice in another. (shrink)

Misconduct in science is often viewed and analyzed through the lenses of normative ethics and moral philosophy. However, notions and methods in the philosophy of science could also provide rather penetrative explanatory insights into the nature and causes of scientific misconduct. A brief illustration in this regard, using as examples the widely popular Popperian falsification and the Kuhnian scientific paradigm, is provided. In multiple areas of scientific research, failure to seek falsification in a Popperian manner constitutes a questionable (...) research practice and could lead to “falsification” in the context of research misconduct. On the other hand, scientific misconduct is often facilitated by its perpetrators using the familiarity, expectations and confines of a Kuhnian paradigm to blend in fabricated data/results. A rudimentary application of these philosophical notions could be useful in our understanding of the nature and cause of research misconduct, and facilitate mitigation of the latter through educational means. (shrink)

Recent studies from Western countries indicate significant levels of questionable research practices, but similar data from low and middle-income countries are limited. Our aims were to assess the prevalence of and attitudes regarding research misconduct among researchers in several universities in the Middle East and to identify factors that might account for our findings. We distributed an anonymous questionnaire to a convenience sample of investigators at several universities in Egypt, Lebanon, and Bahrain. Participants were asked to a) self-report their (...) extent of research misconducts, as well as their knowledge of colleagues engaging in similar research misconducts and b) provide their extent of agreement with certain attitudes about research misconduct. We used descriptive, bivariate, and multivariate logistic regression statistics to analyze the data. Data from 278 participants showed a high prevalence of misconduct, as 59.4% of our respondents self-reported to committing at least one misbehaviors and 74.5% reported having knowledge of any misbehaviors among any of their colleagues. The most common type of self-report misconduct was “circumventing research ethics regulations” followed by “fabrication and falsification”. A significant predictor of misconduct included a lack of “prior ethics training”. Scientific misconduct represents a significant issue in several universities in the Middle East. The demonstration that a lack of “prior ethics training” was a significant predictor of misconduct should lead to educational initiatives in research integrity. Further studies are needed to confirm whether our results can be generalized to other universities in the Middle East. (shrink)

We examined all 208 closed cases involving official findings of research misconduct published by the US Office of Research Integrity from 1992 to 2011 to determine how often scientists mention in a retraction or correction notice that there was an ethical problem with an associated article. 75 of these cases cited at least one published article affected by misconduct for a total of 174 articles. For 127 of these 174, we found both the article and a retraction or correction statement. (...) Since eight of the 127 published statements consisted of simply the word ‘retracted,’ our analysis focused on the remaining 119 for which a more detailed retraction or correction was published. Of these 119 statements, only 41.2% mentioned ethics at all (and only 32.8% named a specific ethical problem such as fabrication, falsification or plagiarism), whereas the other 58.8% described the reason for retraction or correction as error, loss of data or replication failure when misconduct was actually at issue. Among the published statements in response to an official finding of misconduct (within the time frame studied), the proportion that mentioned ethics was significantly higher in recent years than in earlier years, as was the proportion that named a specific problem. To promote research integrity, scientific journals should consider adopting policies concerning retractions and corrections similar to the guidelines developed by the Committee on Publication Ethics. Funding agencies and institutions should take steps to ensure that articles affected by misconduct are retracted or corrected. (shrink)

BackgroundPlagiarism is considered as serious research misconduct, together with data fabrication and falsification. However, little is known about biomedical researchers’ views on plagiarism. Moreover, it has been argued – based on limited empirical evidence – that perceptions of plagiarism depend on cultural and other determinants. The authors explored, by means of an online survey among 46 reputable universities in Europe and China, how plagiarism is perceived by biomedical researchers in both regions.MethodsWe collected work e-mail addresses of biomedical researchers (...) identified through the websites of 13 reputable universities in Europe and 33 reputable universities in China and invited them to participate in an online anonymous survey. Our questionnaire was designed to assess respondents’ views about plagiarism by asking whether they considered specific practices as plagiarism. We analyzed if respondents in China and Europe responded differently, using logistic regression analysis with adjustments for demographic and other relevant factors.ResultsThe authors obtained valid responses from 204 researchers based in China (response rate 2.1%) and 826 researchers based in Europe (response rate 5.6%). Copying text from someone else’s publication without crediting the source, using idea(s) from someone else’s publication without crediting the source and republishing one’s own work in another language without crediting the source were considered as plagiarism by 98, 67 and 64%, respectively. About one-third of the respondents reported to have been unsure whether they had been plagiarizing.Overall, the pattern of responses was similar among respondents based in Europe and China. Nevertheless, for some items significant differences did occur in disadvantage of Chinese respondents.ConclusionsFindings indicate that nearly all biomedical researchers understand (and disapprove of) the most obvious forms of plagiarism, but uncertainties and doubts were apparent for many aspects. And the minority of researchers who did not recognize some types of plagiarism as plagiarism was larger among China-based respondents than among Europe-based respondents. The authors conclude that biomedical researchers need clearer working definitions of plagiarism in order to deal with grey zones. (shrink)

Experiment, instrumentation, and procedures of measurement, the body of practices and technologies forming the technical culture of science, have received at most a cameo appearance in most histories. For the history of science is almost always written as the history of theory. Of course, the interpretation of science as dominated by theory was the main pillar of the critique, launched by Kuhn, Quine, Hanson, Feyerabend, and others, of the positivist and logical empiricist traditions in the philosophy of science. Against Carnap, (...) Hempel, Nagel, and Popper, who accorded observation reports an independent status either as a source of inductive support or as a basis for the falsification of scientific theories, Hanson and Kuhn emphasized the theory-ladenness of observation. They made this central point – that all observation is shaped by reference to theory – the cornerstone of a full-blown philosophy of science by buttressing it with two additional lines of argument: First, theories are always underdetermined by the data, several theories being compatible with the same set of data. Hence, choice between theories is never a matter of empirical support, but always turns around conceptual issues. Second, statements derived from theory never confront nature alone; they are always clothed in a web of interrelated beliefs. Thus, theories, their associated observation languages, and the entire technical culture they support must be accepted or rejected as wholes. (shrink)

BackgroundThe areas of Research Ethics (RE) and Research Integrity (RI) are rapidly evolving. Cases of research misconduct, other transgressions related to RE and RI, and forms of ethically questionable behaviors have been frequently published. The objective of this scoping review was to collect RE and RI cases, analyze their main characteristics, and discuss how these cases are represented in the scientific literature.MethodsThe search included cases involving a violation of, or misbehavior, poor judgment, or detrimental research practice in relation to a (...) normative framework. A search was conducted in PubMed, Web of Science, SCOPUS, JSTOR, Ovid, and Science Direct in March 2018, without language or date restriction. Data relating to the articles and the cases were extracted from case descriptions.ResultsA total of 14,719 records were identified, and 388 items were included in the qualitative synthesis. The papers contained 500 case descriptions. After applying the eligibility criteria, 238 cases were included in the analysis. In the case analysis, fabrication and falsification were the most frequently tagged violations (44.9%). The non-adherence to pertinent laws and regulations, such as lack of informed consent and REC approval, was the second most frequently tagged violation (15.7%), followed by patient safety issues (11.1%) and plagiarism (6.9%). 80.8% of cases were from the Medical and Health Sciences, 11.5% from the Natural Sciences, 4.3% from Social Sciences, 2.1% from Engineering and Technology, and 1.3% from Humanities. Paper retraction was the most prevalent sanction (45.4%), followed by exclusion from funding applications (35.5%).ConclusionsCase descriptions found in academic journals are dominated by discussions regarding prominent cases and are mainly published in the news section of journals. Our results show that there is an overrepresentation of biomedical research cases over other scientific fields compared to its proportion in scientific publications. The cases mostly involve fabrication, falsification, and patient safety issues. This finding could have a significant impact on the academic representation of misbehaviors. The predominance of fabrication and falsification cases might diverge the attention of the academic community from relevant but less visible violations, and from recently emerging forms of misbehaviors. (shrink)

Background There is a dearth of information on the prevalence of scientific misconduct from Nigeria. Objectives This study aimed at determining the prevalence of scientific misconduct in a group of researchers in Nigeria. Factors associated with the prevalence were ascertained. Method A descriptive study of researchers who attended a scientific conference in 2010 was conducted using the adapted Scientific Misconduct Questionnaire-Revised (SMQ-R). Results Ninety-one researchers (68.9%) admitted having committed at least one of the eight listed forms of scientific misconduct. Disagreement (...) about authorship was the most common form of misconduct committed (36.4%) while plagiarism was the least (9.2%). About 42% of researchers had committed falsification of data or plagiarism. Analysis of specific acts of misconduct showed that committing plagiarism was inversely associated with years in research (Fisher exact p-value = 0.02); falsifying data was related to perceived low effectiveness of the institution's rules and procedures for reducing scientific misconduct (X2 = 6.44, p-value = 0.01); and succumbing to pressure from study sponsor to engage in unethical practice was related to sex of researcher (Fisher exact p-value = 0.02). Conclusions The emergent data from this study is a cause for serious concern and calls for prompt intervention. The best response to reducing scientific misconduct will proceed from measures that contain both elements of prevention and enforcement. Training on research ethics has to be integrated into the curriculum of undergraduate and postgraduate students while provision should be made for in-service training of researchers. Penalties against acts of scientific misconduct should be enforced at institutional and national levels. (shrink)

The last two decades have witnessed the rising prevalence of both co-publishing and retraction. Focusing on research collaboration, this paper utilizes a unique dataset to investigate factors contributing to retraction probability and elapsed time between publication and retraction. Data analysis reveals that the majority of retracted papers are multi-authored and that repeat offenders are collaboration prone. Yet, all things being equal, collaboration, in and of itself, does not increase the likelihood of producing flawed or fraudulent research, at least in (...) the form of retraction. That holds for all retractions and also retractions due to falsification, fabrication, and plagiarism. The research also finds that publications with authors from elite universities are less likely to be retracted, which is particularly true for retractions due to FFP. China stands out with the fastest retracting speed compared to other countries. Possible explanations, limitations, and policy implications are also discussed. (shrink)

Background There is a dearth of information on the prevalence of scientific misconduct from Nigeria. Objectives This study aimed at determining the prevalence of scientific misconduct in a group of researchers in Nigeria. Factors associated with the prevalence were ascertained. Method A descriptive study of researchers who attended a scientific conference in 2010 was conducted using the adapted Scientific Misconduct Questionnaire‐Revised (SMQ‐R). Results Ninety‐one researchers (68.9%) admitted having committed at least one of the eight listed forms of scientific misconduct. Disagreement (...) about authorship was the most common form of misconduct committed (36.4%) while plagiarism was the least (9.2%). About 42% of researchers had committed falsification of data or plagiarism. Analysis of specific acts of misconduct showed that committing plagiarism was inversely associated with years in research (Fisher exact p‐value = 0.02); falsifying data was related to perceived low effectiveness of the institution's rules and procedures for reducing scientific misconduct (X2 = 6.44, p‐value = 0.01); and succumbing to pressure from study sponsor to engage in unethical practice was related to sex of researcher (Fisher exact p‐value = 0.02). Conclusions The emergent data from this study is a cause for serious concern and calls for prompt intervention. The best response to reducing scientific misconduct will proceed from measures that contain both elements of prevention and enforcement. Training on research ethics has to be integrated into the curriculum of undergraduate and postgraduate students while provision should be made for in‐service training of researchers. Penalties against acts of scientific misconduct should be enforced at institutional and national levels. (shrink)

We investigated the acceptability and frequency of the use of cognitive enhancement (CE) drugs and three different types of academic misconduct (plagiarism, cheating in exams, and falsifying/fabricating data). Data from a web-based survey among German university students were used. Moral acceptability was relatively low for CE drug use and moderate for academic misconduct, while the correlation of their respective acceptability was moderately weak. Prevalence of CE drug use was lower than for academic misconduct and (very) lightly correlated with (...) the prevalence of plagiarism and fabrication/falsification. Acceptability of the investigated behaviors was associated with higher prevalence rates of each behavior. (shrink)

We have national guidelines for the responsible conduct of research (RCR) and procedures for handling allegations of misconduct in Finland. The guidelines have been formulated and updated by the Finnish Advisory Board on Research Integrity (TENK). In this article, we introduce and evaluate the national RCR guidelines. We also present statistics of alleged and proven RCR violation cases and frequency of appeals to TENK on the decisions or procedures of the primary institutions. In addition, we analyze the available data (...) on seven investigated cases in more detail. Positive aspects in the Finnish system are a fairly good infrastructure to investigate suspected RCR violations and a wide concept of RCR violations, which consists of fabrication, falsification, plagiarism, misappropriation, and other misbehaviors. However, the guidelines contain poorly elaborated definitions, do not treat the complainant and the suspect in an equal way, and need to be revised. Confusion about the concepts and criteria of the RCR violations seems to be common in primary institutions and among the complainants. Even if research institutions and universities have officially adhered to the national RCR guidelines, slipping from the guidelines occurs quite commonly. All these factors lead to frequent dissatisfaction with the decisions or procedures applied, high rate of appeals to TENK, and far from optimal functionality of the system. (shrink)

This article presents results from the national survey conducted in 2018 for the project Research Integrity in Norway. A total of 31,206 questionnaires were sent out to Norwegian researchers by e-mail, and 7291 responses were obtained. In this paper, we analyse the survey data to determine attitudes towards and the prevalence of fabrication, falsification and plagiarism and contrast this with attitudes towards and the prevalence of the more questionable research practices surveyed. Our results show a relatively low percentage (...) of self-reported FFPs, while the number of researchers who report having committed one of the QRPs during the last three years reached a troublesome 40%. The article also presents a ranking of the perceived severity of FFP and QRPs among Norwegian researchers. Overall, there is a widespread normative consensus, where FFP is considered more troublesome than QRPs. (shrink)

Irrespective of the presence of formal norms, behaviours such as plagiarism, data fabrication and falsification are commonly regarded as unethical and unfair. Almost unanimously, they are considered forms of academic misconduct. Is this the case also for newer behaviours that technology is making possible and are now entering the academic scenario?