Three problems with Kuhn's concept of "crisis"

The aim of the article is to explore Thomas Kuhn’s notion of “scientific crisis” and indicate some difficulties with it. First, Kuhn defines “crisis” through the notion of “anomaly” but distinguishes these concepts in two different ways: categorically and quantitatively. Both of these alternatives face considerable problems. The categorical definition relies on a distinction between “discoveries” and “inventions” that, as Kuhn himself admits, is artificial. The quantitative definition states that crises are a deeper, more profound type of anomaly. Kuhn, however, does not offer any criteria for objectively defining this “severity” of the crises. The second kind of problem is related to the application of the concept of “crisis.” Apparently, Kuhn attributes crises to individuals as much as to communities. Lastly, there is the problem of the function of crises. In The Structure of Scientific Revolutions, they are presented as a precondition to scientific revolutions. In later articles, however, Kuhn seems to see them only as a common antecedent to revolutions

A estrutura das controvérsias científicas: a epistemologia social de Thomas Kuhn

Changes of theories are major events in science. Two main types of questions may be asked about them: i) how do scientists choose new theories?, and ii) how is consensus formed? Generally, philosophers do not distinguish these two questions. Kuhn, on the contrary, offers very different answers to each of these questions. Theory-choice, on the one hand, is explained through the application of epistemic criteria, such as accuracy and consistency; nonetheless, because these values do not prescribe a single choice, consensus formation, on the other hand, is explained through a series of socio-epistemic mechanisms, namely: scientific pedagogy, diffusion and production of knowledge within the community (the “wave motion”), and restructuring of the scientific field. These mechanisms are the basis of Kuhn’s social epistemology, in that they are not restricted to sociology nor epistemology, encompassing both social interactions and epistemic evaluations of theories. Keywords: Thomas Kuhn, consensus formation, social epistemology.Mudanças de teorias são eventos centrais na ciência. Dois tipos principais de perguntas podem ser feitas em relação a eles: i) como os cientistas escolhem novas teorias? e ii) como o consenso é formado? A maior parte dos filósofos não costuma distinguir estas duas questões. Kuhn, entretanto, oferece respostas muito diferentes para cada uma delas. A escolha de teoria é explicada, por ele, por meio da aplicação de critérios epistêmicos, como precisão e consistência. O fato de que esses valores não prescrevem uma única escolha, contudo, leva-o a explicar a formação de consenso por meio de uma série de mecanismos socioepistêmicos, a saber: a pedagogia científica; a difusão e produção de conhecimento dentro da comunidade (o “movimento das ondas”); e a reestruturação do campo científico. Esses mecanismos são a base da epistemologia social de Kuhn, na medida em que não se restringem nem à sociologia nem à epistemologia, envolvendo tanto interações sociais como avaliações epistêmicas de teorias. Palavras-chave: Thomas Kuhn, formação de consenso, epistemologia social.Mudanças de teorias são eventos centrais na ciência. Dois tipos principais de perguntas podem ser feitas em relação a eles: i) como os cientistas escolhem novas teorias? e ii) como o consenso é formado? A maior parte dos filósofos não costuma distinguir estas duas questões. Kuhn, entretanto, oferece respostas muito diferentes para cada uma delas. A escolha de teoria é explicada, por ele, por meio da aplicação de critérios epistêmicos, como precisão e consistência. O fato de que esses valores não prescrevem uma única escolha, contudo, leva-o a explicar a formação de consenso por meio de uma série de mecanismos socioepistêmicos, a saber: a pedagogia científica; a difusão e produção de conhecimento dentro da comunidade (o “movimento das ondas”); e a reestruturação do campo científico. Esses mecanismos são a base da epistemologia social de Kuhn, na medida em que não se restringem nem à sociologia nem à epistemologia, envolvendo tanto interações sociais como avaliações epistêmicas de teorias. Palavras-chave: Thomas Kuhn, formação de consenso, epistemologia social

Thomas Kuhn's Theory of Rationality

According to a widespread view, Thomas Kuhn’s model of scientific development would relegate rationality to a second plane, openly flirting with irrationalist positions. The intent of this article is to clarify this aspect of his thinking and refute this common interpretation. I begin by analysing the nature of values in Kuhn’s model and how they are connected to rationality. For Kuhn, a theory is chosen rationally when: i) the evaluation is based on values characteristic of science; ii) a theory is considered better the more it manifests these values; and iii) the scientist chooses the best-evaluated theory. The second part of this article deals with the thesis of the variability of values. According to Kuhn, the examples through which epistemic values are presented vary for each person, and for this reason individuals interpret these criteria differently. Consequently, two scientists, using the same values, can come to a rational disagreement over which theory to choose. Finally, I point out the limitations of this notion of rationality for the explanation of consensus formation, and the corresponding demand for a sociological theory that reconnects individual rationality with convergence of opinions

Paradigms in Action

The concept of “paradigm” became widely known with Thomas Kuhn’s book The Structure of Scientific Revolutions. From there on, paradigms started being employed in the most diverse fields and situations. Curiously, though, the popularity of the term went hand in hand with an enormous vagueness in its application: numerous meanings were attributed to this concept and different things were claimed to be paradigms. The main reason for the lack of agreement regarding the notion and the use of paradigm was the absence of a detailed description and analysis of a concrete paradigm in Kuhn’s book—especially, one coupled with a discussion that could contrast paradigms to other epistemic objects, such as “theories.” The aim of this article is to fill this gap. First, I briefly examine the notion of paradigm, stressing its core meaning as that of “exemplar.” Next, I analyze a specific case in economics, indicating the features that make it a paradigm: (i) the fact that it is an example not reducible to an axiomatizable theory, and (ii) that this example is constitutive of normal science

Thomas kuhn’s theory of rationality

According to a widespread view, Thomas Kuhn’s model of scientific development would relegate rationality to a second plane, openly flirting with irrationalist positions. The intent of this article is to clarify this aspect of his thinking and refute this common interpretation. I begin by analysing the nature of values in Kuhn’s model and how they are connected to rationality. For Kuhn, a theory is chosen rationally when: i) the evaluation is based on values characteristic of science; ii) a theory is considered better the more it manifests these values; and iii) the scientist chooses the best-evaluated theory. The second part of this article deals with the thesis of the variability of values. According to Kuhn, the examples through which epistemic values are presented vary for each person, and for this reason individuals interpret these criteria differently. Consequently, two scientists, using the same values, can come to a rational disagreement over which theory to choose. Finally, I point out the limitations of this notion of rationality for the explanation of consensus formation, and the corresponding demand for a sociological theory that reconnects individual rationality with convergence of opinions

Three problems with Kuhn's concept of "crisis"

The aim of the article is to explore Thomas Kuhn’s notion of “scientific crisis” and indicate some difficulties with it. First, Kuhn defines “crisis” through the notion of “anomaly” but distinguishes these concepts in two different ways: categorically and quantitatively. Both of these alternatives face considerable problems. The categorical definition relies on a distinction between “discoveries” and “inventions” that, as Kuhn himself admits, is artificial. The quantitative definition states that crises are a deeper, more profound type of anomaly. Kuhn, however, does not offer any criteria for objectively defining this “severity” of the crises. The second kind of problem is related to the application of the concept of “crisis.” Apparently, Kuhn attributes crises to individuals as much as to communities. Lastly, there is the problem of the function of crises. In The Structure of Scientific Revolutions, they are presented as a precondition to scientific revolutions. In later articles, however, Kuhn seems to see them only as a common antecedent to revolutions

Benchmarks for Pir\'a 2.0, a Reading Comprehension Dataset about the Ocean, the Brazilian Coast, and Climate Change

Pir\'a is a reading comprehension dataset focused on the ocean, the Brazilian coast, and climate change, built from a collection of scientific abstracts and reports on these topics. This dataset represents a versatile language resource, particularly useful for testing the ability of current machine learning models to acquire expert scientific knowledge. Despite its potential, a detailed set of baselines has not yet been developed for Pir\'a. By creating these baselines, researchers can more easily utilize Pir\'a as a resource for testing machine learning models across a wide range of question answering tasks. In this paper, we define six benchmarks over the Pir\'a dataset, covering closed generative question answering, machine reading comprehension, information retrieval, open question answering, answer triggering, and multiple choice question answering. As part of this effort, we have also produced a curated version of the original dataset, where we fixed a number of grammar issues, repetitions, and other shortcomings. Furthermore, the dataset has been extended in several new directions, so as to face the aforementioned benchmarks: translation of supporting texts from English into Portuguese, classification labels for answerability, automatic paraphrases of questions and answers, and multiple choice candidates. The results described in this paper provide several points of reference for researchers interested in exploring the challenges provided by the Pir\'a dataset.Comment: Accepted at Data Intelligence. Online ISSN 2641-435

The BLue Amazon Brain (BLAB): A Modular Architecture of Services about the Brazilian Maritime Territory

We describe the first steps in the development of an artificial agent focused on the Brazilian maritime territory, a large region within the South Atlantic also known as the Blue Amazon. The "BLue Amazon Brain" (BLAB) integrates a number of services aimed at disseminating information about this region and its importance, functioning as a tool for environmental awareness. The main service provided by BLAB is a conversational facility that deals with complex questions about the Blue Amazon, called BLAB-Chat; its central component is a controller that manages several task-oriented natural language processing modules (e.g., question answering and summarizer systems). These modules have access to an internal data lake as well as to third-party databases. A news reporter (BLAB-Reporter) and a purposely-developed wiki (BLAB-Wiki) are also part of the BLAB service architecture. In this paper, we describe our current version of BLAB's architecture (interface, backend, web services, NLP modules, and resources) and comment on the challenges we have faced so far, such as the lack of training data and the scattered state of domain information. Solving these issues presents a considerable challenge in the development of artificial intelligence for technical domains

Individuals, Communities, and Groups in Thomas Kuhn’s Model of Scientific Development

In The Structure of Scientific Revolutions, Thomas Kuhn resorts to concepts from several disciplines in order to describe the general patterns of scientific development. This blend of disciplines can be explained in part by Kuhn's intellectual path, from physics to history and then to philosophy of science; but it also points to a deeper methodological problem, which is the question of what is the real unity of analysis in his model of science. The primary intention of this article is, thus, to give a solution to this difficulty. The answer, I believe, rests on identifying three fundamental units present in Kuhn's theory of scientific development. They are, respectively, the individual, responsible for producing evidence, spreading information, and choosing theories; the community, a set of scientists investigating a series of phenomena; and the groups, individuals with similar behavior but with looser institutional or social ties — a usually neglected category in Kuhnian literature, but equally fundamental for the final outcome of scientific debates. After investigating these categories in detail, I propose a way of integrating them into a general model for explaining the resolution of scientific controversies. Finally, I try to resolve the apparent conflict among disciplinary vocabularies by offering an account of the function of sociological, psychological, and epistemological concepts for describing controversies, and some of the methodologies appropriate for each of these tasks