The current assumptions of knowledge acquisition brought about the crisis in the reproducibility of experiments. A complementary perspective should account for the specific causality characteristic of life by integrating past, present, and future. A “second Cartesian revolution,” informed by and in awareness of anticipatory processes, should result in scientific methods that transcend the theology of determinism and reductionism. In our days, science, itself an expression of anticipatory activity, makes possible alternative understandings of reality and its dynamics. For this purpose, the (...) study advances G-complexity for defining and comparing decidable and undecidable knowledge. AI and related computational expressions of knowledge could benefit from the awareness of what distinguishes the dynamics of life from any other expressions of change. (shrink)

We characterize access to empirical objects in biology from a theoretical perspective. Unlike objects in current physical theories, biological objects are the result of a history and their variations continue to generate a history. This property is the starting point of our concept of measurement. We argue that biological measurement is relative to a natural history which is shared by the different objects subjected to the measurement and is more or less constrained by biologists. We call symmetrization the theoretical and (...) often concrete operation which leads to considering biological objects as equivalent in a measurement. Last, we use our notion of measurement to analyze research strategies. Some strategies aim to bring biology closer to the epistemology of physical theories, by studying objects as similar as possible, while others build on biological diversity. (shrink)

The dependence on history of both present and future dynamics of life is a common intuition in biology and in humanities. Historicity will be understood in terms of changes of the space of possibilities as well as by the role of diversity in life’s structural stability and of rare events in history formation. We hint to a rigorous analysis of “path dependence” in terms of invariants and invariance preserving transformations, as it may be found also in physics, while departing from (...) the physico-mathematical analyses. The idea is that the invariant traces of the past under organismal or ecosystemic transformations contribute to the understanding of present and future states of affairs. This yields a peculiar form of unpredictability in biology, at the core of novelty formation: the changes of observables and pertinent parameters may depend also on past events. In particular, in relation to the properties of synchronic measurement in physics, the relevance of diachronic measurement in biology is highlighted. This analysis may a fortiori apply to cognitive and historical human dynamics, while allowing to investigate some general properties of historicity in biology. (shrink)

"The pursuit of science by professional scientists every day bears less and less resemblance to the perception of science by the general public. It is not the rule-based, methodical system for accumulating facts that dominates the public view. Rather it is the idiosyncratic, often bumbling search for understanding in mostly uncharted places. It is full of wrong turns, cul-de-sacs, mistaken identities, false findings, errors of fact and judgment-and the occasional remarkable success. The widespread but distorted view of science as infallible (...) originates in an education system that teaches nothing but facts using very large, very frightening textbooks, and is spread by media that report on discoveries but almost never on process. It is further reinforced by politicians who pay for it and want to use it to determine policy and therefore want it right and, worst of all, sometimes by scientists who learn early on that talking too much about failures and not enough about successes can harm their careers. Failure, then, is a book that seeks to make science more appealing by exposing its faults. In this sequel to Ignorance, Stuart Firestein shows us that scientific enterprise is riddled with failures, and that this is not only necessary but good. Failure reveals how science got its start, when humans began to use a process-trial and error-as a kind of recipe that includes a hefty dose of failure. It gives the non-scientifically trained public an insider's view of how science is actually done, with the aim of making it accessible, comprehensible, and entertaining."--Publisher description. (shrink)

A discussion of Rose's new theory which argues that life depends on the interactions within cells, organisms and ecosystems and is not wholly dependent on DNA.

Current fears of a “reproducibility crisis” have led researchers, sources of scientific funding, and the public to question both the efficacy and trustworthiness of science. Suggested policy changes have been focused on statistical problems, such as p-hacking, and issues of experimental design and execution. However, “reproducibility” is a broad concept that includes a number of issues. Furthermore, reproducibility failures occur even in fields such as mathematics or computer science that do not have statistical problems or issues with experimental design. Most (...) importantly, these proposed policy changes ignore a core feature of the process of scientific inquiry that occurs after reproducibility failures: the integration of conflicting observations and ideas into a coherent theory. (shrink)

A heated debate surrounds the significance of reproducibility as an indicator for research quality and reliability, with many commentators linking a "crisis of reproducibility" to the rise of fraudulent, careless and unreliable practices of knowledge production. Through the analysis of discourse and practices across research fields, I point out that reproducibility is not only interpreted in different ways, but also serves a variety of epistemic functions depending on the research at hand. Given such variation, I argue that the uncritical pursuit (...) of reproducibility as an overarching epistemic value is misleading and potentially damaging to scientific advancement. Requirements for reproducibility, however they are interpreted, are one of many available means to secure reliable research outcomes. Furthermore, there are cases where the focus on enhancing reproducibility turns out not to foster high-quality research. Scientific communities and Open Science advocates should learn from inferential reasoning from irreproducible data, and promote incentives for all researchers to explicitly and publicly discuss their methodological commitments, the ways in which they learn from mistakes and problems in everyday practice, and the strategies they use to choose which research component of any project needs to be preserved in the long term, and how. (shrink)

The paper argues against the central dogma and its interpretation by C. Kenneth Waters and Alex Rosenberg. I argue that certain phenomena in the regulation of gene expression provide a break with the central dogma, according to which sequence specificity for a gene product must be template derived. My thesis of 'molecular epigenesis' with its three classes of phenomena, sequence 'activation', 'selection', and 'creation', is exemplified by processes such as transcriptional activation, alternative cis- and trans-splicing, and RNA editing. It argues (...) that other molecular resources share the causal role of genes; the sequence specificity for the linear sequence of any gene product is distributed between the coding sequence, cis-acting sequences, trans-acting factors, environmental signals, and the contingent history of the cell (thesis of distributed causal specificity). I conclude that the central dogma has unnecessarily restricted genetic research to the sequencing of protein-coding genes, unilinear pathway analyses, and the focus on exclusive specificity. (shrink)