Song in oscine birds relies upon the rare capacity of vocal learning. Transmission can be vertical, horizontal, or oblique. As a rule, memorization and production by a naïve bird are not simultaneous: the long-term storage of song phrases precedes their first vocal rehearsal by months. While a wealth of detail regarding songbird enculturation has been uncovered by focusing on the apprentice, whether observational learning can fully account for the ontogeny of birdsong, or whether there could also be an element of (...) active teaching involved, has remained an open question. Given the paucity of knowledge on animal cultures, I argue for the utility of an inclusive definition of teaching that encourages data be collected across a wide range of taxa. Borrowing insights from musicology, I introduce the Australian pied butcherbird into the debate surrounding mechanisms of cultural transmission. I probe the relevance and utility of mentalistic, culture-based, and functionalist approaches to teaching in this species. Sonographic analysis of birdsong recordings and observational data of pied butcherbird behavior at one field site provide evidence that I assess based on criteria laid down by Caro and Hauser, along with later refinements to their functionalist definition. The candidate case of teaching reviewed here adds to a limited but growing body of reports supporting the notion that teaching may be more widespread than is currently realized. Nonetheless, I describe the challenges of confirming that learning has occurred in songbird pupils, given the delay between vocal instruction and production, as well as the low status accorded to anecdote and other observational evidence commonly mustered in instances of purported teaching. As a corrective, I press for an emphasis on biodiversity that will guide the study of teaching beyond human accounts and intractable discipline-specific burdens of proof. (shrink)

Feyerabend is infamous for his defense of pluralism, which he extends to every topic he discusses. Disagreement, a by-product of this pluralism, becomes a sign of flourishing critical communities. In Feyerabend’s political works, he extends this pluralism from science to democratic societies and incorporates his earlier work on scientific methodology into a procedure for designing just policy. However, a description and analysis of Feyerabend’s conception of disagreement is lacking. In this paper, I reconstruct and assess Feyerabend’s conception of disagreement, with (...) a particular emphasis on the role of experts, and its role in the formation of science policy. I go on to assess this argument in light of recent literature on manufactured disagreement on politically contentious science policy. I conclude by suggesting some prospects and problems for de-idealizing Feyerabend’s position on disagreement to see whether it may be plausibly implemented. (shrink)

Citizen science projects have started to utilize Machine Learning to sort through large datasets generated in fields like astronomy, ecology and biodiversity, biology, and neuroimaging. Human–machine systems have been created to take advantage of the complementary strengths of humans and machines and have been optimized for efficiency and speed. We conducted qualitative content analysis on meta-summaries of documents reporting the results of 12 citizen science projects that used machine learning to optimize classification tasks. We examined the distribution of tasks between (...) citizen scientists, experts, and algorithms, and how epistemic agency was enacted in terms of whose knowledge shapes the distribution of tasks, who decides what knowledge is relevant to the classification, and who validates it. In our descriptive results, we found that experts, who include professional scientists and algorithm developers, are involved in every aspect of a project, from annotating or labelling data to giving data to algorithms to train them to make decisions from predictions. Experts also test and validate models to improve their accuracy by scoring their outputs when algorithms fail to make correct decisions. Experts are mostly the humans involved in a loop, but when algorithms encounter problems, citizens are also involved at several stages. In this paper, we present three main examples of citizens-in-the-loop: when algorithms provide incorrect suggestions; when algorithms fail to know how to perform classification; and when algorithms pose queries. We consider the implications of the emphasis on optimization on the ideal of science and the role of citizen scientists from a perspective informed by Science and Technology Studies and Information Systems. Based on our findings, we conclude that ML in CS classification projects, far from being deterministic in its nature and effects, may be open to question. There is no guarantee that these technologies can replace citizen scientists, nor any guarantee that they can provide citizens with opportunities for more interesting tasks. (shrink)

Dominant forms of contemporary big-data based digital citizen science do not question the institutional divide between qualified experts and lay-persons. In our paper, we turn to the historical case of a large-scale amateur project on biogeographical birdwatching in the late nineteenth and early twentieth century to show that networked amateur research can operate in a more autonomous mode. This mode depends on certain cultural values, the constitution of specific knowledge objects, and the design of self-governed infrastructures. We conclude by arguing (...) that the contemporary quest for autonomous citizen science is part of a broader discourse on the autonomy of scientific research in general. Just as the actors in our historical case positioned themselves against the elitism of gentlemen scientists, avant-garde groups of the twenty first century like biohackers and civic tech enthusiasts position themselves against the system of professional science—while “digital citizen science” remains to oscillate between claims for autonomy and realities of heteronomy, constantly reaffirming the classic lay-expert divide. (shrink)

Despite the increase in marine science curriculum in secondary schools, marine science is not generally required curricula and has been largely deemphasized or ignored in relation to earth science, biology, chemistry, and physics. I call for the integration and implementation of marine science more fully in secondary science education through authentic inquiry practices that foster the development of an erotic relationship with the ocean. Such a relationship can provide an opportunity to develop ocean literacy if that means people who engage (...) can actively participate in making more informed choices and advocate for affected parties and the ocean. I show how Simone de Beauvoir's erotic ethic influences the philosophy of the eroticism of the ocean, which is integral in the investigation and promotion of erotic generosities in science education, and using this theory to develop some educational implications for marine science within science education. Ultimately, I argue that the development and nurturing of an erotic ethic in the science education classroom is a valuable way to promote moral and ethical thinking such that students can afford nature, and more specifically in this article, the ocean, equivalent moral considerations in our community and science education. (shrink)

Research collaborations beyond the boundaries of science—such as transdisciplinary, participatory or co-research projects—usually aim at increasing the societal impact of the research conducted. In the literature discussing such collaborations, as well as in science policy endorsing them, it is generally assumed that the wanted societal impact is achieved through exchange that contributes to knowledge production and to the results of the research. However, collaboration beyond the boundaries of science can help a research project reach its societal impact goals even if (...) it does not contribute to the epistemic outcomes of the project at all. Instead, other kinds of contributions from the extra-academic partners, and what the extra-academic partners receive from the collaboration, can be crucial. Recognizing this helps us to better understand existing practices, and to identify potentially interesting forms of collaboration beyond the boundaries of science. (shrink)

This paper describes the activities of amateur plant breeders and their application of various methods and technologies derived from genetics research over the course of the twentieth century. These ranged from selection and hybridization to more interventionist approaches such as radiation treatment to induce genetic mutations and chemical manipulation of chromosomes. I argue that these activities share characteristics with twenty-first-century do-it-yourself (DIY) biology (a recent upswing in amateur experimental biology) as well as other amateur science and technology of the twentieth (...) century. The characterization of amateur plant breeding as amateur experimental biology offers a corrective to a dominant narrative within the history of biology, in which the turn to experimental research in the early twentieth century is thought to have served as an obvious dividing line between amateur and professional activities. Considered alongside other better-known amateur efforts, it also suggests that we might gain something by taking a more unified approach to the study of amateur science and technology. (shrink)

La ciencia abierta constituye una transformación radical en la manera de llevar a cabo la investigación científica. Se trata de un nuevo modelo de hacer ciencia que se basa en el trabajo colaborativo entre personas de la academia y también en la apertura y la transparencia de todas las fases de la investigación. La ciencia abierta tiene sus antecedentes en el uso de las Tecnologías de la Información y la Comunicación por quienes investigan y en la consolidación del acceso abierto (...) a las publicaciones. Por otro lado, en su desarrollo también ha contado con tres elementos facilitadores: su conexión con los valores clásicos de la ciencia, la acción de responsables políticos con capacidad resolutiva en sus organizaciones, y el apoyo institucional, en especial de la Comisión Europea y de diversas agencias de financiación de la investigación. En el artículo se analizan diversas definiciones de ciencia abierta para destacar sus características fundamentales: apertura, transparencia y reutilización de contenidos. Se considera la ciencia abierta como un término «paraguas» que agrupa diversas piezas o elementos como el acceso abierto, los datos abiertos, la revisión abierta, el uso de preprints, la ciencia ciudadana y los nuevos modelos de evaluación. A pesar de que existe discrepancia sobre cuáles son esas piezas elementales, el artículo se centra en los seis elementos mencionados, repasa la situación actual de cada uno de ellos, y pone especial énfasis en su grado de desarrollo y en lo que aportan a la ciencia abierta. Se constata una notable diversidad en el desarrollo de cada una de las piezas y también la ausencia de una acción coordinada, lo que podría suponer una ralentización de las prácticas de ciencia abierta. A pesar de los destacados avances en acceso abierto, de la notable compartición de datos de investigación y de un respetable uso de preprints, se ha avanzado muy poco en el establecimiento de nuevas métricas y de nuevos modelos de evaluación, aun cuando estos son un elemento clave para incentivar la expansión de la ciencia abierta en todas las disciplinas. (shrink)

[This is the complete issue of the second issue of Mɛtascience] -/- This second issue of the journal Mεtascience continues the char acterization of this new branch of knowledge that is metasci ence. If it is new, it is not in a radical sense since Mario Bunge practiced it in an exemplary way, since logical positivists were accused of practicing only a mere metascience, since scientists have always practiced it implicitly, and since some philosophers no longer practice philosophy but rather (...) metascience, but without characterizing it or theorizing it, that is, without realizing that they have abandoned one general discourse for another. The novelty therefore lies in this aware ness that a general discourse without philosophy is possible: a scien tific general discourse. The twelve contributions gathered in this volume illustrate the metascientific approach to knowledge of the world as well as to knowledge of knowledge of the world, that is, science. And like Bunge’s project, they are neither part of the analytical movement nor the continental movement in philosophy. We will read here studies about the Bungean system, some applications of Bungean thought, some metascientific contributions, and some reflections around meta science. Among metascientific disciplines, ontology occupies a prominent place in this issue of Mεtascience. Metascience differs from philoso phy in its rejection of the fundamental philosophical distinction be tween appearance and reality. Metascientific ontology therefore does not postulate the existence of any metaphysical reality. But metasci entific ontology, no more than philosophical ontology, is a factual sci ence. The first, because it studies scientific constructs and not concrete objects, the second, because it is interested in transcendent or meta physical objects. (shrink)

General ontology is a prominent theoretical foundation for information technology analysis, design, and development. Ontology is a branch of philosophy which studies what exists in reality. A widely used ontology in information systems, especially for conceptual modeling, is the BWW (Bunge–Wand–Weber), which is based on ideas of the philosopher and physicist Mario Bunge, as synthesized by Wand and Weber. The ontology was founded on an early subset of Bunge’s philosophy; however, many of Bunge’s ideas have evolved since then. An important (...) question, therefore, is: do the more recent ideas expressed by Bunge call for a new ontology? In this paper, we conduct an analysis of Bunge’s earlier and more recent works to address this question. We present a new ontology based on Bunge’s later and broader works, which we refer to as Bunge’s Systemist Ontology (BSO). We then compare BSO to the constructs of BWW. The comparison reveals both considerable overlap between BSO and BWW, as well as substantial differences. From this comparison and the initial exposition of BSO, we provide suggestions for further ontology studies and identify research questions that could provide a fruitful agenda for future scholarship in conceptual modeling and other areas of information technology. (shrink)