[Purposes] This paper aims to summarize the research outcome on publishing ethics of scientific journals abroad, which is expected to serve as a reference for the research on related topics in China. [Methods] Literature review method and content coding method were adopted to systematically sum up related research abroad. Then, the status quo and development trend were analyzed. [Findings] There are five main research topics: anomy of publishing ethics, elements of publishing ethics norms, status quo of publishing ethics (...) implementation, knowledge of authors and editors on publishing ethics and their attitudes, and management of publishing ethics. [Conclusions] Foreign research on publishing ethics of scientific journals has achieved fruitful results with obvious characteristics, but there is a lack of research scope definition and systematic analysis of ethical norms. Chinese scientific journals should take international research outcome as a reference and strengthen the research on ethical norms to enhance the development of publishing ethics. (shrink)

Dear Editors, -/- I found the content of your editorials to be highly intriguing [1,2]. Scientific journals are witnessing a growing prevalence of publications related to artificial intelligence (AI). Three letters to the editor were recently published in your journal [3-5]. The renowned journal Nature has dedicated approximately 25 publications solely to the subject of ChatGPT. Moreover, a quick search on Pubmed using the term "ChatGPT" yields around 900 articles, with the vast majority originating in 2023. These statistics (...) underscore the substantial interest of the scientific community in this area. -/- AI, especially the ChatGPT tool and the recent Bard, have faced criticism and been portrayed as significant adversaries of science. It is evident that many authors or researchers, who may not be well-versed in writing, can greatly benefit from these tools, as mentioned earlier. Without taking a contrarian stance, one should consider the potential advantages of such technologies for researchers in less privileged regions, where access to new technologies is limited, and local or regional challenges abound [6]. AI cannot be confounded with other technologies, as it specifically focuses on replicating human-like intelligence and decision-making processes, rather than simply automating tasks or improving performance based on data patterns. -/- The translation into English poses challenges due to the dominance of English in worldwide publications, with over 95% of articles being published in this language, and even reaching 98% in some fields. Although this manuscript was partially translated using AI, it can still benefit researchers from non-native English regions. Even simple tasks like text editing can be problematic for researchers in underprivileged areas. AI can play a crucial role in the evolution of online lectures and classes, providing valuable support for African maxillofacial surgeons who lack the luxury of taking breaks from work to update their knowledge, as they may be the only available option [7]. One of the remarkable features of AI is its ability to discover knowledge gaps. The use of simple tools like reference organizers is rapidly evolving and can become automated or semi-automated through AI. However, we must carefully consider whether we should refrain from relying too heavily on AI in certain cases, as this could be seen as a significant regression. -/- On the other hand, we must be cautious about freely allowing AI tools to circulate in scientific journals and books without proper regulation [8]. Currently, accurately identifying texts generated by AI is challenging, and their effectiveness remains relatively low, at less than 30%. This means that only about 30 out of every 100 texts can be confidently classified as AI-generated. The technology must advance further to increase detection accuracy or at least raise suspicion. Academic journals no longer view authors acknowledging artificial intelligence tools as co-authors in their research favorably. This is crucial to prevent certain unscrupulous individuals, such as "false prophets," charlatans, and flat-earthers, from infiltrating the realm of science, potentially impeding the progress of serious research conducted by professionals dedicated to advancing humanity through science. -/- It is essential to keep in mind that AI does not generate anything novel. Human authors can not be fully substituted [9]. In research involving groundbreaking concepts, innovations, case reports, or technical notes, the use of AI tends to be less frequent due to its lack of capability in creating innovative outcomes. On the other hand, reviews, whether narrative, systematic, or scoping, are based on existing publications. To address potential fraudulent practices, editors, reviewers, and journals themselves should exercise greater vigilance and apply more stringent filters for this type of publication. -/- An article from over a decade ago already discussed the professions most susceptible to replacement by computerization [10]. Maxillofacial surgeons, physicians, dentists, and psychologists are among the professions that are less likely to be displaced. This position can be attributed to the significant level of patient-professional interaction, the development of specific manual skills over time, and the ability to make adaptable decisions during procedures. These intricacies pose formidable challenges for AI to grasp, regardless of its level of advancement. -/- We should maintain a composed yet vigilant stance at this juncture. Just as Portuguese navigators feared encountering serpents and sea monsters when they ventured into uncharted waters, the uncertainty and novelty of AI can evoke apprehension in us all. Nonetheless, we must embrace the benefits that AI can offer while imposing strict regulations and appropriate penalties to prevent any potential abuses carried out "in the name of science." -/- Sincerely yours,. (shrink)

Scientific realism driven by inference to the best explanation (IBE) takes empirically confirmed objects to exist, independent, pace empiricism, of whether those objects are observable or not. This kind of realism, it has been claimed, does not need probabilistic reasoning to justify the claim that these objects exist. But I show that there are scientific contexts in which a non-probabilistic IBE-driven realism leads to a puzzle. Since IBE can be applied in scientific contexts in which empirical confirmation (...) has not yet been reached, realists will in these contexts be committed to the existence of empirically unconfirmed objects. As a consequence of such commitments, because they lack probabilistic features, the possible empirical confirmation of those objects is epistemically redundant with respect to realism. (shrink)

What is scientific progress? This paper advances an interpretation of this question, and an account that serves to answer it. Roughly, the question is here understood to concern what type of cognitive change with respect to a topic X constitutes a scientific improvement with respect to X. The answer explored in the paper is that the requisite type of cognitive change occurs when scientific results are made publicly available so as to make it possible for anyone to (...) increase their understanding of X. This account is briefly compared to two rival accounts of scientific progress, based respectively on increasing truthlikeness and accumulating knowledge, and is argued to be preferable to both. (shrink)

Bird argues that scientific progress consists in increasing knowledge. Dellsén objects that increasing knowledge is neither necessary nor sufficient for scientific progress, and argues that scientific progress rather consists in increasing understanding. Dellsén also contends that unlike Bird’s view, his view can account for the scientific practices of using idealizations and of choosing simple theories over complex ones. I argue that Dellsén’s criticisms against Bird’s view fail, and that increasing understanding cannot account for scientific progress, (...) if acceptance, as opposed to belief, is required for scientific understanding. (shrink)

Scientists are constantly making observations, carrying out experiments, and analyzing empirical data. Meanwhile, scientific theories are routinely being adopted, revised, discarded, and replaced. But when are such changes to the content of science improvements on what came before? This is the question of scientific progress. One answer is that progress occurs when scientific theories ‘get closer to the truth’, i.e. increase their degree of truthlikeness. A second answer is that progress consists in increasing theories’ effectiveness for solving (...) scientific problems. A third answer is that progress occurs when the stock of scientific knowledge accumulates. A fourth and final answer is that scientific progress consists in increasing scientific understanding, i.e. the capacity to correctly explain and reliably predict relevant phenomena. This paper compares and contrasts these four accounts of scientific progress, considers some of the most prominent arguments for and against each account, and briefly explores connections to different forms of scientific realism. (shrink)

First, I argue that scientific progress is possible in the absence of increasing verisimilitude in science’s theories. Second, I argue that increasing theoretical verisimilitude is not the central, or primary, dimension of scientific progress. Third, I defend my previous argument that unjustified changes in scientific belief may be progressive. Fourth, I illustrate how false beliefs can promote scientific progress in ways that cannot be explicated by appeal to verisimilitude.

We report the results of a study that investigated the views of researchers working in seven scientific disciplines and in history and philosophy of science in regard to four hypothesized dimensions of scientific realism. Among other things, we found that natural scientists tended to express more strongly realist views than social scientists, that history and philosophy of science scholars tended to express more antirealist views than natural scientists, that van Fraassen’s characterization of scientific realism failed to cluster (...) with more standard characterizations, and that those who endorsed the pessimistic induction were no more or less likely to endorse antirealism. (shrink)

Imagination is necessary for scientific practice, yet there are no in vivo sociological studies on the ways that imagination is taught, thought of, or evaluated by scientists. This article begins to remedy this by presenting the results of a qualitative study performed on two systems biology laboratories. I found that the more advanced a participant was in their scientific career, the more they valued imagination. Further, positive attitudes toward imagination were primarily due to the perceived role of imagination (...) in problem-solving. But not all problem-solving episodes involved clear appeals to imagination, only maximally specific problems did. This pattern is explained by the presence of an implicit norm governing imagination use in the two labs: only use imagination on maximally specific problems, and only when all other available methods have failed. This norm was confirmed by the participants, and I argue that it has epistemological reasons in its favour. I also found that its strength varies inversely with career stage, such that more advanced scientists do (and should) occasionally bring their imaginations to bear on more general problems. A story about scientific pedagogy explains the trend away from (and back to) imagination over the course of a scientific career. Finally, some positive recommendations are given for a more imagination-friendly scientific pedagogy. (shrink)

A prominent type of scientific realism holds that some important parts of our best current scientific theories are at least approximately true. According to such realists, radically distinct alternatives to these theories or theory-parts are unlikely to be approximately true. Thus one might be tempted to argue, as the prominent anti-realist Kyle Stanford recently did, that realists of this kind have little or no reason to encourage scientists to attempt to identify and develop theoretical alternatives that are radically (...) distinct from currently accepted theories in the relevant respects. In other words, it may seem that realists should recommend that scientists be relatively conservative in their theoretical endeavors. This paper aims to show that this argument is mistaken. While realists should indeed be less optimistic of finding radically distinct alternatives to replace current theories, realists also have greater reasons to value the outcomes of such searches. Interestingly, this holds both for successful and failed attempts to identify and develop such alternatives. (shrink)

We model scientific theories as Bayesian networks. Nodes carry credences and function as abstract representations of propositions within the structure. Directed links carry conditional probabilities and represent connections between those propositions. Updating is Bayesian across the network as a whole. The impact of evidence at one point within a scientific theory can have a very different impact on the network than does evidence of the same strength at a different point. A Bayesian model allows us to envisage and (...) analyze the differential impact of evidence and credence change at different points within a single network and across different theoretical structures. (shrink)

Epistemic accounts of scientific collaboration usually assume that, one way or another, two heads really are more than twice better than one. We show that this hypothesis is unduly strong. We present a deliberately crude model with unfavorable hypotheses. We show that, even then, when the priority rule is applied, large differences in successfulness can emerge from small differences in efficiency, with sometimes increasing marginal returns. We emphasize that success is sensitive to the structure of competing communities. Our results (...) suggest that purely epistemic explanations of the efficiency of collaborations are less plausible but have much more powerful socioepistemic versions. (shrink)

Extensional scientific realism is the view that each believable scientific theory is supported by the unique first-order evidence for it and that if we want to believe that it is true, we should rely on its unique first-order evidence. In contrast, intensional scientific realism is the view that all believable scientific theories have a common feature and that we should rely on it to determine whether a theory is believable or not. Fitzpatrick argues that extensional realism (...) is immune, while intensional realism is not, to the pessimistic induction. I reply that if extensional realism overcomes the pessimistic induction at all, that is because it implicitly relies on the theoretical resource of intensional realism. I also argue that extensional realism, by nature, cannot embed a criterion for distinguishing between believable and unbelievable theories. (shrink)

ABSTRACTThis discussion note aims to contribute to the ongoing debate over the nature of scientific progress. I argue against the semantic view of scientific progress, according to which scientific progress consists in approximation to truth or increasing verisimilitude. If the semantic view of scientific progress were correct, then scientists would make scientific progress simply by arbitrarily adding true disjuncts to their hypotheses or theories. Given that it is not the case that scientists could make (...) class='Hi'>scientific progress simply by arbitrarily adding true disjuncts to their hypotheses or theories, it follows that the semantic view of scientific progress is incorrect. (shrink)

Stegenga (forthcoming) formulates and defends a novel account of scientific progress, according to which science makes progress just in case there is a change in scientific justification. Here we present several problems for Stegenga’s account, concerning respectively (i) obtaining misleading evidence, (ii) losses or destruction of evidence, (iii) oscillations in scientific justification, and (iv) the possibility of scientific regress. We conclude by sketching a substantially different justification-based account of scientific progress that avoids these problems.

What is scientific progress? On Alexander Bird’s epistemic account of scientific progress, an episode in science is progressive precisely when there is more scientific knowledge at the end of the episode than at the beginning. Using Bird’s epistemic account as a foil, this paper develops an alternative understanding-based account on which an episode in science is progressive precisely when scientists grasp how to correctly explain or predict more aspects of the world at the end of the episode (...) than at the beginning. This account is shown to be superior to the epistemic account by examining cases in which knowledge and understanding come apart. In these cases, it is argued that scientific progress matches increases in scientific understanding rather than accumulations of knowledge. In addition, considerations having to do with minimalist idealizations, pragmatic virtues, and epistemic value all favor this understanding-based account over its epistemic counterpart. (shrink)

Scientific realists believe both what a scientific theory says about observables and unobservables. In contrast, scientific antirealists believe what a scientific theory says about observables, but not about unobservables. I argue that scientific realism is a more useful doctrine than scientific antirealism in science classrooms. If science teachers are antirealists, they are caught in Moore’s paradox when they help their students grasp the content of a scientific theory, and when they explain a phenomenon (...) in terms of a scientific theory. Teachers ask questions to their students to check whether they have grasped the content of a scientific theory. If the students are antirealists, they are also caught in Moore’s paradox when they respond positively to their teachers’ questions, and when they explain a phenomenon in terms of a scientific theory. Finally, neither teachers nor students can understand phenomena in terms of scientific theories, if they are antirealists. (shrink)

When science makes cognitive progress, who or what is it that improves in the requisite way? According to a widespread and unchallenged assumption, it is the cognitive attitudes of scientists themselves, i.e. the agents by whom scientific progress is made, that improve during progressive episodes. This paper argues against this assumption and explores a different approach. Scientific progress should be defined in terms of potential improvements to the cognitive attitudes of those for whom progress is made, i.e. the (...) receivers rather than the producers of scientific information. This includes not only scientists themselves, but also various other individuals who utilize scientific information in different ways for the benefit of society as a whole. (shrink)

Natural kinds, real kinds, or, following J.S Mill simply, Kinds, are thought to be an important asset for scientific realists in the non-fundamental (or “special”) sciences. Essential natures are less in vogue. I show that the realist would do well to couple her Kinds with essential natures in order to strengthen their epistemic and ontological credentials. I argue that these essential natures need not however be intrinsic to the Kind’s members; they may be historical. I concentrate on assessing the (...) merits of historical essential natures in a paradigm case of Kinds in the non-fundamental sciences: species. I specify two basic jobs for essential natures: 1) offering individuation criteria, and 2) providing a causal explanation of the Kind’s multiple projectable properties. I argue that at least in the case of species historical essences are fit for both tasks. The principled resistance to Kinds with historical essences should also be cleared. (shrink)

This paper considers the relationship between science and common sense. It takes as its point of departure, Eddington’s distinction between the table of physics and the table of common sense, as well as Eddington’s suggestion that science shows common sense to be false. Against the suggestion that science shows common sense to be false, it is argued that there is a form of common sense, basic common sense, which is not typically overthrown by scientific research. Such basic common sense (...) is strongly confirmed by our everyday experience and may itself serve as the basic for scientific realism. (shrink)

I defend a novel account of scientific progress centred around justification. Science progresses, on this account, where there is a change in justification. I consider three options for explicating this notion of change in justification. This account of scientific progress dispels with a condition for scientific progress that requires accumulation of truth or truthlikeness, and it emphasises the social nature of scientific justification.

This paper reconsiders the challenge presented to scientific realism by the semantic incommensurability thesis. A twofold distinction is drawn between methodological and semantic incommensurability, and between semantic incommensurability due to variation of sense and due to discontinuity of reference. Only the latter presents a challenge to scientific realism. The realist may dispose of this challenge on the basis of a modified causal theory of reference, as argued in the author’s 1994 book, The incommensurability thesis. This referential response has (...) been the subject of a charge of meta-incommensurability by Hoyningen-Huene et al., who argue that the realist’s referential response begs the question against anti-realist advocates of incommensurability. In reply, it is noted that a tu quoque rejoinder is available to the realist. It is also argued that the dialectical situation favours the scientific realist, since the anti-realist defence of incommensurability depends on an incoherent distinction between phenomenal world and world-in-itself. In light of such incoherence, and a strong commonsense presumption in favour of realism, the referential response to semantic incommensurability may be justifiably based on realism. (shrink)

In his late years, Thomas Kuhn became interested in the process of scientific specialization, which does not seem to possess the destructive element that is characteristic of scientific revolutions. It therefore makes sense to investigate whether and how Kuhn’s insights about specialization are consistent with, and actually fit, his model of scientific progress through revolutions. In this paper, I argue that the transition toward a new specialty corresponds to a revolutionary change for the group of scientists involved (...) in such a transition. I will clarify the role of the scientific community in revolutionary changes and characterize the incommensurability across specialties as possessing both semantic and methodological aspects. The discussion of the discovery of the structure of DNA will serve both as an illustration of my main argument and as reply to one criticism raised against Kuhn—namely, that his model cannot capture cases of revolutionary yet non-disruptive episodes of scientific progress. Revisiting Kuhn’s ideas on specialization will shed new light on some often overlooked features of scientific change. (shrink)

I assess Churchland's views on folk psychology and conceptual thinking, with particular emphasis on the connection between these topics.

In Kant, Science, and Human Nature, Robert Hanna argues against a version of scientific realism founded on the Kripke/Putnam theory of reference, and defends a Kant-inspired manifest realism in its place. I reject Kriple/Putnam for different reasons than Hanna does, and argue that what should replace it is not manifest realism, but Kant‘s own scientific realism, which rests on a radically different theory of reference. Kant holds that we picture manifest objects by uniting manifolds of sensation using concepts-qua-inferential-rules. (...) When these rules are demonstrated to be invalid, we replace the picture of the macroscopic world with a picture of the microscopic entities of theoretical science that unites the very same manifolds using different rules of inference. Thus, we refer to "unobservable" theoretical entities in the same way that we do manifest ones: by specifying both their determinate location in space and time and the concepts by which they are understood. (shrink)

The demarcation between science and non-science seems to play an important role in the process of scientific change, as theories regularly transition from being considered scientific to being considered unscientific and vice versa. However, theoretical scientonomy is yet to shed light on this process. The goal of this paper is to tackle the problem of demarcation from the scientonomic perspective. Specifically, we introduce scientificity as a distinct epistemic stance that an agent can take towards a theory. We contend (...) that changes in this stance are to be traced and explained by scientonomy. Thus, we formulate a new law of theory demarcation to account for changes in scientificity within the scientonomic framework. (shrink)

Scientific Realism (SR) has three crucial aspects: 1) the centrality of the concept of truth, 2) the idea that success is a reliable indicator of truth, and 3) the idea that the Inference to the Best Explanation is a reliable inference rule. It will be outlined how some realists try to overcome the difficulties which arise in justifying such crucial aspects relying on an adaptationist view of evolutionism, and why such attempts are inadequate. Finally, we will briefly sketch some (...) of the main difficulties the realist has to face in defending those crucial aspects, and how such difficulties are deeply related: they derive from the inability of SR to satisfyingly avoid the sceptical challenge of the criterion of truth. Indeed, SR seems not to be able to fill the so-called ‘epistemic gap’ (Sankey 2008). In fact, the epistemic gap cannot be filled in no way other than obtaining a criterion of truth, but such a criterion cannot be obtained if the epistemic gap obtains. (shrink)

A scientific community can be modeled as a collection of epistemic agents attempting to answer questions, in part by communicating about their hypotheses and results. We can treat the pathways of scientific communication as a network. When we do, it becomes clear that the interaction between the structure of the network and the nature of the question under investigation affects epistemic desiderata, including accuracy and speed to community consensus. Here we build on previous work, both our own and (...) others’, in order to get a firmer grasp on precisely which features of scientific communities interact with which features of scientific questions in order to influence epistemic outcomes. (shrink)

Scientific explanations must bear the proper relationship to the world: they must depict what, out in the world, is responsible for the explanandum. But explanations must also bear the proper relationship to their audience: they must be able to create human understanding. With few exceptions, philosophical accounts of explanation either ignore entirely the relationship between explanations and their audience or else demote this consideration to an ancillary role. In contrast, I argue that considering an explanation’s communicative role is crucial (...) to any satisfactory account of explanation. (shrink)

We argue that the main results of scientific papers may appropriately be published even if they are false, unjustified, and not believed to be true or justified by their author. To defend this claim we draw upon the literature studying the norms of assertion, and consider how they would apply if one attempted to hold claims made in scientific papers to their strictures, as assertions and discovery claims in scientific papers seem naturally analogous. We first use a (...) case study of William H. Bragg’s early 20th century work in physics to demonstrate that successful science has in fact violated these norms. We then argue that features of the social epistemic arrangement of science which are necessary for its long run success require that we do not hold claims of scientific results to their standards. We end by making a suggestion about the norms that it would be appropriate to hold scientific claims to, along with an explanation of why the social epistemology of science—considered as an instance of collective inquiry—would require such apparently lax norms for claims to be put forward. (shrink)

In this paper I wish to connect the recent debate in the philosophy of quantum mechanics concerning the nature of the wave function to the historical debate in the philosophy of science regarding the tenability of scientific realism. Being realist about quantum mechanics is particularly challenging when focusing on the wave function. According to the wave function ontology approach, the wave function is a concrete physical entity. In contrast, according to an alternative viewpoint, namely the primitive ontology approach, the (...) wave function does not represent physical entities. In this paper, I argue that the primitive ontology approach can naturally be interpreted as an instance of the so-called ‘explanationism’ realism, which has been proposed as a response to the pessimistic-meta induction argument against scientific realism. If my arguments are sound, then one could conclude that: (1) contrarily to what is commonly though, if explanationism realism is a good response to the pessimistic-meta induction argument, it can be straightforwardly extended also to the quantum domain; (2) the primitive ontology approach is in better shape than the wave function ontology approach in resisting the pessimistic-meta induction argument against scientific realism. (shrink)

We present the negative phenomena of understanding in relation to scientific explanations. We begin by formulating the distinction between genuine understanding and lack of understanding, to define the epistemic category of misunderstanding. We illustrate misunderstanding with a short meta-philosophical study on the current debates about distinctively mathematical explanations.

Scientific essentialism holds that: (1) each scientific kind is associated with the same set of properties in every possible world; and (2) every individual member of a scientific kind belongs to that kind in every possible world in which it exists. Recently, Ellis (Scientific essentialism, 2001 ; The philosophy of nature 2002 ) has provided the most sustained defense of scientific essentialism, though he does not clearly distinguish these two claims. In this paper, I argue (...) that both claims face a number of formidable difficulties. The necessities of scientific essentialism are not adequately distinguished from semantic necessities, they have not been shown to be necessities in the strictest sense, they must be relativized to context, and they must either be confined to a subset of scientific properties without warrant or their connection to causal powers must be revoked. Moreover, upon closer examination (1) turns out to be a trivial thesis that can be satisfied by non-kinds, and (2) is inapplicable to some of the most fundamental kinds in the basic sciences. (shrink)

In a recent paper, Barry Loewer attempts to defend Humeanism about laws of nature from a charge that Humean laws are not adequately explanatory. Central to his defense is a distinction between metaphysical and scientific explanations: even if Humeans cannot offer further metaphysical explanations of particular features of their “mosaic,” that does not preclude them from offering scientific explanations of these features. According to Marc Lange, however, Loewer’s distinction is of no avail. Defending a transitivity principle linking (...) class='Hi'>scientific explanantia to their metaphysical grounds, Lange argues that a charge of explanatory inadequacy resurfaces once this intuitive principle is in place. This paper surveys, on behalf of the Humean, three strategies for responding to Lange’s criticism. The ready availability of these strategies suggests that Lange’s argument may not bolster anti-Humean convictions, since the argument rests on premises that those not antecedently sharing these convictions may well reject. The three strategies also correspond to three interesting ways of thinking about relations of grounding linking Humean laws and their instances, all of which are consistent with theses of Humean supervenience, and some of which have been heretofore overlooked. (shrink)

Without doubt, there is a great diversity of scientific images both with regard to their appearances and their functions. Diagrams, photographs, drawings, etc. serve as evidence in publications, as eye-catchers in presentations, as surrogates for the research object in scientific reasoning. This fact has been highlighted by Stephen M. Downes who takes this diversity as a reason to argue against a unifying representation-based account of how visualisations play their epistemic role in science. In the following paper, I will (...) suggest an alternative explanation of the diversity of scientific images. This account refers to processes which are caused by the social setting of science. What exactly is meant by this, I will spell out with the aid of Ludwik Fleck’s theory of the social mechanisms of scientific communication. (shrink)

Background and Objectives: In this research article, the researcher addresses the issue of creating public understanding in a democratic society about the progress of science, with an emphasis on pluralism from philosophers of science. The idea that there is only one truth and that there are just natural laws awaiting discovery by scientists has historically made it difficult to explain scientific progress. This belief motivates science to develop theories that explain the unity of science, and it is thought that (...) diversity in the way different ideas presented by scientists is a problem that results in time being wasted in search of the most accurate theory. Some scientists perceive a benefit in having a range of scientific hypotheses, though. One benefit that is frequently cited is that scientific diversity as a whole contributes to the development of a democratic society that permits the expression of a range of viewpoints. The road to accountable scientific pluralism is fraught with difficulties, though. Therefore, it is crucial to take into account both pluralism's advantages and disadvantages. This research aims at: 1. analyzing in an epistemological way the interpretation of scientific theories and the progress of science from the perspectives of scientific pluralists; 2. analyzing the relationship between science and democracy in explaining scientific significance and progress; and 3. synthesizing new knowledge on epistemic dependentism and to argue that it plays a significant role in evaluating research issues related to scientific pluralism. Methodology: The research methodology involves the application of documentary investigation along with philosophical discourse. The method of philosophical argumentation involves analyzing the lines of arguments found in relevant academic publications in order to assess their validity and soundness. Main Results: One key argument of the pluralists is the use of the concept of theoretical pluralism, which suggests that scientific knowledge is created from a variety of perspectives according to the social and cultural context of knowledge creation. It is found that part of Longino's argument is based on the negation of rational/social dichotomy. Moreover, her theory is a departure from philosopher of science Philip Kitcher, who advocates the creation of scientific knowledge and the evaluation of scientific progress through the means of democratic society. He explains that these procedures will lead to "well-ordered science" in democratic society. Discussions: The researcher examines the underlying ideas accepted by these two philosophers of science and finds that although their opinions differ, they have common ground in the acceptance of consensus. However, the views of both philosophers still lack weight in explaining the knowledge itself. The researcher argues that the acceptance of pluralism as a way of understanding scientific progress necessarily lends itself to dependentism, which points to interdependence in comparisons of superiority/inferiority between scientific theories. It is undeniable that the situation has emerged all the time, even though the success of the scientific theories being compared to each other comes from different social and cultural grounds of thought. Conclusions: Some popular models of scientific pluralism in the philosophy of science still lack a compelling justification, particularly on the epistemic grounds. By elucidating the epistemic significance of the interdependence of these things, scientific pluralism can be strengthened by incorporating the notion of epistemic dependentism into the analysis of scientific progress. (shrink)

Review of T. Nickles (ed), Scientific Discovery: Case Studies.

Scientific disagreements are an important catalyst for scientific progress. But what happens when scientists disagree amidst times of crisis, when we need quick yet reliable policy guidance? In this paper we provide a normative account for how scientists facing disagreement in the context of ‘fast science’ should respond, and how policy makers should evaluate such disagreement. Starting from an argumentative, pragma-dialectic account of scientific controversies, we argue for the importance of ‘higher-order evidence’ (HOE) and we specify desiderata (...) for scientifically relevant HOE. We use our account to analyze the controversy about the aerosol transmission of COVID-19. (shrink)

A consensus in a scientific community is often used as a resource for making informed public-policy decisions and deciding between rival expert testimonies in legal trials. This paper contains a social-epistemic analysis of the high-profile Bendectin drug controversy, which was decided in the courtroom inter alia by deference to a scientific consensus about the safety of Bendectin. Drawing on my previously developed account of knowledge-based consensus, I argue that the consensus in this case was not knowledge based, hence (...) courts’ deference to it was not epistemically justified. I draw sceptical lessons from this analysis regarding the value of scientific consensus as a desirable and reliable means of resolving scientific controversies in public life. (shrink)

This thirteenth volume of Collected Papers is an eclectic tome of 88 papers in various fields of sciences, such as astronomy, biology, calculus, economics, education and administration, game theory, geometry, graph theory, information fusion, decision making, instantaneous physics, quantum physics, neutrosophic logic and set, non-Euclidean geometry, number theory, paradoxes, philosophy of science, scientific research methods, statistics, and others, structured in 17 chapters (Neutrosophic Theory and Applications; Neutrosophic Algebra; Fuzzy Soft Sets; Neutrosophic Sets; Hypersoft Sets; Neutrosophic Semigroups; Neutrosophic Graphs; Superhypergraphs; (...) Plithogeny; Information Fusion; Statistics; Decision Making; Extenics; Instantaneous Physics; Paradoxism; Mathematica; Miscellanea), comprising 965 pages, published between 2005-2022 in different scientific journals, by the author alone or in collaboration with the following 110 co-authors (alphabetically ordered) from 26 countries: Abduallah Gamal, Sania Afzal, Firoz Ahmad, Muhammad Akram, Sheriful Alam, Ali Hamza, Ali H. M. Al-Obaidi, Madeleine Al-Tahan, Assia Bakali, Atiqe Ur Rahman, Sukanto Bhattacharya, Bilal Hadjadji, Robert N. Boyd, Willem K.M. Brauers, Umit Cali, Youcef Chibani, Victor Christianto, Chunxin Bo, Shyamal Dalapati, Mario Dalcín, Arup Kumar Das, Elham Davneshvar, Bijan Davvaz, Irfan Deli, Muhammet Deveci, Mamouni Dhar, R. Dhavaseelan, Balasubramanian Elavarasan, Sara Farooq, Haipeng Wang, Ugur Halden, Le Hoang Son, Hongnian Yu, Qays Hatem Imran, Mayas Ismail, Saeid Jafari, Jun Ye, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Darjan Karabašević, Abdullah Kargın, Vasilios N. Katsikis, Nour Eldeen M. Khalifa, Madad Khan, M. Khoshnevisan, Tapan Kumar Roy, Pinaki Majumdar, Sreepurna Malakar, Masoud Ghods, Minghao Hu, Mingming Chen, Mohamed Abdel-Basset, Mohamed Talea, Mohammad Hamidi, Mohamed Loey, Mihnea Alexandru Moisescu, Muhammad Ihsan, Muhammad Saeed, Muhammad Shabir, Mumtaz Ali, Muzzamal Sitara, Nassim Abbas, Munazza Naz, Giorgio Nordo, Mani Parimala, Ion Pătrașcu, Gabrijela Popović, K. Porselvi, Surapati Pramanik, D. Preethi, Qiang Guo, Riad K. Al-Hamido, Zahra Rostami, Said Broumi, Saima Anis, Muzafer Saračević, Ganeshsree Selvachandran, Selvaraj Ganesan, Shammya Shananda Saha, Marayanagaraj Shanmugapriya, Songtao Shao, Sori Tjandrah Simbolon, Florentin Smarandache, Predrag S. Stanimirović, Dragiša Stanujkić, Raman Sundareswaran, Mehmet Șahin, Ovidiu-Ilie Șandru, Abdulkadir Șengür, Mohamed Talea, Ferhat Taș, Selçuk Topal, Alptekin Ulutaș, Ramalingam Udhayakumar, Yunita Umniyati, J. Vimala, Luige Vlădăreanu, Ştefan Vlăduţescu, Yaman Akbulut, Yanhui Guo, Yong Deng, You He, Young Bae Jun, Wangtao Yuan, Rong Xia, Xiaohong Zhang, Edmundas Kazimieras Zavadskas, Zayen Azzouz Omar, Xiaohong Zhang, Zhirou Ma.‬‬‬‬‬‬‬‬. (shrink)

Scientific antirealists run the argument from underconsideration against scientific realism. I argue that the argument from underconsideration backfires on antirealists’ positive philosophical theories, such as the contextual theory of explanation (van Fraassen, 1980), the English model of rationality (van Fraassen, 1989), the evolutionary explanation of the success of science (Wray, 2008; 2012), and explanatory idealism (Khalifa, 2013). Antirealists strengthen the argument from underconsideration with the pessimistic induction against current scientific theories. In response, I construct a pessimistic induction (...) against antirealists that since antirealists generated problematic philosophical theories in the past, they must be generating problematic philosophical theories now. (shrink)

In response to historical challenges, advocates of a sophisticated variant of scientific realism emphasize that theoretical systems can be divided into numerous constituents. Setting aside any epistemic commitment to the systems themselves, they maintain that we can justifiably believe those specific constituents that are deployed in key successful predictions. Stathis Psillos articulates an explicit criterion for discerning exactly which theoretical constituents qualify. I critique Psillos's criterion in detail. I then test the more general deployment realist intuition against a set (...) of well-known historical cases, whose significance has, I contend, been overlooked. I conclude that this sophisticated form of realism remains threatened by the historical argument that prompted it. A criterion for scientific realism Assessing the criterion A return to the crucial insight: responsibility A few case studies Assessing deployment realism. (shrink)

When does a model explain? When does it promote understanding? A dominant approach to scientific explanation is the interventionist view. According to this view, when X explains Y, intervening on X can produce, prevent or alter Y in some predictable way. In this paper, I argue for two claims. First, I reject a position that many interventionist theorists endorse. This position is that to explain some phenomenon by providing a model is also to understand that phenomenon. While endorsing the (...) interventionist view, I argue that explaining and understanding are distinct scientific achievements. Second, I defend a novel theory of scientific understanding. According to this view, when some model M promotes understanding, M makes available a distinctive mental state. This state is of the same psychological kind as when we grasp events in a narrative as bearing on some ultimate conclusion. To conclude, I show that, given this view, mechanistic explanations often provide a powerful source of understanding that many causal-historical models lack. This paper will be of interest to both philosophers of science and epistemologists engaged in the topics of explanation and understanding. (shrink)

In this article, I explore the compatibility of inference to the best explanation (IBE) with several influential models and accounts of scientific explanation. First, I explore the different conceptions of IBE and limit my discussion to two: the heuristic conception and the objective Bayesian conception. Next, I discuss five models of scientific explanation with regard to each model’s compatibility with IBE. I argue that Kitcher’s unificationist account supports IBE; Railton’s deductive–nomological–probabilistic model, Salmon’s statistical-relevance model, and van Fraassen’s erotetic (...) account are incompatible with IBE; and Salmon’s causal–mechanical model is merely consistent with IBE. In short, many influential models of scientific explanation do not support IBE. I end by outlining three possible conclusions to draw: (1) either philosophers of science or defenders of IBE have seriously misconstrued the concept of explanation, (2) philosophers of science and defenders of IBE do not use the term ‘explanation’ univocally, and (3) the ampliative conception of IBE, which is compatible with any model of scientific explanation, deserves a closer look. (shrink)

Theoretical models are widely held as sources of knowledge of reality. Imagination is vital to their development and to the generation of plausible hypotheses about reality. But how can imagination, which is typically held to be completely free, effectively instruct us about reality? In this paper I argue that the key to answering this question is in constrained uses of imagination. More specifically, I identify make-believe as the right notion of imagination at work in modelling. I propose the first overarching (...) taxonomy of types of constraints on scientific imagination that enables knowledge of reality. And I identify two main kinds of knowledge enabled by models, knowledge of the imaginary scenario specified by models and knowledge of reality. (shrink)

Dellsén (2017) has recently argued for an understanding-based account of scientific progress, the noetic account, according to which science (or a particular scientific discipline) makes cognitive progress precisely when it increases our understanding of some aspect of the world. Dellsén contrasts this account with Bird’s (2007, 2015) epistemic account, according to which such progress is made precisely when our knowledge of the world is increased or accumulated. In a recent paper, Park (2017) criticizes various aspects of Dellsén’s account (...) and his arguments in favor of the noetic account as against Bird’s epistemic account. This paper responds to Park’s objections. Since a number of Park’s arguments rely on the idea that scientific progress may merely consists in “achieving the means to increase knowledge” (Park 2017: 570), I will start by discussing this “means-end thesis”. (shrink)

First, I answer the controversial question ’What is scientific realism?’ with extensive reference to the varied accounts of the position in the literature. Second, I provide an overview of the key developments in the debate concerning scientific realism over the past decade. Third, I provide a summary of the other contributions to this special issue.

The aim of this paper is to show that global scientific promises aka “scientific world-conceptions” have an interesting history that should be taken into account also for contemporary debates. I argue that the prototypes of many contemporary philosophical positions concerning the role of science in society can already be found in the philosophy of science of the 1920s and 1930s. First to be mentioned in this respect is the Scientific World-Conception of the Vienna Circle (The Manifesto) that (...) promised to contribute to the realization of an enlightened, rational and science-oriented society and culture. The Manifesto was not the only „scientific world-conception“ that philosophers and scientists put forward in the 1920s. Also the scientific world-conception of the philosopher and physicist Moritz Schlick, and the Weltanschauung of Sigmund Freud deserve to be mentioned. Still other examples of are Carnap’s Scientific Humanism and the project of The International Encyclopedia of Unified Science which was related to American pragmatism as well, as is shown by Charles W. Morris and others. Forgotten for a long time, since the beginning of the 21rst century, at least some of the Viennese projects are reconsidered in a new wave of „socially engaged philosophy of science”. (shrink)

If scientists embrace scientific realism, they can use a scientific theory to explain and predict observables and unobservables. If, however, they embrace scientific antirealism, they cannot use a scientific theory to explain observables and unobservables, and cannot use a scientific theory to predict unobservables. Given that explanation and prediction are means to make scientific progress, scientists can make more scientific progress, if they embrace scientific realism than if they embrace scientific antirealism.

Ground is all the rage in contemporary metaphysics. But what is its nature? Some metaphysicians defend what we could call, following Skiles and Trogdon (2021), the inheritance view: it is because constitutive forms of metaphysical explanation are such-and-such that we should believe that ground is so-and-so. However, many putative instances of inheritance are not primarily motivated by scientific considerations. This limitation is harmless if one thinks that ground and science are best kept apart. Contrary to this view, we believe (...) that ground is a highly serviceable tool for investigating metaphysical areas of science. In this paper, we defend a naturalistic version of the inheritance view which takes constitutive scientific explanation as a better guide to ground. After illustrating the approach and its merits, we discuss some implications of the emerging scientific conception for the theory of ground at large. (shrink)