Bridging Physics and Biology Teaching through Modeling

As the frontiers of biology become increasingly interdisciplinary, the physics education community has engaged in ongoing efforts to make physics classes more relevant to life sciences majors. These efforts are complicated by the many apparent differences between these fields, including the types of systems that each studies, the behavior of those systems, the kinds of measurements that each makes, and the role of mathematics in each field. Nonetheless, physics and biology are both sciences that rely on observations and measurements to construct models of the natural world. In the present theoretical article, we propose that efforts to bridge the teaching of these two disciplines must emphasize shared scientific practices, particularly scientific modeling. We define modeling using language common to both disciplines and highlight how an understanding of the modeling process can help reconcile apparent differences between the teaching of physics and biology. We elaborate how models can be used for explanatory, predictive, and functional purposes and present common models from each discipline demonstrating key modeling principles. By framing interdisciplinary teaching in the context of modeling, we aim to bridge physics and biology teaching and to equip students with modeling competencies applicable across any scientific discipline.Comment: 10 pages, 2 figures, 3 table

Theory of language: a taxonomy

The study of language has been historically proposed as a model for human sciences. For the structuralists, it is because languages, like society, and cultural habits, are man-made rule-based systems. For the Darwinists, it is because cultures and societies are like living species, and can be studied with biological methodology. Sociology, biology and linguistics are considered analogous in different ways. To support work in theoretical and applied linguistics, this paper discusses the problem of the nature of language, investigating how the question “What is language?” has been approached from different angles. Textbook answers guide us in many different directions: language is a tool for communication—and for thinking. It is a collection of words and instructions how to use them. It is the characteristic which—arguably—separates humans from other animals. It is a social construction, a system of symbols, a system of systems, and so on. To classify perspectives, the intellectual history of schools of linguistic thought is examined, connecting linguistic theory with related disciplines. A taxonomy is proposed based on two axes: humanistic versus biological; and historical versus systemic. Main linguistics frameworks are identified and placed into a fourfold table based on these axes. They include the Bloomfieldian school (Type 1); Saussurean structuralism and its derivatives (Type 2); generative grammar and biolinguistics (Type 3); and cognitive‒evolutionary linguistics (Type 4).Peer reviewe

The Price equation program: simple invariances unify population dynamics, thermodynamics, probability, information and inference

The fundamental equations of various disciplines often seem to share the same basic structure. Natural selection increases information in the same way that Bayesian updating increases information. Thermodynamics and the forms of common probability distributions express maximum increase in entropy, which appears mathematically as loss of information. Physical mechanics follows paths of change that maximize Fisher information. The information expressions typically have analogous interpretations as the Newtonian balance between force and acceleration, representing a partition between direct causes of change and opposing changes in the frame of reference. This web of vague analogies hints at a deeper common mathematical structure. I suggest that the Price equation expresses that underlying universal structure. The abstract Price equation describes dynamics as the change between two sets. One component of dynamics expresses the change in the frequency of things, holding constant the values associated with things. The other component of dynamics expresses the change in the values of things, holding constant the frequency of things. The separation of frequency from value generalizes Shannon's separation of the frequency of symbols from the meaning of symbols in information theory. The Price equation's generalized separation of frequency and value reveals a few simple invariances that define universal geometric aspects of change. For example, the conservation of total frequency, although a trivial invariance by itself, creates a powerful constraint on the geometry of change. That constraint plus a few others seem to explain the common structural forms of the equations in different disciplines. From that abstract perspective, interpretations such as selection, information, entropy, force, acceleration, and physical work arise from the same underlying geometry expressed by the Price equation.Comment: Version 3: added figure illustrating geometry; added table of symbols and two tables summarizing mathematical relations; this version accepted for publication in Entrop

Assessing evaluation procedures for individual researchers: the case of the Italian National Scientific Qualification

The Italian National Scientific Qualification (ASN) was introduced as a prerequisite for applying for tenured associate or full professor positions at state-recognized universities. The ASN is meant to attest that an individual has reached a suitable level of scientific maturity to apply for professorship positions. A five member panel, appointed for each scientific discipline, is in charge of evaluating applicants by means of quantitative indicators of impact and productivity, and through an assessment of their research profile. Many concerns were raised on the appropriateness of the evaluation criteria, and in particular on the use of bibliometrics for the evaluation of individual researchers. Additional concerns were related to the perceived poor quality of the final evaluation reports. In this paper we assess the ASN in terms of appropriateness of the applied methodology, and the quality of the feedback provided to the applicants. We argue that the ASN is not fully compliant with the best practices for the use of bibliometric indicators for the evaluation of individual researchers; moreover, the quality of final reports varies considerably across the panels, suggesting that measures should be put in place to prevent sloppy practices in future ASN rounds