“Hypernormal science” has minimal potential for contestation on matters of principle and practice so that information exchange can be unproblematic. Sciences comprise hypernormal domains and more contestable “normal” domains where knowledge diffusion, like acquiring linguistic fluency, depends on face-to-face interaction. Hypernormal domains belonging to molecular biology are contrasted with normal domains in gravitational wave detection physics. Sciences as a whole should not be confused with their typical domains. The analysis has immediate implications for proposed transitions out of the Covid-19 lockdown, (...) proposed solutions to the replication crisis, and, perhaps, our understanding of the early development of social studies of science. (shrink)

In this response to Robert Hudson’s article, “Should We Strive to Make Science Bias-Free? A Philosophical Assessment of the Reproducibility Crisis,” we identify three ways in which he misrepresents our work: he conflates value-ladenness with bias; he describes our view as one in which values are the same as evidential factors; and he creates a false dichotomy between two ways that values could be considered in science for policy. We share Hudson’s concerns about promoting scientific reproducibility and reducing bias in (...) science, but we reject his view that the value-free ideal provides helpful guidance for addressing these issues. (shrink)

English summary: This paper uses research on the COVID-19 pandemic as the backdrop for an accessible discussion of the value and status of science, and of the role of valuesin science. In particular, the paper seeks to debunk three common myths or dogmas about scientific research: (i) that there is such a thing as 'scientific proof' of a theory or hypothesis, (ii) that disagreement is necessarily unhealthy or unnatural in science, (iii) and that personal values play no role in scientific (...) research. (shrink)

In this paper I explore an underdiscussed factor contributing to the replication crisis: Scientists, and following them policy makers, often neglect sources of errors in the production and interpretation of data and thus overestimate what can be learnt from them. This neglect leads scientists to conduct experiments that are insufficiently informative and science consumers, including other scientists, to put too much weight on experimental results. The former leads to fragile empirical literatures, the latter to surprise and disappointment when the fragility (...) of the empirical basis of some disciplines is revealed. (shrink)

The experience of the use of applied containerized biomedical software tools in cloud environment is summarized. The reproducibility of scientific computing in relation with modern technologies of scientific calculations is discussed. The main approaches to biomedical data preprocessing and integration in the framework of the intelligent analytical system are described. At the conditions of pandemic, the success of health care system depends significantly on the regular implementation of effective research tools and population monitoring. The earlier the risks of disease can (...) be identified, the more effective process of preventive measures or treatments can be. This publication is about the creation of a prototype for such a tool within the project «Development of methods, algorithms and intelligent analytical system for processing and analysis of heterogeneous clinical and biomedical data to improve the diagnosis of complex diseases», implementted by the V.M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, together with the United Institute of Informatics Problems, National Academy of Sciences of Belarus. The insurers, entering the market, can insure mostly low risks by facilitating more frequent changes of insurers by consumers and mixing the overall health insurance market. Socio-demographic variables can be risk adjusters. Since age and gender have a relatively small explanatory power, other socio-demographic variables were studied – marital status, retirement status, disability status, educational level, income level. Because insurers have an interest in beneficial diagnoses for their policyholders, they are also interested in the ability to interpret relevant information – upcoding: insurers can encourage their policyholders to consult with doctors more often to select as many diagnoses as possible. Many countries and health care systems use diagnostic information to determine the reimbursement to a service provider, revealing the necessary data. For processing and analysis of these data, software implementations of construction for classifiers, allocation of informative features, processing of heterogeneous medical and biological variables for carrying out scientific research in the field of clinical medicine are developed. The experience of the use of applied containerized biomedical software tools in cloud environment is summarized. The reproducibility of scientific computing in relation with modern technologies of scientific calculations is discussed. Particularly, attention is paid to containerization of biomedical applications, this permits to get reproducibility of the conditions in which the calculations took place, technologies of software pipelining of calculations, that allows to organize flow calculations, and technologies for parameterization of software environment, that allows to reproduce, if necessary, an identical computing environment. The main approaches to biomedical data preprocessing and integration in the framework of the intelligent analytical system are described. The experience of using the developed linear classifier, gained during its testing on artificial and real data, allows us to conclude about several advantages provided by the containerized form of the created application: it permits to provide access to real data located in cloud environment; it is possible to perform calculations to solve research problems on cloud resources both with the help of developed tools and with the help of cloud services; such a form of research organization makes numerical experiments reproducible, i.e. any other researcher can compare the results of their developments on specific data that have already been studied by others, in order to verify the conclusions and technical feasibility of new results; there exists a universal opportunity to use the developed tools on technical devices of various classes from a personal computer to powerful cluster. (shrink)

The crisis of replication has led many to blame statistical significance tests for making it too easy to find impressive looking effects that do not replicate. However, the very fact it becomes difficult to replicate effects when features of the tests are tied down actually serves to vindicate statistical significance tests. While statistical significance tests, used correctly, serve to bound the probabilities of erroneous interpretations of data, this error control is nullified by data-dredging, multiple testing, and other biasing selection effects. (...) Arguments claiming to vitiate statistical significance tests attack straw person variants of tests that commit well-known fallacies and misinterpretations. There is a tension between popular calls for preregistration – arguably, one of the most promising ways to boost replication – and accounts that downplay error probabilities: Bayes Factors, Bayesian posteriors, likelihood ratios. By underscoring the importance of error control for well testedness, the replication crisis points to reformulating tests so as to avoid fallacies and report the extent of discrepancies that are and are not indicated with severity. (shrink)

The epistemic attitudes of scientists, such as epistemic tolerance and authoritarianism, play important roles in the discourse about rivaling theories. Epistemic tolerance stands for the mental attitude of an epistemic agent, e.g., a scientist, who is open to opposing views, while epistemic authoritarianism represents the tendency to uncritically accept views of authorities. Another relevant epistemic factor when it comes to the epistemic decisions of scientists is the skepticism towards the scientific method. However, the question is whether these epistemic attitudes are (...) influenced by their sociopolitical counterparts, such as the researcher’s degree of conservatism. To empirically investigate the interplay between epistemic and sociopolitical attitudes of scientists, we conducted a survey with researchers (N = 655) across different disciplines. We propose scales for measuring epistemic tolerance and epistemic authoritarianism, as well as a scale for detecting the participants' readiness to question the scientific method. Furthermore, we investigate the relationship between epistemic tolerance and epistemic authoritarianism on the one hand, and career stage and sociopolitical views on the other hand. Interestingly, our study found only small correlations between the participants' degree of conservatism and their epistemic attitudes. This suggests that political views, against common argumentation, actually do not play an important role in one’s scientific decisions. Moreover, social scientists scored higher on the epistemic tolerance and lower on the epistemic authoritarianism scale than natural scientists. Finally, the results indicate that natural scientists question the scientific method less than social scientists. (shrink)

While there has been much discussion of how the scientific establishment’s culture can engender research misconduct and scientific irreproducibility, this has been discussed much less frequently with respect to the medical profession. Here the authors posit that a lack of self-criticism, an encouragement of novel scientific research generated by the recruitment policies of the UK Royal Training Colleges along with insufficient training in the sciences are core reasons as to why research misconduct and dishonesty prevail within the medical community. Furthermore, (...) the UK General Medical Council’s own data demonstrates a historic inattentiveness to the ease with which doctors can engage in research misconduct. Suggestions are made as to how these issues can be investigated and alternative incentives for career advancement are adumbrated. (shrink)

Objectivity, as one of the key attributes of science, has become an indispensable part of its ethos and a central theme of the philosophy of science. As such, it has been a subject of philosophical reflection by a number of authors. In our project – in which both philosophers of science and scientists participate – we examine the concept of objectivity in the natural sciences with the tools of experimental philosophy. We aim to identify specific operational dimensions of objectivity, those (...) with which current scientist actually work, thus making them accessible for further theoretical analysis and research. In this text, we present results from the first, qualitative phase of our research based on in-depth interviews and focus groups with scientists working in the Czech Republic. Further, we confront this empirical data with theoretical notions of objectivity. We also present other findings from the research and formulate hypotheses for the research’s subsequent phases. (shrink)

Understanding modeling in biology requires understanding how biology is organized as a discipline and how this organization influences the research practices of biologists. Biology includes a wide range of sub-disciplines, such as cell biology, population biology, evolutionary biology, molecular biology, and systems biology among others. Biologists in sub-disciplines such as cell, molecular, and systems biology believe that the use of a few experimental models allows them to discover biological universals, whereas biologists in sub-disciplines such as ecology and evolutionary biology believe (...) that the use of many different experimental and mathematical models is necessary in order to do this. Many practitioners of both approaches misunderstand best practices of modeling, especially those related to model testing. We stress the need for biologists to better engage with best practices and for philosophers of biology providing normative guidance for biologists to better engage with current developments in biology. This is especially important as biology transitions from a “data-poor” to a “data-rich” discipline. If 21st century biology is going to capitalize on the unprecedented availability of ecological, evolutionary, and molecular data, of computational resources, and of mathematical and statistical tools, biologists will need a better understanding of what modeling is and can be. (shrink)

Current Perspectives in Philosophy of Biology.

The aim of the paper is to clarify the concept of scientific ignorance: what is it, what are its sources, and when is it epistemically detrimental for science. I present a taxonomy of scientific ignorance, distinguishing between intrinsic and extrinsic sources. I argue that the latter can create a detrimental epistemic gap, which have significant epistemic and social consequences. I provide three examples from medical research to illustrate this point. To conclude, I claim that while some types of scientific ignorance (...) are inevitable and even desirable, other types of scientific ignorance are epistemically and ethically flawed and should be prevented. (shrink)

Principalele probleme cu care se confruntă oamenii de știință în lucrul cu seturile mari de date (Big Data), evidențiind principale aspecte etice, luând în considerare inclusiv legislația din Uniunea Europeană. După o scurtă Introducere despre Big Data, secțiunea Tehnologia prezintă aplicațiile specifice în cercetare. Urmează o abordare a principalelor probleme filosofice specifice în Aspecte filosofice, și Aspecte legale cu evidențierea problemelor etice specifice din Regulamentul UE privind protecția datelor 2016/679 (General Data Protection Regulation, "GDPR"). Secțiunea Probleme etice detaliază aspectele specifice (...) generate de Big Data. După o scurtă secțiune Cercetarea Big Data, finalizez lucrarea cu prezentarea Concluziilor pentru etica cercetării în lucrul cu Big CUPRINS: Abstract 1. Introducere - 1.1 Definiții - 1.2 Dimensiunile Big Data 2. Tehnologia - 2.1 Aplicații - - 2.1.1 În cercetare 3. Aspecte filosofice 4 Aspecte legale - 4.1 GDPR - - Etapele procesării datelor personale - - Principiile procesării datelor - - Politica de confidențialitate și transparența - - Scopurile procesării datelor - - Confidențialitate prin design și implicită - - Paradoxul (legal) al Big Data 5. Probleme etice - Etica în cercetare - Conștientizarea - Consimțământul - Controlul - Transparența - Încrederea - Proprietatea - Supravegherea și securitatea - Identitatea digitală - Realitatea ajustată - De-anonimizarea - Inegalitatea digitală - Confidențialitatea 6. Cercetarea Big Data Concluzii Bibliografie DOI: 10.13140/RG.2.2.27629.33761 . (shrink)

Citation-based metrics are increasingly used as a proxy to define representative, considerable, or significant papers. We challenge this belief by taking into account factors that may play a role in providing citations to a manuscript and whether/how those highly cited studies could shape a scientific field. A different approach to summarisation of relevant core publications within a topic is proposed.

The deep crisis in modern fundamental science development is ever more evident and openly recognised now even by mainstream, official science professionals and leaders. By no coincidence, it occurs in parallel to the world civilisation crisis and related global change processes, where the true power of unreduced scientific knowledge is just badly missing as the indispensable and unique tool for the emerging greater problem solution and further progress at a superior level of complex world dynamics. Here we reveal the mathematically (...) exact reason for the crisis in conventional science, containing also the natural and unified problem solution in the form of well-specified extension of usual, artificially restricted paradigm. We show how that extended, now causally complete science content provides various "unsolvable" problem solutions and opens new development possibilities for both science and society, where the former plays the role of the main, direct driver for the latter. We outline the related qualitative changes in science organisation, practice and purposes, giving rise to the sustainability transition in the entire civilisation dynamics towards the well-specified superior level of its unreduced, now well understood and universally defined complexity. (shrink)

ABSTRACTPossibly, the replication crisis constitutes the most important problem in psychology. It calls into question whether psychology is a science. Existing conceptualizations of replicability depend on effect sizes; the larger the population effect size, the greater the probability of replication. This is problematic and contributes to the replication crisis. A different conceptualization, not dependent on population effect sizes, is desirable. The proposed solution features the closeness of sample means to their corresponding population means, in both the original and replication experiments. (...) If the researcher has specified the sampling precision desired, it is possible to calculate the probability of replication, prior to data collection, and without dependence on the population effect size or expected population effect size. In addition, it is not necessary to know population means or standard deviations, nor sample means or standard deviations, to employ the proposed a priori way of thinking about... (shrink)

Francesco Guala once wrote that ‘The problem of extrapolation is a minor scandal in the philosophy of science’. This paper agrees with the statement, but for reasons different from Guala’s. The scandal is not, or not any longer, that the problem has been ignored in the philosophy of science. The scandal is that framing the problem as one of external validity encourages poor evidential reasoning. The aim of this paper is to propose an alternative—an alternative which constitutes much better evidential (...) reasoning about target systems of interest, and which makes do without consideration of external validity. (shrink)

Multiple simultaneous independent discoveries, so well enunciated by Robert K. Merton in the early 1960s but already discussed for several hundreds of years, is a classic concept in the sociology of science. In this paper, the concept of multiple simultaneous independent errors is proposed, analyzed, and discussed. The concept of Selective Pessimistic Induction is proposed and used to connect MIDs with MIEs. Five types of MIEs are discussed: multiple errors in the interpretation of experimental data or computational results; multiple misjudgments (...) of the value of another’s research results or conclusions; multiple cases of false anticipation of achieving a certain experimental result; multiples of ignoring or omitting relevant precedents; and multiple instances of failure due to a not-yet-conceived scientific concept or principle. Causal MIDs and MIEs are those that can be traced directly to antecedent knowledge. Acausal MIDs and MIEs are those involving a consequential and identifiable leap from antecedent knowledge. Examples of causal and acausal MIEs are provided, mostly but not exclusively from the discipline of chemistry. Comparisons are made between MIDs and MIEs. Topics for future research are discussed and implications of these concepts are proposed. (shrink)

Data which constitute satisfactory evidence in other contexts are sometimes not treated as valid evidence in the context of scientic conrmation. I give a justicatory explanation of this fact, appealing to the incentives, biases, and social situatedness of scientists.

We conducted two eye-tracking experiments investigating the processing of the Mandarin reflexive ziji in order to tease apart structurally constrained accounts from standard cue-based accounts of memory retrieval. In both experiments, we tested whether structurally inaccessible distractors that fulfill the animacy requirement of ziji influence processing times at the reflexive. In Experiment 1, we manipulated animacy of the antecedent and a structurally inaccessible distractor intervening between the antecedent and the reflexive. In conditions where the accessible antecedent mismatched the animacy cue, (...) we found inhibitory interference whereas in antecedent-match conditions, no effect of the distractor was observed. In Experiment 2, we tested only antecedent-match configurations and manipulated locality of the reflexive-antecedent binding (Mandarin allows non-local binding). Participants were asked to hold three distractors (animate vs. inanimate nouns) in memory while reading the target sentence. We found slower reading times when animate distractors were held in memory (inhibitory interference). Moreover, we replicated the locality effect reported in previous studies. These results are incompatible with structure-based accounts. However, the cue-based ACT-R model of Lewis and Vasishth ( 2005 ) cannot explain the observed pattern either. We therefore extend the original ACT-R model and show how this model not only explains the data presented in this article, but is also able to account for previously unexplained patterns in the literature on reflexive processing. (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)

This paper looks at an appeal to the authority of biomedical research that has recently been used by empirical economists to motivate and justify their methods. I argue that those who make this appeal mistake the nature of biomedical research. Randomised trials, which are said to have revolutionised biomedical research, are a central methodology, but according to only one paradigm. There is another paradigm at work in biomedical research, the inferentialist paradigm, in which randomised trials play no special role. I (...) outline the inferentialist alternative in broad strokes, apply it to a recent controversy in econometrics and draw some general conclusions concerning econometric methodology. (shrink)

Many natural scientists of the past and the present have imagined that they pursued their activity according to its own inherent rules in a realm distinctly separate from the business world, or at least in a realm where business tended to interfere with science from time to time, but was not ultimately an essential component, ‘because one thought that in science one possessed and loved something unselfish, harmless, self-sufficient, and truly innocent, in which man’s evil impulses had no part whatever’, (...) as Nietzsche once commented (Nietzsche 1974, p.106). With the extreme technological changes that have occurred in the last fifty years and the orchestrated management changes in the culture of science, it is now obvious that science is intimately tied to private businesses, industry, and society. Within this structure, the scientist has generally unknowingly defined him or herself in accordance with obsolete myths that have tended to handicap the scientist’s freedom of action, by obscuring the modern political and economic realities of science, and neglecting the inherent responsibilities of the scientist as a critical actor in the theater of human civilization. The increasing incorporation of academic science and private industry, and the governmentally supervised nature of modem academic science, has corrupted the traditional freedom and character of the scientist. In order to navigate oneself and find meaning within the new structure of science, scientists now desperately need a fresh ethos that at once considers modern realities of the politics and management of science, societal urgencies, and global politics, as well as establishing a moral perspective where modern scientists can be actors with their own intentionality and responsibility. -/- In the culture of science, myths and ideologies are of critical importance for the formation of the scientist, because these ideas determine how scientists conceive of themselves as professionals and free individuals. More importantly, these ideas determine how scientists approach scientific activity, which exists in a social context, and which ultimately has the potential to dramatically change the characteristics of civilization as it is played out on the political and technological battlefield. It is a commonly held notion in the community of the natural sciences that science now is essentially what it was when it was described by the Nobel laureates of the past; those sweet, cushioning, pleasant words consecrating the ‘temple of science’; the picture of a humble, rational, and noble Einstein is imprinted into our memories. By dismantling these obsolete myths of the scientist and surveying contemporary trends in science, this article will explore a more realistic perspective toward the field of science. The goal of this investigation is to determine the modern reality and ultimate meaning of ‘science as a vocation’ (Shorett 2003). Finally, moral philosophy will be demonstrated to be a critical clement in the self-assertion of the scientist and the elucidation of the meaning of science as a vocation in a global technological society. -/- From the Postscript, 2015: This article took final form when I was a postdoctoral researcher in Canada. Reading it now, I recognize the article still has value, despite its many flaws, hyperboles, and idealism. Many issues in the article have become increasingly relevant, such as the need to make constant trade-offs in courses of action and continuously search for more morally significant research paths. Perhaps the greatest goals in writing the article were to increase intellectual control over the path of my scientific research, to escape the increasing conformity and constraints on modern life, to participate in an open society, to formulate my personal goals and goal hierarchies, to dispel any delusions of overconfidence, and to not be corrupted. (shrink)

The analogy between science and theater work is so strict as to be normally taken for granted without the need of further specification. This implies that the analogy is completely ignored. Here I try to go in depth into the character of this analogy and to demonstrate how stopping and thinking about this issue could give some useful hints for solving problems that contemporary science is experiencing.

This paper develops an account of the opacity problem in medical machine learning (ML). Guided by pragmatist assumptions, I argue that opacity in ML models is problematic insofar as it potentially undermines the achievement of two key purposes: ensuring generalizability and optimizing clinician–machine decision-making. Three opacity amelioration strategies are examined, with explainable artificial intelligence (XAI) as the predominant approach, challenged by two revisionary strategies in the form of reliabilism and the interpretability by design. Comparing the three strategies, I argue that (...) interpretability by design is most promising to overcome opacity in medical ML. Looking beyond the individual opacity amelioration strategies, the paper also contributes to a deeper understanding of the problem space and the solution space regarding opacity in medical ML. (shrink)

Populists are often cast as deniers of rationality, creators of a climate of “post-truth,” and valuing tribe over truth and the rigors of science. Their critics claim the authority of rationality and empirical facts. Yet the critics no less than populists enable an environment of spurious claims and defective argumentation. This is especially true in the realm of science. An important case study is the account of scientific trust offered by a leading public intellectual and historian of science, Naomi Oreskes, (...) and the misapplication of that theory during the coronavirus pandemic. (shrink)

In the context of discovery-oriented hypothesis testing research, behavioral scientists widely accept a convention for false positive (α) and false negative error rates (β) proposed by Jacob Cohen, who deemed the general relative seriousness of the antecedently accepted α = 0.05 to be matched by β = 0.20. Cohen’s convention not only ignores contexts of hypothesis testing where the more serious error is the β-error. Cohen’s convention also implies for discovery-oriented hypothesis testing research that a statistically significant observed effect is (...) four times more probable to be a mistaken discovery than for a statistically significant true observed effect to be independently replicable. In the long run, Cohen’s convention thus is epistemically harmful to the development of a progressive science of human behavior, making its acceptance crucial in explaining the replication crisis in behavioral science. The balance between α- and β-errors generally ought to be struck using both epistemic and practical considerations. Yet epistemic considerations alone imply that making a genuine contribution to the body of knowledge in behavioral science requires error rates that are not only small but also symmetrical. (shrink)

Despite continued attention, finding adequate criteria for distinguishing “good” from “bad” scholarly journals remains an elusive goal. In this essay, I propose a solution informed by the work of Imre Lakatos and his methodology of scientific research programmes (MSRP). I begin by reviewing several notable attempts at appraising journal quality – focusing primarily on the impact factor and development of journal blacklists and whitelists. In doing so, I note their limitations and link their overarching goals to those found within the (...) philosophy of science. I argue that Lakatos’s MSRP and specifically his classifications of “progressive” and “degenerative” research programmes can be analogized and repurposed for the evaluation of scholarly journals. I argue that this alternative framework resolves some of the limitations discussed above and offers a more considered evaluation of journal quality – one that helps account for the historical evolution of journal-level publication practices and attendant contributions to the growth (or stunting) of scholarly knowledge. By doing so, the seeming problem of journal demarcation is diminished. In the process I utilize two novel tools (the mistake index and scite index) to further illustrate and operationalize aspects of the MSRP. (shrink)

Academic publishing is undergoing a highly transformative process, and many established rules and value systems that are in place, such as traditional peer review (TPR) and preprints, are facing unprecedented challenges, including as a result of post-publication peer review. The integrity and validity of the academic literature continue to rely naively on blind trust, while TPR and preprints continue to fail to effectively screen out errors, fraud, and misconduct. Imperfect TPR invariably results in imperfect papers that have passed through varying (...) levels of rigor of screening and validation. If errors or misconduct were not detected during TPR’s editorial screening, but are detected at the post-publication stage, an opportunity is created to correct the academic record. Currently, the most common forms of correcting the academic literature are errata, corrigenda, expressions of concern, and retractions or withdrawals. Some additional measures to correct the literature have emerged, including manuscript versioning, amendments, partial retractions and retract and replace. Preprints can also be corrected if their version is updated. This paper discusses the risks, benefits and limitations of these forms of correcting the academic literature. (shrink)

Social cognition is critical for successfully navigating social relationships. Current evidence suggests that older adults exhibit poorer performance in several core social-cognitive domains compared to younger adults. Neurocognitive decline is commonly discussed as one of the key arbiters of age-related decline in social-cognitive abilities. While evidence supports this notion, age effects are likely attributable to multiple factors. This paper aims to recontextualize past evidence by focusing issues of motivation, task design, and representative samples. In light of these issues, we identify (...) directions for future research to aide our understanding of social-cognitive aging. (shrink)

For model-based frequentist statistics, based on a parametric statistical model ${{\cal M}_\theta }$, the trustworthiness of the ensuing evidence depends crucially on the validity of the probabilistic assumptions comprising ${{\cal M}_\theta }$, the optimality of the inference procedures employed, and the adequateness of the sample size to learn from data by securing –. It is argued that the criticism of the postdata severity evaluation of testing results based on a small n by Rochefort-Maranda is meritless because it conflates [a] misuses (...) of testing with [b] genuine foundational problems. Interrogating this criticism reveals several misconceptions about trustworthy evidence and estimation-based effect sizes, which are uncritically embraced by the replication crisis literature. (shrink)

Objectivity in the sciences is a much-touted yet problematic concept. It is sometimes held up as characterising scientific knowledge, yet operational definitions are diverse and call for such paradoxical genius as the ability to see without a perspective, to predict repeatability, to elicit nature’s own self-revelation, or to discern the structure of reality with inerrancy. Here we propose a positive and general definition of objectivity based on work in the Reformational philosophy tradition. We recognise a suite of relation-frames–ways in which (...) things function and relate to each other, which can be analytically distinguished in the process of conceptual abstraction. These relation-frames also ground the diverse aspects of scientific analysis within which relationships and properties may be abstracted from entities and systems. We argue that objectivity can be understood as characteristic of representations that attempt to portray a subject in an earlier relation-frame than that in which it characteristically functions. In short, objectivity is projection. This proposal is exemplified from mathematics and the natural sciences and some possible objections to it are considered, as well as its extension to the social sciences. (shrink)

Open access-introduction into moral philosophy in German language that contains chapters on the concept of morality, on the development and the main positions of normative ethics, on meta-ethics, and on the various fields of applied ethics. One of its distinctive features is that it explicitly reflects on the role of morality and ethics in modern society and that it analyses the import of alternative conceptual and normative positions for determining this role. The book can be freely downloaded from the publisher's (...) website via the URL below. (shrink)

Psychological science is maturing and therefore transitioning from explorative to theory-driven research. While explorative research seeks to find something “new,” theory-driven research seeks to elaborate on already known and hence predictable effects. A consequence of these differences is that the quality of explorative and theory-driven research needs to be judged by distinct criterions that optimally support their respective development. Especially, theory-driven research needs to be judged by its methodological rigor. A focus on innovativeness, which is typical for explorative research, will (...) instead incentivize bad research practices (e.g., imprecise theorizing, ignoring previous research, parallel theories). To support the advancement of psychology, we must drop the innovation requirement for theory-driven research and instead require the strongest methods, which are marked by high internal and external validity. Precise theorizing needs to substitute novelty. Theories are advanced by requiring explicit, testable assumptions, and an explicit preference for one theory over another. These explicit and potentially wrong assumptions should not be silenced within the peer-review process, but instead be scrutinized in new publications. Importantly, these changes in scientific conduct need to be supported by senior researchers, especially, in their roles as editors, reviewers, and in the hiring process. An important obstacle to further theory-driven research is to measure scientific merit using researchers’ number of publications, which favors theoretically shallow and imprecise writing. Additionally, it makes publications the central target of scientific misconduct even though they are the main source of information for the scientific community and the public. To advance the field, researchers should be judged by their contribution to the scientific community (e.g., exchange with and support of colleagues, and mentoring). Another step to advance psychology is to clearly differentiate between measurement model and theory, and not to overgeneralize based on few stimuli, incidences, or studies. We will use ideas from the theory of science to underline the changes necessary within the field of psychology to overcome this existential replication crisis. (shrink)

We provide a novel articulation of the epistemic peril of p-hacking using three resources from philosophy: predictivism, Bayesian confirmation theory, and model selection theory. We defend a nuanced position on p-hacking: p-hacking is sometimes, but not always, epistemically pernicious. Our argument requires a novel understanding of Bayesianism, since a standard criticism of Bayesian confirmation theory is that it cannot represent the influence of biased methods. We then turn to pre-analysis plans, a methodological device used to mitigate p-hacking. Some say that (...) pre-analysis plans are epistemically meritorious while others deny this, and in practice pre-analysis plans are often violated. We resolve this debate with a modest defence of pre-analysis plans. Further, we argue that pre-analysis plans can be epistemically relevant even if the plan is not strictly followed—and suggest that allowing for flexible pre-analysis plans may be the best available policy option. (shrink)

ABSTRACTDespite the extensive literature on what questionable research practices are and how to measure them, the normative underpinnings of such practices have remained less explored. QRPs often fall into a grey area of justifiable and unjustifiable practices. Where to precisely draw the line between such practices challenges individual scholars and this harms science. We investigate QRPs from a normative perspective using the theory of communicative action. We highlight the role of the collective in assessing individual behaviours. Our contribution is a (...) framework that allows identification of when particular actions cross over from acceptable to unacceptable practice. Thus, this article provides grounds for developing scientific standards to raise the quality of scientific research. (shrink)

Les principaux problèmes rencontrés par les scientifiques qui travaillent avec des ensembles de données massives (mégadonnées, Big Data), en soulignant les principaux problèmes éthiques, tout en tenant compte de la législation de l'Union européenne. Après une brève Introduction au Big Data, la section Technologie présente les applications spécifiques de la recherche. Il suit une approche des principales questions philosophiques spécifiques dans Aspects philosophiques, et Aspects juridiques en soulignant les problèmes éthiques spécifiques du règlement de l'UE sur la protection des données (...) 2016/679 (General Data Protection Regulation, « GDPR »). La section Problèmes éthiques détaille les problèmes spécifiques générés par le big data. Après une brève section de Recherche de big data, sont présentées les Conclusions sur l’éthique de la recherche dans l’utilisation du big data. SOMMAIRE: Abstract 1. Introduction - 1.1 Définitions - 1.2 Les dimensions du big data 2. La technologie - 2.1 Applications - - 2.1.1 En recherche 3. Aspects philosophiques 4 Aspects juridiques - 4.1 RGPD (GDPR) - - Étapes du traitement des données personnelles - - Principes du traitement des données - - Politique de confidentialité et transparence - - Finalités du traitement des données - - Confidentialité par conception et confidentialité implicite - - Le paradoxe (juridique) des mégadonnées 5. Problèmes éthiques - L'éthique dans la recherche - Prise de conscience - Consentement - Contrôle - Transparence - Confiance - Propriété - Surveillance et sécurité - Identité numérique - Réalité ajustée - De-anonymisation - Inégalité numérique - Confidentialité 6. Recherche des mégadonnées Conclusions Bibliographie DOI: 10.13140/RG.2.2.10128.56328 . (shrink)

The replicability of findings in experimental psychology can be improved by distinguishing sharply between hypothesis-generating research and hypothesis-testing research. This distinction can be achieved by preregistration, a method that has recently attracted widespread attention. Although preregistration is fair in the sense that it inoculates researchers against hindsight bias and confirmation bias, preregistration does not allow researchers to analyze the data flexibly without the analysis being demoted to exploratory. To alleviate this concern we discuss how researchers may conduct blinded analyses. As (...) with preregistration, blinded analyses break the feedback loop between the analysis plan and analysis outcome, thereby preventing cherry-picking and significance seeking. However, blinded analyses retain the flexibility to account for unexpected peculiarities in the data. We discuss different methods of blinding, offer recommendations for blinding of popular experimental designs, and introduce the design for an online blinding protocol. (shrink)

Appendix 1 was incomplete in the initial online publication. The original article has been corrected.

Responding to recent concerns about the reliability of the published literature in psychology and other disciplines, we formed the X-Phi Replicability Project to estimate the reproducibility of experimental philosophy. Drawing on a representative sample of 40 x-phi studies published between 2003 and 2015, we enlisted 20 research teams across 8 countries to conduct a high-quality replication of each study in order to compare the results to the original published findings. We found that x-phi studies – as represented in our sample (...) – successfully replicated about 70% of the time. We discuss possible reasons for this relatively high replication rate in the field of experimental philosophy and offer suggestions for best research practices going forward. (shrink)

In a recent editorial published in Nature, the journal's editors comment on a new automated software that has been used to check findings in psychology publications. The editors express concern with the way in which the anonymous fact-checkers have proceeded, but at the same time, they underscore the crucial role of peer criticism for scientific progress and insist: "self-correction is at the heart of science." Brief as it is, the editorial showcases that peer criticism and the application of norms of (...) good research practice are very thorny issues indeed.It is essential for the functioning of science that empirical findings, arguments, as well as methodological approaches are scrutinized... (shrink)

Biomedical innovation and translation are increasingly emphasizing research using “big data.” The hope is that big data methods will both speed up research and make its results more applicable to “real-world” patients and health services. While big data research has been embraced by scientists, politicians, industry, and the public, numerous ethical, organizational, and technical/methodological concerns have also been raised. With respect to technical and methodological concerns, there is a view that these will be resolved through sophisticated information technologies, predictive algorithms, (...) and data analysis techniques. While such advances will likely go some way towards resolving technical and methodological issues, we believe that the epistemological issues raised by big data research have important ethical implications and raise questions about the very possibility of big data research achieving its goals. (shrink)

Hierarchies of evidence are an important and influential tool for appraising evidence in medicine. In recent years, hierarchies have been formally adopted by organizations including the Cochrane Collaboration [1], NICE [2,3], the WHO [4], the US Preventive Services Task Force [5], and the Australian NHMRC [6,7]. The development of such hierarchies has been regarded as a central part of Evidence-Based Medicine, a movement within healthcare which prioritises the use of epidemiological evidence such as that provided by Randomised Controlled Trials. Philosophical (...) work on the methodology of medicine has so far mostly focused on claims about the superiority of RCTs, and hence has largely neglected the questions of what hierarchies are, what assumptions they require, and how they affect clinical practice. This thesis shows that there is great variation in the hierarchies defended and in the interpretations they are, and can be, given. The interpretative assumptions made in using hierarchies are crucial to the content and defensibility of the underlying philosophical commitments concerning evidence and medical practice. Once this variation is been identified, it becomes clear that the little philosophical work that has been done so far affects only some hierarchies, under some interpretations. Modest interpretations offered by La Caze [11], conditional hierarchies like GRADE [12-14], and heuristic approaches such as that defended by Howick et al. [15,16] all survive previous philosophical criticism. This thesis extends previous criticisms by arguing that modest interpretations are so weak as to be unhelpful for clinical practice; that GRADE and similar conditional models omit clinically relevant information, such as information about variation in treatments’ effects and the causes of different responses to therapy; and that heuristic approaches lack the necessary empirical support. The conclusion is that hierarchies in general embed untenable philosophical assumptions: principally that information about average treatment effects backed by high-quality evidence can justify strong recommendations, and that the impact of evidence from individual studies can and should be appraised in isolation. Hierarchies are a poor basis for the application of evidence in clinical practice. The Evidence-Based Medicine movement should move beyond them and explore alternative tools for appraising the overall evidence for therapeutic claims. (shrink)