Concern about the integrity of empirical research has arisen in recent years in the light of studies showing the vast majority of publications in academic journals report positive results, many of these results are false and cannot be replicated, and many positive results are the product of data dredging and the application of flexible data analysis practices coupled with selective reporting. While a number of potential solutions have been proposed, the effects of these are poorly understood and empirical evaluation of (...) each would take many years. We propose that methods from the systems sciences be used to assess the effects, both positive and negative, of proposed solutions to the problem of declining research integrity such as study registration, Registered Reports, and open access to methods and data. In order to illustrate the potential application of systems science methods to the study of research integrity, we describe three broad types of models: one built on the characteristics of specific academic disciplines; one a diffusion of research norms model conceptualizing researchers as susceptible, “infected” and recovered; and one conceptualizing publications as a product produced by an industry comprised of academics who respond to incentives and disincentives. (shrink)

Leading animal models are powerful tools for translational research, but they also present obstacles. Poorly conducted preclinical research in animals is a common cause of translational failure, but even when such research is well-designed and carefully executed, challenges remain. In particular, dominant models may bias research directions, elide essential aspects of human disease, omit important context, or subtly shift research targets. Recognizing these stumbling blocks can help us find ways to avoid them: employing a wider range of models, incorporating more (...) realistic environmental conditions, better aligning studies between animals and patients, and focusing on human biology and therapeutic goals. Such changes are costly; but insisting it would be impractical or unrealistic to change strategies offers no way out of the current impasse. Rather, we must acknowledge the obstacles as well as the advantages presented by core models, and direct some of our investments in translational research toward getting around them. The dominance of biomedical research by a handful of animal models introduces subtle but significant obstacles to translation. Recognizing these obstacles is a critical first step toward finding ways around them; this paper describes how dominant models can create roadblocks, and suggests strategies to improve the efficiency of translation from animal models to humans. (shrink)

The “reproducibility crisis” has been a highly visible source of scientific controversy and dispute. Here, I propose and review several avenues for identifying and prioritizing research studies for the purpose of targeted validation. Of the various proposals discussed, I identify scientific data science as being a strategy that merits greater attention among those interested in reproducibility. I argue that the tremendous potential of scientific data science for uncovering high-value research studies is a significant and rarely discussed benefit of the transition (...) to a fully open-access publishing model. (shrink)

This study tested the hypothesis that in the minds of adult religious adherents, acquired beliefs about the extraordinary characteristics of God coexist with, rather than replace, an initial representation of God formed by co-option of the evolved person concept. In three experiments, Christian religious adherents were asked to evaluate a series of statements for which core intuitions about persons and acquired Christian beliefs about God were consistent or inconsistent. Participants were less accurate and slower to respond to inconsistent versus consistent (...) statements, suggesting that the core intuitions both coexisted alongside and interfered with the acquired beliefs. In Experiment 2 when responding under time pressure participants were disproportionately more likely to make errors on inconsistent versus consistent statements than when responding with no time pressure, suggesting that the resolution of interference requires cognitive resources the functioning of which decreases under cognitive load. In Experiment 3 a plausible alternative interpretation of these findings was ruled out by demonstrating that the response accuracy and time differences on consistent versus inconsistent statements occur for God—a supernatural religious entity—but not for a natural religious entity. (shrink)

No scientific conclusion follows automatically from a statistically non-significant result, yet people routinely use non-significant results to guide conclusions about the status of theories (or the effectiveness of practices). To know whether a non-significant result counts against a theory, or if it just indicates data insensitivity, researchers must use one of: power, intervals (such as confidence or credibility intervals), or else an indicator of the relative evidence for one theory over another, such as a Bayes factor. I argue Bayes factors (...) allow theory to be linked to data in a way that overcomes the weaknesses of the other approaches. Specifically, Bayes factors use the data themselves to determine their sensitivity in distinguishing theories (unlike power), and they make use of those aspects of a theory’s predictions that are often easiest to specify (unlike power and intervals, which require specifying the minimal interesting value in order to address theory). Bayes factors provide a coherent approach to determining whether non-significant results support a null hypothesis over a theory, or whether the data are just insensitive. They allow accepting and rejecting the null hypothesis to be put on an equal footing. Concrete examples are provided to indicate the range of application of a simple online Bayes calculator, which reveal both the strengths and weaknesses of Bayes factors. (shrink)

In light of the widespread existence of financial and non-financial issues that contribute to the appearance or fact of conflict of interest, it is proposed that conflict of interest should generally be assumed, no matter the source of financial support or the expressed declarations of conflicts and even with respect to one’s own work. No new model is advanced for modification of peer-review processes or for elaboration of author declarations of interest. Researchers should be assessing the quality of published work (...) as best they can and make their own decisions on the appropriate use of the work. While some apparent sources of conflict are likely more obvious and serious than others, even subtler biases can influence scientific reports. Ignoring peer-reviewed contributions because of conflict-of-interest concerns is discouraged. Listening skeptically to all sources, including yourself, is encouraged. (shrink)

The three main approaches in statistical inference—classical statistics, Bayesian and likelihood—are in current use in phylogeny research. The three approaches are discussed and compared, with particular emphasis on theoretical properties illustrated by simple thought-experiments. The methods are problematic on axiomatic grounds, extra-mathematical grounds relating to the use of a prior or practical grounds. This essay aims to increase understanding of these limits among those with an interest in phylogeny.

Science traditionally is taught as a linear process based on logic and carried out by objective researchers following the scientific method. Practice of science is a far more nuanced enterprise, one in which intuition and passion become just as important as objectivity and logic. Whether the activity is committing to study a particular research problem, drawing conclusions about a hypothesis under investigation, choosing whether to count results as data or experimental noise, or deciding what information to present in a research (...) paper, ethical challenges inevitably will arise because of the ambiguities inherent in practice. Unless these ambiguities are acknowledged and their sources understood explicitly, responsible conduct of science education will not adequately prepare the individuals receiving the training for the kinds of decisions essential to research integrity that they will have to make as scientists. (shrink)

This paper examines a looming reproducibility crisis in the core of the hard sciences. Namely, it concentrates on molecular modeling and simulation (MMS), a family of methods that predict properties of substances through computing interactions on a molecular level and that is widely popular in physics, chemistry, materials science, and engineering. The paper argues that in order to make quantitative predictions, sophisticated models are needed which have to be evaluated with complex simulation procedures that amalgamate theoretical, technological, and social factors (...) – leading to problems with reproducibility. Thus, for methodological reasons, the predictive success causes a reproducibility problem. (shrink)

While the common procedure of statistical significance testing and its accompanying concept of p-values have long been surrounded by controversy, renewed concern has been triggered by the replication crisis in science. Many blame statistical significance tests themselves, and some regard them as sufficiently damaging to scientific practice as to warrant being abandoned. We take a contrary position, arguing that the central criticisms arise from misunderstanding and misusing the statistical tools, and that in fact the purported remedies themselves risk damaging science. (...) We argue that banning the use of p-value thresholds in interpreting data does not diminish but rather exacerbates data-dredging and biasing selection effects. If an account cannot specify outcomes that will not be allowed to count as evidence for a claim—if all thresholds are abandoned—then there is no test of that claim. The contributions of this paper are: To explain the rival statistical philosophies underlying the ongoing controversy; To elucidate and reinterpret statistical significance tests, and explain how this reinterpretation ameliorates common misuses and misinterpretations; To argue why recent recommendations to replace, abandon, or retire statistical significance undermine a central function of statistics in science: to test whether observed patterns in the data are genuine or due to background variability. (shrink)

I draw lessons from experimental economics. I argue that the lack of mathematical formalism cannot be usefully thought as the cause of the underappreciation of contextual and generalizability considerations. Instead, this lack is problematic because it hinders a clear relationship between theory and quantitative predictions. I also advocate a pragmatic policy-focused approach as a partial remedy to the generalizability problem.

There is much discussion in the media and some of the scientific literature of how many of the conclusions from scientific research should be doubted. These critiques often focus on studies – typically in non‐experimental spheres of biomedical and social sciences – that search large datasets for novel correlations, with a risk that inappropriate statistical evaluations might yield dubious conclusions. By contrast, results from experimental biological research can often be interpreted largely without statistical analysis. Typically: novel observation(s) are reported, and (...) an explanatory hypothesis is offered; multiple labs undertake experiments to test the hypothesis; interpretation of the results may refute the hypothesis, support it or provoke its modification; the test/revise sequence is reiterated many times; and the field moves forward. I illustrate this experimental/non‐experimental dichotomy by examining the contrasting recent histories of: (a) our remarkable and growing understanding of how several inositol‐containing phospholipids contribute to the lives of eukaryote cells; and (b) the difficulty of achieving any agreed mechanistic understanding of why consuming dietary supplements of inositol is clinically beneficial in some metabolic diseases. (shrink)

As machine learning has gradually entered into ever more sectors of public and private life, there has been a growing demand for algorithmic explainability. How can we make the predictions of complex statistical models more intelligible to end users? A subdiscipline of computer science known as interpretable machine learning (IML) has emerged to address this urgent question. Numerous influential methods have been proposed, from local linear approximations to rule lists and counterfactuals. In this article, I highlight three conceptual challenges that (...) are largely overlooked by authors in this area. I argue that the vast majority of IML algorithms are plagued by (1) ambiguity with respect to their true target; (2) a disregard for error rates and severe testing; and (3) an emphasis on product over process. Each point is developed at length, drawing on relevant debates in epistemology and philosophy of science. Examples and counterexamples from IML are considered, demonstrating how failure to acknowledge these problems can result in counterintuitive and potentially misleading explanations. Without greater care for the conceptual foundations of IML, future work in this area is doomed to repeat the same mistakes. (shrink)

In this work, we explore the epistemic import of the value-ladenness of Neyman-Pearson’s Theory of Testing Hypotheses by reconstructing and extending Daniel Steel’s argument for the legitimate influence of pragmatic values on scientific inference. We focus on how to properly understand N-P’s pragmatic value-ladenness and the epistemic reliability of N-P. We develop an account of the twofold influence of pragmatic values on N-P’s epistemic reliability and replicability. We refer to these two distinguished aspects as “direct” and “indirect”. We discuss the (...) replicability of experiments in terms of the indirect aspect and the replicability of outcomes in terms of the direct aspect. We argue that the influence of pragmatic values is beneficial to N-P’s epistemic reliability and replicability indirectly. We show that while the direct influence of pragmatic values can be beneficial, its negative effects on reliability and replicability are also unavoidable in some cases, with the direct and indirect aspects possibly being incongruent. (shrink)

Funerals are a reflective practice to bid farewell to the departed soul. Different religions, cultural traditions, rituals, and social beliefs guide how funeral practices take place. Family and friends gather together to support each other in times of grief. However, during the coronavirus pandemic, the way funerals are taking place is affected by the country's rules and region to avoid the spread of infection. The present study explores the media portrayal of public sentiments over funerals. In particular, the present study (...) tried to identify linguistic dimensions associated with lexical components of social processes, affective processes, fear, and disgust. An exhaustive search of newspaper coverage of funeral and related articles was made for a specific corona period. After an initial screening for the details and language used, a total of 46 newspaper articles on funerals were finalized for the analysis. Linguistic Inquiry and Word Count (LIWC) software was used to determine the association between linguistic dimensions of function words and words related to social and affective processes, as presented in the newspaper articles. Sentiment Analysis and Cognition Engine (SEANCE) was applied for the analysis of sentiment, social cognition, and social order. Bayesian correlation analysis and regression revealed positive and significant associations between function words and affective processes, between pronouns and social processes, and between negative adjectives and psychological processes of fear and disgust. Also, significant negative associations were found between polarity nouns and psychological processes of fear and disgust and between polarity verbs and psychological processes of fear and disgust. Bayes factor 10 provides strong evidence in favor of the study hypotheses. The media is influenced by the prevailing sentiments in society and reflects their perception of the current social order and beliefs. The findings provide a glimpse into the prevailing sentiment of society through the lens of media coverage. These understandings are expected to enhance our observations of how people express their feelings over the loss of their loved ones and help mental health professionals develop their therapeutic protocols to treat the coronavirus disease 2019 (COVID-19)-affected population. (shrink)

Universities are seldom lauded publicly for maintaining good processes and practices; instead, media stories commonly focus on shortcomings. Furthermore, universities, even when doing everything right, sometimes are unfairly targeted for criticism in circumstances in which making a public defence is difficult. A prominent case at the University of Wollongong shows how defending a university’s integrity can be hampered by confidentiality requirements, lack of public understanding of thesis examination processes and of disciplinary expectations, and university procedures not designed for extraordinary attacks. (...) The implication is that there can be value in fostering greater awareness of the ways that universities and disciplinary fields operate, and reconsidering procedures with an eye towards possible attacks, both external and internal. (shrink)

The main problems faced by scientists in working with Big Data sets, highlighting the main ethical issues, taking into account the legislation of the European Union. After a brief Introduction to Big Data, the Technology section presents specific research applications. There is an approach to the main philosophical issues in Philosophical Aspects, and Legal Aspects with specific ethical issues in the EU Regulation on the protection of natural persons with regard to the processing of personal data and on the free (...) movement of such data, and repealing Directive 95/46/EC (Data Protection Directive - General Data Protection Regulation, "GDPR"). The Ethics Issues section details the specific aspects of Big Data. After a brief section of Big Data Research, I finalize my work with the presentation of Conclusions on research ethics in working with Big Data. -/- ISBN 978-606-033-307-4 , DOI: 10.58679/MM14975 . (shrink)

The past ten years have seen multiple attempts to estimate the relation between the global personality trait extraversion and compatibilist free will judgments. Here, we contribute to that line of research by conducting a meta-analysis of 17 published and eight unpublished studies (N = 2,811) estimating that relation. Overall, the mean effect size was modest but remarkably robust across materials, locations, and labs (z =.19, 95% CI.15-.24, p <.001). No significant publication bias was detected in the studies (t (23) = (...) 1.88, p =.07). While there was no significant heterogeneity in the studies (Q (24) = 34.42, p =.08, I2 = 26.05), a moderator analysis suggested that the effect is strongest in cases that contain highly affective actions (e.g., murder) (z =.22, 95% CI.17-.28, p <.001) and weakest in cases that contain actions with low affect (e.g., asking whether free will is compatible with determinism) (z =.09, 95% CI -.05-.23, p =.22). The meta-analysis provides additional evidence that extraversion is related to compatibilist free will judgments and helps to identify opportunities to discover boundary conditions and more proximal causal mechanisms for the relation. The results of the meta-analysis also have implications for informed decision making. (shrink)

Once an experiment is done, the observations have been made and the data have been analyzed, what should scientists communicate to the world at large, and how should they do it? This, I will argue, is an intricate question, and one that philosophers can make a contribution to. I will illustrate these points by reference to the debate between Fisher and Neyman & Pearson in the 1950s, which I take to be, at heart, a debate about norms of scientific communication. (...) I will argue that scientists need a richer set of tools for communicating epistemic states that may be very nuanced, and will point to way in which philosophers can contribute. (shrink)

Empirical success is a central criterion for scientific decision-making. Yet its understanding in philosophical studies of science deserves renewed attention: Should philosophers think differently about the advancement of science when they deal with the uncertainty of outcome in ongoing research in comparison with historical episodes? This paper argues that normative appeals to empirical success in the evaluation of competing scientific explanations can result in unreliable conclusions, especially when we are looking at the changeability of direction in ongoing investigations. The challenges (...) we encounter arise from the inherent dynamics of disciplinary and experimental objectives in research practice. In this paper we discuss how these dynamics inform the evaluation of empirical success by analyzing three of its requirements: data accommodation, instrumental reliability, and predictive power. We conclude that the assessment of empirical success in developing inquiry is set against the background of a model’s interactive success and prospective value in an experimental context. Our argument is exemplified by the analysis of an apparent controversy surrounding the model of a quantum nose in research on olfaction. Notably the public narrative of this controversy rests on a distorted perspective on measures of empirical success. (shrink)

P-hacking or data dredging involves manipulation of the research data in order to obtain a statistically significant result. The reasons behind P-hacking and the consequences of the same are discussed in the present manuscript.

Anglophone musicologists read the cultural theorist Slavoj Žižek more than they read the French psychoanalyst Jacques Lacan, and they are more concerned with Žižekian academia than they are with Lacan’s clinical practice. Two major problems emerge: Lacan is conflated with Žižek, and Lacan is conflated with Kant. As a result, analytic discourse is confused with post-modern academia as well as an eighteenth-century master-discourse on the Sublime. According to the author’s argument, Lacanian musicology is a misnomer, for it in fact refers (...) to Žižekian musicology, and what musicologists call the Lacanian Real is not really Lacanian. The re-branding of the Kantian Sublime and/or the Thing as the Lacanian Real is not necessary; it is a symptom of confusion. The article concludes with a cautious recommendation, pertinent to the study of music and discourses. (shrink)

Scientific integrity cannot be adequately ensured by appeals to the ethical principles of individual researchers. Research fraud has become a public scandal, exacerbated by our inability accurately to judge its extent. Current reliance on peer review of articles ready for publication as the sole means to control the quality and integrity of the majority of research has been shown to be inadequate, partly because faults in the research process may be concealed and partly because anonymous peer review is itself imperfect. (...) Consequently, the scientific literature is mixed, with the reader unable always to distinguish the good articles from the bad. Scientific research is subject to market forces that will always provide a motivation for a range of misdemeanours. This has led to a ‘market for lemons’. Regulations, and sanctions against miscreants, need to be modelled on those historically found necessary to limit financial fraud. Practical and effective systems of process control and audit have already been devised to ensure the integrity of clinical and pre-clinical research. These should be adapted for use in a much wider range of research activities. (shrink)

Critically growing problems of fundamental science organisation and content are analysed with examples from physics and emerging interdisciplinary fields. Their origin is specified and new science structure (organisation and content) is proposed as a unified solution.

Objective: Ethical guidelines are designed to ensure benefits, protection and respect of participants in clinical research. Clinical trials must now be registered on open-access databases and provide details on ethical considerations. This systematic survey aimed to determine the extent to which recently registered clinical trials report the use of standard of care and post-trial obligations in trial registries, and whether trial characteristics vary according to setting. Methods: We selected global randomized trials registered on http://www.clinicaltrials.gov and http://www.controlled-trials.com. We searched for intervention (...) trials of HIV/AIDS, malaria, and tuberculosis from 9 October 2004, the date of the most recent version of the Helsinki Declaration, to 10 April 2007. Results: We collected data from 312 trials. Fifty-eight percent (58%, 95% CI = 53 to 64) of trial protocols report informed consent. Fifty-eight percent (58%, 95% CI = 53 to 64) of trials report active controls. Almost no trials (1%, 95% CI = 0.5 to 3) mention post-trial provisions. Most trials measure surrogate outcomes. Twenty percent (20%, 95% CI = 16 to 25) of trials measure patient-important outcomes, such as death; and the odds that these outcomes are in a low income country are five times greater than for a developed country (odds ratio (OR) 5.03, 95% CI = 2.70 to 9.35, p = < 0.001). Pharmaceutical companies are involved in 28% (CI = 23 to 33) of trials and measure surrogate outcomes more often than nonpharmaceutical companies (OR 2.45, 95% CI = 1.18 to 5.09, p = 0.31). Conclusion: We found a large discrepancy in the quality of reporting and approaches used in trials in developing settings compared to wealthier settings. (shrink)

Many philosophers of science and methodologists have argued that the ability to repeat studies and obtain similar results is an essential component of science. A finding is elevated from single observation to scientific evidence when the procedures that were used to obtain it can be reproduced and the finding itself can be replicated. Recent replication attempts show that some high profile results – most notably in psychology, but in many other disciplines as well – cannot be replicated consistently. These replication (...) attempts have generated a considerable amount of controversy, and the issue of whether direct replications have value has, in particular, proven to be contentious. However, much of this discussion has occurred in published commentaries and social media outlets, resulting in a fragmented discourse. To address the need for an integrative summary, we review various types of replication studies and then discuss the most commonly voiced concerns about direct replication. We provide detailed responses to these concerns and consider different statistical ways to evaluate replications. We conclude there are no theoretical or statistical obstacles to making direct replication a routine aspect of psychological science. (shrink)

The diversified methodology and expertise of interdisciplinary research teams provide the opportunity to overcome the limited perspectives of individual disciplines. This is particularly true at the interface of Robotics, Neuroscience, and Psychology as the three fields have quite different perspectives and approaches to offer. Nonetheless, aligning backgrounds and interdisciplinary expectations can present challenges due to varied research cultures and practices. Overcoming these challenges stands at the beginning of each productive collaboration and thus is a mandatory step in cognitive neurorobotics. In (...) this article, we share eight lessons that we learned from our ongoing interdisciplinary project on human-robot and robot-robot interaction in social settings. These lessons provide practical advice for scientists initiating interdisciplinary research endeavors. Our advice can help to avoid early problems and deal with differences between research fields, prepare for and anticipate challenges, align project expectations, and speed up research progress, thus promoting effective interdisciplinary research across Robotics, Neuroscience, and Psychology. (shrink)

Wood, Kressel, Joshi, and Louie’s (2014) meta-analysis of menstrual cycle influences on mate preferences identified three artifacts that influenced study findings: imprecise estimates of the fertile phase, decline over time, and publication effects. These artifacts also were evident in another recent meta-analysis by Gildersleeve, Haselton, and Fales (2014a). This consistent evidence of artifacts is not challenged by Gildersleeve et al.’s (2014b) failure to find another artifact–chasing significance levels. In addition, Wood et al. correctly coded the findings of Gangestad and colleagues’ (...) research, given the variation in their reporting formats and inclusion criteria, which in some studies included only 54% of the sample. The controversy over menstrual cycle effects could be beneficial in increasing interest in publishing null results as well as in identifying evolutionary models that build on women’s capacity to regulate reproduction according to societal roles. (shrink)

Research Integrity (RI) is high on the agenda of both institutions and science policy. The European Union as well as national ministries of science have launched ambitious initiatives to combat misconduct and breaches of research integrity. Often, such initiatives entail attempts to regulate scientific behavior through guidelines that institutions and academic communities can use to more easily identify and deal with cases of misconduct. Rather than framing misconduct as a result of an information deficit, we instead conceptualize Questionable Research Practices (...) (QRPs) as attempts by researchers to reconcile epistemic and social forms of uncertainty in knowledge production. Drawing on previous literature, we define epistemic uncertainty as the inherent intellectual unpredictability of scientific inquiry, while social uncertainty arises from the human-made conditions for scientific work. Our core argument—developed on the basis of 30 focus group interviews with researchers across different fields and European countries—is that breaches of research integrity can be understood as attempts to loosen overly tight coupling between the two forms of uncertainty. Our analytical approach is not meant to relativize or excuse misconduct, but rather to offer a more fine-grained perspective on what exactly it is that researchers want to accomplish by engaging in it. Based on the analysis, we conclude by proposing some concrete ways in which institutions and academic communities could try to reconcile epistemic and social uncertainties on a more collective level, thereby reducing incentives for researchers to engage in misconduct. (shrink)

This paper introduces the concept of ‘hyper-ambition’ in academia as a contributing factor to what has been termed a ‘replication crisis’ across some sciences. The replication crisis is an umbrella term that covers a range of ‘questionable research practices’, from sloppy reporting to fraud. There are already many proposals to address questionable research practices, some of which focus on the values, norms, and motivations of researchers and institutes, and suggest measures to promote research integrity. Yet it is not easy to (...) promote integrity in hyper-competitive academic environments that value high levels of ambition. I argue that in such contexts, it is as likely that a kind of hyper-ambition is fostered that (inadvertently or otherwise) prioritises individual success above all, including to the detriment of scientific quality. In addition, efforts to promote values like integrity falter because they rely on sufficient uniformity in motivations or tendencies. Codes and guidance promoting integrity are, however, likely to influence those for whom such values are not optional, while others simply find ways around them. To demonstrate this I offer a thought experiment in which we consider the imaginary working situations of two ordinary academics. I conclude that tackling questionable research practices in the light of the replication crisis requires robust ‘top down’ measures that expect and accommodate a broader range of academic values, motivations, and tendencies, while challenging those that help to promote hyper-ambition. (shrink)

Scientists often respond to failures to replicate by citing differences between the experimental components of an original study and those of its attempted replication. In this paper, we investigate these purported mismatch explanations. We assess a body of failures to replicate in neuroscience studies on spinal cord injury. We argue that a defensible mismatch explanation is one where a mismatch of components is a difference maker for a mismatch of outcomes, and the components are relevantly different in the follow-up study, (...) given the scope of the original study. With this account, we argue that not all differences between studies are meaningful, even if they are difference makers. As our examples show, focusing only on these differences results in disregarding the representativeness of the original experiment’s components and the scope of its outcomes, undercutting other epistemic aims, such as translation, in the process. (shrink)

This articles suggests that the root of the current crisis in modern scientific innovation is mainly due to the method that science applies towards the real world. The scientific method reduces its possibilities by not considering the comprehensiveness of the human person, i.e. science is impersonal. Philosophers of science in the 20th century have identified this anthropological reductionism and further detected the limits of the scientific method. The lack of alternative solutions leads science into a cul-de-sac. The notion of crisis, (...) recently pointed out by Leonardo Polo’s Transcendental Anthropology, allows us to detect the limit, to abandon that limit and to open knowledge to further dimensions of unrestricted novelty such as freedom or love. Here we highlight the following distinctions: firstly, the state of crisis and the critical conscience, secondly, the ‘desperate vs. puzzle-solver’ critical conscience, thirdly, the limit of science and its abandonment. (shrink)

The primary aim of this study was to investigate the relation between self-perceived executive functions and the school achievement of young adolescents, while controlling for parental education and sex. We specifically focused on executive aspects of daily life behavior and the higher-order EFs, as measured with self-report, rather than on the more basic EFs which have been the primary focus of prior investigations. In two independent samples of sixth graders, students evaluated their EFs on a self-report questionnaire, the Amsterdam Executive (...) Functioning Inventory. School achievement in the domains of mathematics and reading comprehension were evaluated with nationally used, norm-based achievement tests. Results revealed that the self-perceived EFs of young adolescents were significantly correlated with their school achievement in both study samples. School achievement was also correlated with the level of parental education, but the factor sex did not have such influence. In study 1, self-perceived EFs explained additional variance in school achievement, while controlling for parental education and sex. In study 2, this was only the case for the most robust measure of school achievement, i.e., the end-of-primary-school final achievement test. Furthermore, besides the relation with achievement tests, we also found a relation between self-perceived EFs and teacher ratings behavioral problems in the classroom. Together, our findings imply that young students can properly reflect on the effectiveness and appropriateness of their EFs in a way that is relevant to their academic achievement and classroom behavior. The findings underscore the importance of considering the development of EFs and parental education in the evaluation of academic achievements in early adolescence. (shrink)

Research integrity is usually discussed in terms of responsibilities that individual researchers bear towards the scientific work they conduct, as well as responsibilities that institutions have to enable those individual researchers to do so. In addition to these two bearers of responsibility, a third category often surfaces, which is variably referred to as culture and practice. These notions merit further development beyond a residual category that is to contain everything that is not covered by attributions to individuals and institutions. This (...) paper discusses how thinking in RI can take benefit from more specific ideas on practice and culture. We start by articulating elements of practice and culture, and explore how values central to RI are related to these elements. These insights help identify additional points of intervention for fostering responsible conduct. This helps to build “cultures and practices of research integrity”, as it makes clear that specific times and places are connected to specific practices and cultures and should have a place in the debate on Research Integrity. With this conceptual framework, practitioners as well as theorists can avoid using the notions as residual categories that de facto amount to vague, additional burdens of responsibility for the individual. (shrink)

While the importance of mechanisms in determining causality in medicine is currently the subject of active debate, the role of mechanistic reasoning in clinical practice has received far less attention. In this paper we look at this question in the context of the treatment of a particular individual, and argue that evidence of mechanisms is indeed key to various aspects of clinical practice, including assessing population-level research reports, diagnostic as well as therapeutic decision making, and the assessment of treatment effects. (...) We use the pulmonary condition bronchiectasis as a source of examples of the importance of mechanistic reasoning to clinical practice. (shrink)