It has been argued that supervenience generates unavoidable confounding problems for interventionist accounts of causation, to the point that we must choose between interventionism and supervenience. According to one solution, the dilemma can be defused by excluding non-causal determinants of an outcome as potential confounders. I argue that this solution undermines the methodological validity of causal tests. Moreover, we don’t have to choose between interventionism and supervenience in the first place. Some confounding problems are effectively circumvented by experimental designs routinely (...) employed in science. The remaining confounding issues concern the physical interpretation of variables and cannot be solved by choosing between interventionism and supervenience. (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)

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)

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)

In this article, the authors use the context of childbirth to consider the power that is endemic in certain forms of evidence within maternity care research. First, there is consideration of how the current evidence hierarchy and experimental‐based studies are the gold standard to determine and direct women's maternity experiences, although this can be at the detriment of care and irrespective of women's needs. This is followed by a critique of how the predominant means to assess women's experiences via satisfaction (...) surveys is of limited utility, offering impartial and restricted insights to assess the quality of care provision. A counter position of hermeneutic phenomenology as research method is then described. This approach offers an alternative perspective by penetrating the taken‐for‐granted ordinariness of an event (such as childbirth) to elicit rich emic meanings. Whilst all approaches to understanding maternity care have a place, depending on the question(s) being asked, the contribution of phenomenology is how it can uncover a depth of contextual understanding into what matters to women and to inform and transform care delivery. (shrink)

Retractions of COVID-19 literature in both preprints and the peer-reviewed literature serve as a reminder that there are still challenging issues underlying the integrity of the biomedical literature. The risks to academia become larger when such retractions take place in high-ranking biomedical journals. In some cases, retractions result from unreliable or nonexistent data, an issue that could easily be avoided by having open data policies, but there have also been retractions due to oversight in peer review and editorial verification. As (...) COVID-19 continues to affect academics and societies around the world, failures in peer review might also constitute a public health risk. The effectiveness by which COVID-19 literature is corrected, including through retractions, depends on the stringency of measures in place to detect errors and to correct erroneous literature. It also relies on the stringent implementation of open data policies. (shrink)

PurposeThe issue of “predatory” publishing and the scholarly value of journals that claim to operate within an academic framework, namely, by using peer review and editorial quality control, but do not, while attempting to extract open access or other publication-related fees, is an extremely important topic that affects academics around the globe. Until 2017, global academia relied on two now-defunct Jeffrey Beall “predatory” OA publishing blacklists to select their choice of publishing venue. This paper aims to explore how media has (...) played a role in spinning public impressions about this issue.Design/methodology/approachThe authors focus on a 2017New York Timesarticle by Gina Kolata, on a selected number of peer reviewed published papers on the topic of “predatory” publications and on an editorial by the Editor-in-Chief ofREM, a SciELO- and Scopus-indexed OA journal.FindingsThe Kolata article offers biased, inaccurate and potentially misleading information about the state of “predatory” publishing: it relies heavily on the assumption that the now-defunct Beall blacklists were accurate when in fact they are not; it relies on a paper published in a non-predatory non-OA journal that claimed incorrectly the existence of financial rewards by faculty members of a Canadian business school from “predatory” publications; it praised a sting operation that used methods of deception and falsification to achieve its conclusions. The authors show how misleading information by theNew York Timeswas transposed downstream via theREMeditorial.Originality/valueEducation of academics. (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)

This article describes contrasting ideas for a set of topics in epidemiological thinking. The premise underlying this contribution to the special edition is that researchers develop their epidemiological thinking over time through interactions with other researchers who have a variety of in-practice commitments, such as to kinds of cases and methods of analysis, and not simply to a philosophical framework for explanation. I encourage discussants from philosophy and epidemiology to draw purposefully from across a range of topics and contrasting positions, (...) and thereby pursue critical thinking in the sense of understanding ideas and practices better when we examine them in relation to alternatives. After an initial topic concerning practices for developing epidemiological literacy, a number of conceptual steps follow—the characterization of the very phenomena we might be concerned with, the scope and challenges of the field of epidemiology, the formulation of categories—before linking associations, predictions, causes and interventions and examining the confounding of purported links. Building on that conceptual basis, the remaining topics consist of issues or angles of analysis related to the complexities of inequalities within and between populations, context, and changes over the life course. The organization of topics derives from a graduate course that I teach that aims for epidemiological literacy, not technical ability in statistical formulas and data analysis, and shares the underlying premise and critical thinking goals of this article. During the topic-by-topic description, some assertions about explanation and intervention emerge, notably, that epidemiological–philosophical discussion about causality often leaves unclear or unexamined whether a modifiable factor shown to have been associated with a difference in the data from past observations should be thought of as factor that, when modified, would generate that difference going forward. The article concludes with a “Limitations of this Study” section that teases out different kinds of description–prescription relationship that are implied in undertaking philosophy of epidemiology and identifies some other considerations that are implied but not emphasized by this article. (shrink)

Mutually supporting methodologies are necessary for building a convincing case establishing a particular effect. Strengths and weaknesses of four empirical methods are discussed. Econometric methods quantify the relative importance of different factors and may assess the time frame over which constitutions matter, but have difficulties in dealing with nonlinear interactions among constitutional and cultural details. Cluster analysis can be a pre-requisite to other methods, and an analytic method in itself, useful for identifying the details that really matter and discovering surprising (...) patterns in the data. I discuss the application of cluster analysis on the Comparative Constitutions Project database. Qualitative comparative analysis can reveal the hidden structure of interactions among different variables, but robustness checks are difficult to perform. Case studies are useful for distinguishing between rules-in-use and rules-in-form and for discovering important informal aspects. They can deal with com.. (shrink)

Research misconduct is an alarming concern worldwide, and especially in Italy, where there is no formal training of young researchers in responsible research practices. The main aim of this study was to map the perceptions and attitudes about RM in a sample of young researchers attending a one-week intensive course on methodology, ethics and integrity in biomedical research, held at the University of Insubria. To this end, we administered the Scientific Misconduct Questionnaire to all attendees at the beginning of the (...) course. Thereafter, SMQ-R was re-administered at the end, to assess the impact of the course on the responsiveness of study participants, which is intended as the frequency of responses other than “don’t know”. Results show that respondents rate as high their own understanding about rules and procedures related to scientific misconduct, as well as the effectiveness of their institution’s measures for reducing it. Most of them perceive as low the chances of getting caught for RM. Some respondents believe that cases of misconduct occur in their workplace and that the integrity of a research is not solely the responsibility of the principal investigator. Among the main factors contributing to research misconduct, the need for publications, unclear definition of what constitutes misconduct and pressure for external funding do stand out. Respondents are concerned about the amount of misconduct and express a pressing need for training on research ethics. Remarkably, the responsiveness of participants tends to increase with course attendance. This finding may be useful to support education programmes devoted to research methodology, ethics and integrity among young researchers. (shrink)

We examine the criticisms and subsequent changes that arise in the course of peer review. Fifty-two scholars who had recently published in Administrative Science Quarterly were surveyed regarding their peer review experience and how their article changed from initial journal submission to eventual publication. Papers that challenged theoretical perspectives faced distinctively high levels of criticism and change, particularly with attention to methodology, while those that offered a new perspective or that extended or combined established perspectives were less criticized and changed. (...) The number of challenge-oriented publications was small as well, suggesting that either few such submissions survive the review process or few are submitted in the first place. Overall, peer review appears open to expansion of the variety of theoretical argument but does little to aid in the winnowing out of established perspectives. (shrink)

It has long been known that scientists have a tendency to conduct experiments in a way that brings about the expected outcome. Here, we provide the first direct demonstration of this type of experimenter bias in experimental philosophy. Opposed to previously discovered types of experimenter bias mediated by face-to-face interactions between experimenters and participants, here we show that experimenters also have a tendency to create stimuli in a way that brings about expected outcomes. We randomly assigned undergraduate experimenters to receive (...) two different hypotheses about folk intuitions of consciousness, and then asked them to design experiments based on their hypothesis. Specifically, experimenters generated sentences ascribing intentional and phenomenal mental states to groups, which were later rated by online participants for naturalness. We found a significant interaction between experimenter hypothesis and participant ratings indicating a general tendency for experimenters to obtain the result that they expected. These results indicate that experimenter bias is a real problem in experimental philosophy since the methods and design employed here mirror the predominant survey methods of the field as a whole. The bearing of the current results on Knobe and Prinz’s :67–83, 2008) group mind hypothesis is discussed, and new methods for avoiding experimenter bias are proposed. (shrink)

This special issue on what some regard as a crisis of replicability in cognitive science (i.e. the observation that a worryingly large proportion of experimental results across a number of areas cannot be reliably replicated) is informed by three recent developments. -/- First, philosophers of mind and cognitive science rely increasingly on empirical research, mainly in the psychological sciences, to back up their claims. This trend has been noticeable since the 1960s (see Knobe, 2015). This development has allowed philosophers to (...) draw on a wider range of relevant resources, but it also makes them vulnerable to relying on claims that may not survive further scrutiny. If we have reasons to believe that a large proportion of findings in the psychological sciences cannot be reliably replicated, this would be a problem for philosophers who use such findings in their work. Second, philosophers are increasingly designing and carrying out their own experiments to back up claims, or to test claims earlier made from the armchair, for example, on the perceived permissibility of diverting trolleys or on the nature of free will. This growing field of experimental philosophy has diversified the intellectual field in philosophy, but may also be vulnerable to issues of replicability that philosophers did not face before. -/- Third, the recent evidence of apparently widespread non-replicability in the social sciences (and other fields) has forced philosophers of science to grapple with long standing questions from their field from a new perspective. To what extent does replicability matter for theory construction? How do the notions of replicability and scientific progress interact? How can normative insights from philosophy of science be used in order to improve scientific practice? -/- It is with these three developments in mind—the increasing importance of empirically-informed philosophy, of experimental philosophy, and of philosophy of science around replicability—that this special issue has been conceived. (shrink)

Media attention to retracted research suggests that a substantial number of papers are corrupted by misinformation. In reality, every paper contains misinformation; at issue is whether the balance of correct versus incorrect information is acceptable. This paper postulates that analysis of retracted research papers can provide insight into medical misinformation, although retracted papers are not a random sample of incorrect papers. Error is the most common reason for retraction and error may be the principal cause of misinformation as well. Still, (...) one-quarter of retracted papers are fraudulent, and misinformation may also arise through fraud. This paper hypothesises that error and fraud are the main sources of misinformation and that error is more common than fraud. Retraction removes misinformation from the literature; bias is non-retracted misinformation. Bias arises when scientific impropriety results in false research findings. Impropriety can involve experimental design, data collection, data analysis, or data presentation. Yet impropriety also arises through earnest error or statistical naiveté; not all bias is fraud. Several measures are proposed to minimise misinformation in the medical literature, including: greater detail in the clinical trial registry, with rigorous definition of inclusion and exclusion criteria and primary endpoints; clear statistical criteria for every aspect of clinical trials, especially sample size; responsibility for data integrity that accrues to all named authors; increased transparency as to how the costs of research were paid; and greater clarity as to the reasons for retraction. Misinformation can arise without malicious intent; authors of incorrect papers are owed a presumption of incompetence, not malice. (shrink)

Evidence hierarchies are widely used to assess evidence in systematic reviews of medical studies. I give several arguments against the use of evidence hierarchies. The problems with evidence hierarchies are numerous, and include methodological shortcomings, philosophical problems, and formal constraints. I argue that medical science should not employ evidence hierarchies, including even the latest and most-sophisticated of such hierarchies.

Subjective Bayesianism is a major school of uncertain reasoning and statistical inference. It is often criticized for a lack of objectivity: it opens the door to the influence of values and biases, evidence judgments can vary substantially between scientists, it is not suited for informing policy decisions. My paper rebuts these concerns by connecting the debates on scientific objectivity and statistical method. First, I show that the above concerns arise equally for standard frequentist inference with null hypothesis significance tests. Second, (...) the criticisms are based on specific senses of objectivity with unclear epistemic value. Third, I show that Subjective Bayesianism promotes other, epistemically relevant senses of scientific objectivity—most notably by increasing the transparency of scientific reasoning. (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)

Plagiarism by college and university faculty members has become a growing issue and concern in academia. This paper presents a case study of an extreme and clear case of such plagiarism. Yet an analysis of the legal and ethical contexts of such plagiarism, and the specific chronicle of this case, illustrate the complexities and difficulties in dealing with such situations. Implications for researchers, for colleges and universities, and for academic publishers and journals are offered.

The cross-cultural differences in epistemic intuitions reported by Weinberg, Nichols and Stich (2001; hereafter: WNS) laid the ground for the negative program of experimental philosophy. However, most of WNS’s findings were not corroborated in further studies. The exception here is the study concerning purported differences between Westerners and Indians in knowledge ascriptions concerning the Zebra Case, which was never properly replicated. Our study replicates the above-mentioned experiment on a considerably larger sample of Westerners (n = 211) and Indians (n = (...) 204). The analysis found a significant difference between the ethnic groups in question in the predicted direction: Indians were more likely to attribute knowledge in the Zebra Case than Westerners. In this paper, we offer an explanation of our result that takes into account the fact that replications of WNS’s other experiments did not find any cross-cultural differences. We argue that the Zebra Case is unique among the vignettes tested by WNS since it should not be regarded as a Gettier case but rather as a scenario exhibiting skeptical pressure concerning the reliability of sense-perception. We argue that skepticism towards perception as a means of gaining knowledge is a trope that is deeply rooted in Western epistemology but is very much absent from Classical Indian philosophical inquiry. This line of reasoning is based on a thorough examination of the skeptical scenarios discussed by philosophers of the Indian Nyaya tradition and their adversaries. (shrink)

Recent work has demonstrated that academic research faces serious challenges. Incentives to defend publishable ideas often lead researchers astray. Despite their tendency to produce error, efforts to publish erroneous results typically help a researcher's career. In addition, errors often arise from seemingly innocent methodological assumptions that allow researchers to believe their research is sound. This article discusses this research, as well as research into difficulties facing epistemic rationality caused by nonepistemic incentives. It then applies the lessons of this research to (...) philosophical practice. It explains why philosophy likely suffers from these problems. It then provides an example of a widely shared methodological assumption that allows such research to be pursued and regularly published. It claims that the significance philosophers place on arguments is inappropriate, and that typical evaluations of philosophical arguments involve an instance of the base-rate fallacy. It concludes by discussing whether or not this article is self-defeating. (shrink)

The results of forensic science are believed to be reliable, and are widely used in support of verdicts around the world. However, due to the lack of suitable empirical studies, we actually know very little about the reliability of such results. In this paper, I argue that phenomena analogous to the main culprits for the replication crisis in psychology are also present in forensic science. Therefore forensic results are significantly less reliable than is commonly believed. I conclude that in order (...) to obtain reliable estimates for the reliability of forensic results, we need to conduct studies analogous to the large-scale replication projects in psychology. Additionally, I point to some ways for improving the reliability of forensic science, inspired by the reforms proposed in response to the replicability crisis. (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)

Historical inductions, that is, the pessimistic metainduction and the problem of unconceived alternatives, are critically analyzed via John D. Norton’s material theory of induction and subsequently rejected as noncogent arguments. It is suggested that the material theory is amenable to a local version of the pessimistic metainduction, for example, in the context of some medical studies.

Previous research indicates that Euro-American women are more upset by imagining their male partners committing homosexual infidelities than heterosexual ones. The present studies sought to replicate these findings and extend them to two non-Western cultures wherein masculine men frequently engage in sexual interactions with feminine third-gender males. Across six studies in three cultural locales, women were asked to rate their degree of upset when imagining that their partner committed infidelity that was heterosexual in nature, as well as infidelity that was (...) homosexual. In two Canadian undergraduate samples, women reported greater upset at imagining partner infidelity with a female, whereas a community sample of middle-aged women reported equal upset across infidelity types. Samoan women reported substantially less upset at the thought of partner infidelity with a third-gender male than with a female. Istmo Zapotec women reported equal upset toward infidelity with a female or a third-gender male, whereas a second Zapotec sample reported slightly greater upset at the thought of infidelity with a muxe. Results illustrate how cultural contexts moderate the degree to which same-sex infidelity scenarios are upsetting to women. (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)

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)

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.

The study of human behavior is severely hampered by logistical problems, ethical and legal constraints, and funding shortfalls. However, the biggest difficulty of conducting social and behavioral research is the extraordinary complexity of the study phenomena. In this article, we review the impact of complexity on research design, hypothesis testing, measurement, data analyses, reproducibility, and the communication of findings in psychological science. The systematic investigation of the world often requires different approaches because of the variability in complexity. Confirmatory testing, multi-factorial (...) designs, survey methods, large samples, and modeling are frequently needed to study complex social and behavioral topics. Complexity impedes the measurement of general constructs, the reproducibility of results and scientific reporting, and the general rigor of research. Many of the benchmarks established by classic work in physical science are not attainable in studies of more complex phenomena. Consequently, the standards used to evaluate scientific research should be tethered to the complexity of the study topic. (shrink)

A science war is in full swing which has taken science's reproducibility crisis as a battleground. While conservatives and corporate interests use the crisis to weaken regulations, their opponent deny the existence of a science's crisis altogether. Thus, for the conservative National Association of Scholars NAS the crisis is real and due to the progressive assault on higher education with ideologies such as neo-Marxism, radical feminism, historicism, post-colonialism, deconstructionism, post-modernism, liberation theology. In the opposite field, some commentators claim that there (...) is no crisis in science and that saying the opposite is irresponsible. These positions are to be seen in the context of the ongoing battle against regulation, of which the new rules proposed at the US Environmental Protection Agency are but the last chapter. In this optic, Naomi Oreskes writes on Nature that what constitutes the crisis is the conservatives' attack on science. This evident right-left divide in the reading of the crisis is unhelpful and dangerous to the survival of science itself. An alternative reading ignored by the contendents would suggest that structural contradictions have emerged in modern science, and that addressing these should be the focus of our attention. (shrink)

Current Perspectives in Philosophy of Biology.

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)

Critical Data Studies explore the unique cultural, ethical, and critical challenges posed by Big Data. Rather than treat Big Data as only scientifically empirical and therefore largely neutral phenomena, CDS advocates the view that Big Data should be seen as always-already constituted within wider data assemblages. Assemblages is a concept that helps capture the multitude of ways that already-composed data structures inflect and interact with society, its organization and functioning, and the resulting impact on individuals’ daily lives. CDS questions the (...) many assumptions about Big Data that permeate contemporary literature on information and society by locating instances where Big Data may be naively taken to denote objective and transparent informational entities. In this introduction to the Big Data & Society CDS special theme, we briefly describe CDS work, its orientations, and principles. (shrink)

Kyle Stanford claims we have historical evidence that there likely are plausible unconceived alternatives in fundamental domains of science, and thus evidence that our best theories in these domains are probably false. Accordingly, we should adopt a form of instrumentalism. Elsewhere, I have argued that in fact we do not have historical evidence for the existence of plausible unconceived alternatives in particular domains of science, and that the main challenge to scientific realism is rather to provide evidence that there are (...) likely not plausible unconceived alternatives. In the present paper, I contend that we may come to have such evidence in the long run of science. I then investigate the epistemic consequences of the claim that we presently do not have evidence for or against the existence of plausible unconceived alternatives, but that in the future we may come to have evidence against the existence of plausible unconceived alternatives. I argue there are prima facie reasons to endorse a form of voluntarism in this situation according to which scientists and others may rationally be more optimistic or more pessimistic about the truth of our best theories, on the grounds that the widespread acceptance of an obligation to be an instrumentalist threatens to disrupt the proper functioning of science, in part because the domain of application of the problem of unconceived alternatives is unclear. (shrink)

The global pessimistic meta-induction argues from the falsity of scientific theories accepted in the past to the likely falsity of currently accepted scientific theories. I contend that this argument commits a statistical error previously unmentioned in the literature and is self-undermining. I then compare the global pessimistic meta-induction to a local pessimistic meta-induction based on recent negative assessments of the reliability of medical research. If there is any future in drawing pessimistic conclusions from the history of science, it lies in (...) local meta-inductions, but these meta-inductions will not result in global distrust of the results of science. (shrink)

Researchers increasingly rely on large data sets of health information, often linked with biological specimens. In recent years, the argument has been made that obtaining informed consent for conducting records-based research is unduly burdensome and results in ?consent bias.? As a type of selection bias, consent bias is said to exist when the group giving researchers access to their data differs from the group denying access. Therefore, to promote socially beneficial research, it is argued that consent should be unnecessary. After (...) analyzing the biostatistics evidence and bioethics arguments, the article concludes that (1) claims about the amount of consent bias are overstated; (2) commonly used statistical methods usually can account for consent bias; and (3) any residual effects of consent bias are below an acceptable level of imprecision and constitute a reasonable social cost for conducting ethically responsible research. (shrink)