Disruption, transformation and silos: medical humanities and the management gurus.

To disrupt, to transform and to break through silos are common sense aims for the medical humanities and other interdisciplinary endeavours. These keywords arise because of the influence upon the academy of management and business gurus, reputed experts who arose in response to the economic crises of the 1980s. Despite the noted analytic deficiencies in the concept of disruption, and its association with product innovation, the term has been extended to academic research, where it connotes radical novelty in research practice, typically accompanied by profound organisational and managerial change. 'Disruption' has become wedded to the word 'transformation' as national funders seek to support more radically innovative research that will maintain Western economic hegemony. A distorted version of Kuhn's model of scientific revolutions underpins the discourse of transformation, which fits humanities research to a template in which revolutionary, transformative shifts can be instrumentally favoured by funders, at the expense of inferior 'incremental' progress. Disruptive and transformative research are, according to funders, more readily produced in organisations that have broken through silos between disciplines. The silo metaphor misleadingly models academic disciplines as if they were essentially unitary entities, akin to the functionally specialised units of a business organisation. The discourse of silos arises from the guru doctrine of the learning organisation. This theory supposes that the organisation-including the university-is literally a living organism, and thereby susceptible to corporate sickness, mortality, infection and disability. Medical humanity researchers should be aware of, and reject, this vitalist metaphysic in which the optimal organisation is a culturally homogeneous supra-personal organism whose immense capacities are harnessed by visionary leaders. Moreover, a new vocabulary should be developed for research evaluation, superseding the supposed hierarchical opposition between transformative and incremental research.

Phenotype divergence and cooperation in isogenic multicellularity and in cancer.

We discuss the mathematical modelling of two of the main mechanisms that pushed forward the emergence of multicellularity: phenotype divergence in cell differentiation and between-cell cooperation. In line with the atavistic theory of cancer, this disease being specific of multicellular animals, we set special emphasis on how both mechanisms appear to be reversed, however not totally impaired, rather hijacked, in tumour cell populations. Two settings are considered: the completely innovating, tinkering, situation of the emergence of multicellularity in the evolution of species, which we assume to be constrained by external pressure on the cell populations, and the completely planned-in the body plan-situation of the physiological construction of a developing multicellular animal from the zygote, or of bet hedging in tumours, assumed to be of clonal formation, although the body plan is largely-but not completely-lost in its constituting cells. We show how cancer impacts these two settings and we sketch mathematical models for them. We present here our contribution to the question at stake with a background from biology, from mathematics and from philosophy of science.

The quality of qualitative research.

In this contribution, we discuss criteria for the quality of qualitative research. We consider reliability and validity as specifications of the comprehensive requirement for 'intersubjective replicability', with which qualitative research should comply. In the data collection phase, 'argumentative' reliability generally must suffice; in the data analysis phase, attention must also be given to 'technical' reliability. Validation of qualitative research has to take place via three approaches: 'communicative', 'critical' or 'empirical' validation. This clarifies the relative validity or 'authenticity' of qualitative research.

Primacy of theory? Exploring perspectives on validity in conceptual psychometrics.

Several conceptions of validity have emphasized the contingency of validity on theory. Here we revisit several contributions to the discourse on the concept of validity, which we consider particularly influential or insightful. Despite differences in metatheory, both Cronbach and Meehl's construct validity, and Borsboom, Mellenbergh and van Heerden's early concept of validity regard validity as a criterion for successful measurement and thus, as crucial for the soundness of psychological science. Others, such as Borgstede and Eggert, regard recourses to validity as an appeal to an (unscientific) folk psychology. Instead, they advocate theory-based measurement. It will be demonstrated that these divergent positions converge in their view of psychological theory as indispensable for the soundness of psychological measurement. However, the formulation of the concept (and scope) of scientific theory differs across the presented conceptions of validity. These differences can be at least partially attributed to three disparities in metatheoretical and methodological stances. The first concerns the question of the structure of scientific theories. The second concerns the question of psychology's subject matter. The third regards whether, and if, to which extent, correlations can be indicative of causality and therefore point toward validity. These results indicate that metatheory may help to structure the discourse on the concept of validity by revealing the contingencies the concrete positions rely on.

The need for a change in medical research thinking. Eco-systemic research frames are better suited to explore patterned disease behaviors.

Many practicing physicians struggle to properly evaluate clinical research studies - they either simply do not know them, regard the reported findings as 'truth' since they were reported in a 'reputable' journal and blindly implement these interventions, or they disregard them as having little pragmatic impact or relevance to their daily clinical work. Three aspects for the latter are highlighted: study populations rarely reflect their practice population, the absolute average benefits on specific outcomes in most controlled studies, while statistically significant, are so small that they are pragmatically irrelevant, and overall mortality between the intervention and control groups are unaffected. These observations underscore the need to rethink our research approaches in the clinical context - moving from the predominant reductionist to an eco-systemic research approach will lead to knowledge better suited to clinical decision-making for an individual patient as it takes into account the complex interplay of multi-level variables that impact health outcomes in the real-world setting.

On the scientific credibility of paleoanthropology.

Smith and Smith and Wood proposed that the human fossil record offers special challenges for causal hypotheses because "unique" adaptations resist the comparative method. We challenge their notions of "uniqueness" and offer a refutation of the idea that there is something epistemologically special about human prehistoric data. Although paleontological data may be sparse, there is nothing inherent about this information that prevents its use in the inductive or deductive process, nor in the generation and testing of scientific hypotheses. The imprecision of the fossil record is well-understood, and such imprecision is often factored into hypotheses and methods. While we acknowledge some oversteps within the discipline, we also note that the history of paleoanthropology is clearly one of progress, with ideas tested and resolution added as data (fossils) are uncovered and new technologies applied, much like in sciences as diverse as astronomy, molecular genetics, and geology.

Positionality statements in science.

The goal of this essay is to clarify positionality as an epistemological scientific concept and address related misunderstandings to help researchers assess whether statements thereof contribute to their work. Positionality statements can be useful for various research designs across scientific fields, when they are used knowingly.

Defining equity, its determinants, and the foundations of equity science.

Advancing equity as a priority is increasingly declared in response to decades of evidence showing the association between poorer health outcomes and the unfair distribution of resources, power, and wealth across all levels of society. Quandries present, however, through incongruence, vagueness and disparate interpretations of the meaning of equity dilute and fragment efforts across research, policy and practice. Progress on reducing health inequities is, in this context, unsurprisingly irresolute. In this article, we make a case for equity science that reimagines the ways in which we (as researchers, as systems leaders, as teachers and mentors, and as citizens in society) engage in this work. We offer a definition of equity, its determinants, and the paradigmatic foundations of equity science, including the assumptions, values, and processes., and methods of this science. We argue for an equity science that can more meaningfully promote coherent alignment between intention, knowledge and action within and beyond the health sciences to spark a more equitable future.

The Myth of the Need for Diversity Among Subjects in Theory-Testing Research: Comments on "Racial Inequality in Psychological Research" by Roberts et al. (2020).

Roberts and colleagues focus on two aspects of racial inequality in psychological research, namely an alleged underrepresentation of racial minorities and the effects attributed to this state of affairs. My comment focuses only on one aspect, namely the assumed consequences of the lack of diversity in subject populations. Representativeness of samples is essential in survey research or applied research that examines whether a particular intervention will work for a particular population. Representativeness or diversity is not necessary in theory-testing research, where we attempt to establish laws of causality. Because theories typically apply to all of humanity, all members of humanity (even American undergraduates) are suitable for assessing the validity of theoretical hypotheses. Admittedly, the assumption that a theory applies to all of humanity is also a hypothesis that can be tested. However, to test it, we need theoretical hypotheses about specific moderating variables. Supporting a theory with a racially diverse sample does not make conclusions more valid than support from a nondiverse sample. In fact, cause-effect conclusions based on a diverse sample might not be valid for any member of that sample.

Cultural evolution: A review of theoretical challenges.

The rapid growth of cultural evolutionary science, its expansion into numerous fields, its use of diverse methods, and several conceptual problems have outpaced corollary developments in theory and philosophy of science. This has led to concern, exemplified in results from a recent survey conducted with members of the Cultural Evolution Society, that the field lacks 'knowledge synthesis', is poorly supported by 'theory', has an ambiguous relation to biological evolution and uses key terms (e.g. 'culture', 'social learning', 'cumulative culture') in ways that hamper operationalization in models, experiments and field studies. Although numerous review papers in the field represent and categorize its empirical findings, the field's theoretical challenges receive less critical attention even though challenges of a theoretical or conceptual nature underlie most of the problems identified by Cultural Evolution Society members. Guided by the heterogeneous 'grand challenges' emergent in this survey, this paper restates those challenges and adopts an organizational style requisite to discussion of them. The paper's goal is to contribute to increasing conceptual clarity and theoretical discernment around the most pressing challenges facing the field of cultural evolutionary science. It will be of most interest to cultural evolutionary scientists, theoreticians, philosophers of science and interdisciplinary researchers.

Limits of Optimization.

Optimization is about finding the best available object with respect to an objective function. Mathematics and quantitative sciences have been highly successful in formulating problems as optimization problems, and constructing clever processes that find optimal objects from sets of objects. As computers have become readily available to most people, optimization and optimized processes play a very broad role in societies. It is not obvious, however, that the optimization processes that work for mathematics and abstract objects should be readily applied to complex and open social systems. In this paper we set forth a framework to understand when optimization is limited, particularly for complex and open social systems.

The notorious man-in-the-street: Hermann Weyl and the problem of knowledge.

Hermann Weyl's philosophical reflections remain a topic of considerable interest in the history and philosophy of science. In particular, Weyl's commitment to a form of idealism, as it pertains to his reading of Husserl and Fichte, has garnered much discussion. However, much less attention has been given to Weyl's later, and at that only partial, turn towards a form of empiricism (i.e. from the late 1920s onward). This lack of focus on Weyl's later philosophy has tended to obscure some of the most significant lessons that Weyl sought to draw from his decades of research in the foundations of mathematics and physics. In this paper, I develop some aspects of what I will term as Weyl's 'modest' empiricism. I will argue that Weyl's turn toward empiricism can be read in the context of a development of Helmholtz's epistemological program and his unique form of 'Kantianism'. The hope is that this reading will not only provide a better understanding of Weyl's later thought, especially his (1954) criticism of Cassirer, but that it may also provide the basis for a novel 'Weylian' account of the mathematization of nature underwriting the group-theoretic methodology of parts of modern physics.

Diagnostic algorithm allows for a scientifically robust and reliable retrospective diagnosis using textual evidence from mid-19th century Basel, Switzerland.

OBJECTIVE: Diagnosing disease from the past using historic textual sources can be controversial as to its accuracy. To overcome these objections, an empirical approach to the historical clinical data was developed. The approach follows a standardised, objective, and systematic evaluation, satisfying the requirements of the philosophy of science. MATERIAL: Physician-managed medical records of mid-19th century patients reported to have suffered from tuberculosis. METHOD: A diagnostic algorithm, quantifying clinical data into a scoring system, was developed based on criteria recorded in the medical sources. The findings were compared to the autopsy results using the Receiver Operating Characteristics method. RESULTS: The generated scoring system correctly predicted the diagnosis of tuberculosis in 86% of patients in the study. 6% false negatives and 8% false positives were predicted. CONCLUSIONS: It is possible to retrospectively diagnose in a reliable and scientifically robust manner under certain conditions. It is important to embed the clinical data into the historical context. A general rejection of retrospective diagnosis is unsubstantiated. Well-designed, disease-specific, and source adapted medical scoring systems are new approaches and overcome criticism raised against retrospective diagnosis. SIGNIFICANCE: This new approach utilises diverse historic sources and potentially leads to reliable retrospective diagnosis of most common diseases of the past. LIMITATIONS: Selection bias of the records allocated. Quality of the historic sources utilized. Restricted statistical assessment potential of historic sources. SUGGESTIONS FOR FURTHER RESEARCH: Development of disease- and epoch-specific medical score systems.

From cause and effect to causes and effects.

It is now-at least loosely-acknowledged that most health and clinical outcomes are influenced by different interacting causes. Surprisingly, medical research studies are nearly universally designed to study-usually in a binary way-the effect of a single cause. Recent experiences during the coronavirus disease 2019 pandemic brought to the forefront that most of our challenges in medicine and healthcare deal with systemic, that is, interdependent and interconnected problems. Understanding these problems defy simplistic dichotomous research methodologies. These insights demand a shift in our thinking from 'cause and effect' to 'causes and effects' since this transcends the classical way of Cartesian reductionist thinking. We require a shift to a 'causes and effects' frame so we can choose the research methodology that reflects the relationships between variables of interest-one-to-one, one-to-many, many-to-one or many-to-many. One-to-one (or cause and effect) relationships are amenable to the traditional randomized control trial design, while all others require systemic designs to understand 'causes and effects'. Researchers urgently need to re-evaluate their science models and embrace research designs that allow an exploration of the clinically obvious multiple 'causes and effects' on health and disease. Clinical examples highlight the application of various systemic research methodologies and demonstrate how 'causes and effects' explain the heterogeneity of clinical outcomes. This shift in scientific thinking will allow us to find the necessary personalized or precise clinical interventions that address the underlying reasons for the variability of clinical outcomes and will contribute to greater health equity.

Edgeworth's mathematization of social well-being.

Francis Ysidro Edgeworth's unduly neglected monograph New and Old Methods of Ethics (1877) advances a highly sophisticated and mathematized account of social well-being in the utilitarian tradition of his 19th-century contemporaries. This article illustrates how his usage of the 'calculus of variations' was combined with findings from empirical psychology and economic theory to construct a consequentialist axiological framework. A conclusion is drawn that Edgeworth is a methodological predecessor to several important methods, ideas, and issues that continue to be discussed in contemporary social well-being studies.

Neuropsychological assessment methodology revisited: metatheoretical reflections.

Theory building in neuropsychology, similar to other disciplines, rests on metatheoretical assumptions of philosophical origin. Such assumptions regarding the relation of psychological and physiological variables influence research methodologies as well as assessment strategies in fields of application. Here, we revisit the classic procedure of Double Dissociation (DD) to illustrate the connection of metatheory and methodology. In a seemingly unbridgeable opposition, the classical neuropsychological procedure of DD can be understood as either presupposing localizationism and a modular view of the brain, or as a special case of the generalized neuro-lens model for neuropsychological assessment. In the latter case, it is more easily compatible with a perspective that emphasizes the systemic-network, rather than the modular, nature of the brain, which as part of the organism, proportionately mediates the situatedness of the human being in the world. This perspective not only makes it possible to structure ecological validation processes and give them a metatheoretical foundation, but also to interlace it with the phenomenological insight that the laboratory as one context of empirical research may be analyzed in terms of situated experience. We conclude with showing that both the localizationist and the system science approach can agree on a view of the brain as a dynamical network, and that metatheory may thus offer important new perspectives of reconciliation.

A Framework for Transparency in Precision Livestock Farming.

As precision livestock farming (PLF) technologies emerge, it is important to consider their social and ethical dimensions. Reviews of PLF have highlighted the importance of considering ethical issues related to privacy, security, and welfare. However, little attention has been paid to ethical issues related to transparency regarding these technologies. This paper proposes a framework for developing responsible transparency in the context of PLF. It examines the kinds of information that could be ethically important to disclose about these technologies, the different audiences that might care about this information, the challenges involved in achieving transparency for these audiences, and some promising strategies for addressing these challenges. For example, with respect to the information to be disclosed, efforts to foster transparency could focus on: (1) information about the goals and priorities of those developing PLF systems; (2) details about how the systems operate; (3) information about implicit values that could be embedded in the systems; and/or (4) characteristics of the machine learning algorithms often incorporated into these systems. In many cases, this information is likely to be difficult to obtain or communicate meaningfully to relevant audiences (e.g., farmers, consumers, industry, and/or regulators). Some of the potential steps for addressing these challenges include fostering collaborations between the developers and users of PLF systems, developing techniques for identifying and disclosing important forms of information, and pursuing forms of PLF that can be responsibly employed with less transparency. Given the complexity of transparency and its ethical and practical importance, a framework for developing and evaluating transparency will be an important element of ongoing PLF research.

The Scientific Status of Acceptance and Commitment Therapy: An Analysis From the Philosophy of Science.

How good is the science in the Acceptance and Commitment Therapy (ACT) program? This article examines ACT philosophy, theory, and research on five dimensions: (1) the quality of its meta-science; (2) the clarity of its constructs; (3) the psychometrics of its principal measures; (4) the adequacy of its account of values; and (5) the quality of its research. Significant problems are found in each dimension, and suggestions for improvements are offered. ACT aligns with a Machiavellianism that is problematic in accurately describing these commitments and constituting a meta-stance that permits problematic values to be embraced. Relatedly, there is evidence of a positive bias in ACT research that has been ignored methodologically and in summaries of ACT. These problems justify significant skepticism regarding any claims from the science associated with ACT. Avoiding questionable research practices, psychometrically problematic measures, and research designs that weaken valid causal inference is recommended. Finally, an increased commitment to open science, intellectual humility, and severe testing is recommended.

Putting the "Decision" in Ramsey's "Theories".

Frank Ramsey's philosophy of science is considered abstruse due to the incompleteness and difficulty of his paper "Theories". This has not prevented various authors from arguing that Ramsey is committed to meaning holism for scientific theories, and that his philosophy of science is anti-realist but anti-reductionist. However, it is unclear exactly how meaning holism works for Ramsey, and how he can be both anti-realist and anti-reductionist. I argue that clarity can be gained on both issues by examining Ramsey's philosophy of science through a reconstruction of his decision theory compatible with his later philosophical beliefs. I develop an account of how credences can be formed over singular, theoretical propositions despite those propositions being fictions. Credences are ultimately measured by preferences over conditionals whose antecedents are the verification conditions of theoretical propositions and outcomes are elements of a privileged partition on an agent's possibility space induced by the language of the theory. Those verification conditions are the observational elements formed from the unions of this induced partition. Meaning holism is explained as the sensitivity of theoretical propositions to their verification conditions. And anti-realism and anti-reductionism can be maintained due to theoretical propositions forming a finer partition of possibility space than observational propositions, which prevents the former from being truth-functions of the latter.

"Molecular Biology"-Pleonasm or Denotation for a Discipline of Its Own? Reflections on the Origins of Molecular Biology and Its Situation Today.

The disciplinary identity of molecular biology has frequently been called into question. Although the debates might sometimes have been more about creating or debunking myths, defending intellectual territory and the distribution of resources, there are interesting underlying questions about this area of biology and how it is conceptually organized. By looking at the history of molecular biology, its origins and development, I examine the possible criteria for its status as a scientific discipline. Doing so allows us to answer the title question in such a way that offers a reasonable middle ground, where molecular biology can be properly viewed as a viable interdisciplinary program that can very well be called a discipline in its own right, even if no strict boundaries can be established. In addition to this historical analysis, a couple of systematic issues from a philosophy of science perspective allow for some assessment of the current situation and the future of molecular biology.