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12. The toys of organic chemistry: material manipulatives and scientific reasoning
- Creator:
- Maddalena, Kate McKinney
- Format:
- print, bez média, and svazek
- Type:
- model:article and TEXT
- Subject:
- teorie vědy, teorie poznání, theory of science, manipulativní modely, materialita, hračky ve vědě, epistemology, manipulative models, materiality, toys in science, 12, and 00
- Language:
- Czech
- Description:
- Chemické vizualizace a modely jsou zvláštními druhy médií myšlení. Tato studie zkoumá několik historických případových studií – archív obrazů z muzeí, specializovaných sbírek a populárně-vědeckých časopisů – emergentních praktik materiálního modelování coby teoretické hry, jež se staly základem molekulární biologie a strukturní chemie. Sleduji dědictví nástrojů vizualizace počínaje Archibaldem Scottem Cooperem a Friedrichem Kekulé na konci 19. století, jejich vyústění do materiálních manipulativů Van’t Hoffa a užití jeho skládaných papírových "hraček“ Linusem Paulingem i jejich následné pronikání do populární obraznosti díky modelu DNA Jamese Watsona a Francise Cricka. Sleduji dále jejich vliv na současné praktiky modelování a zdůrazňuji, že materiální modely, jež tradičně stály za hranicemi deduktivní, pozitivistické vědy, jsou nyní v těchto oblastech chemie akceptovány jako způsob vědeckého uvažování., Chemical visualizations and models are special kinds of media for thinking. In this paper, I examine several historical case studies-an archive of images from museums, special collections, and popular magazines- as examples of emergent practices of physical modeling as theoretical play which became the basis for molecular biology and structural chemistry. I trace a legacy of visualization tools that starts with Archibald Scott Cooper and Friedrich Kekulé in the late 1800s, crystallizes as material manipulatives in Van’t Hoff and his folded paper “toys”, is legitimized in the California lab of Linus Pauling, and is glorified in the popular imaginary with James Watson and Francis Crick’s model of DNA. My tracing then follows several threads into contemporary modeling practices. I ultimately argue that modeling play, originally outside of the boundary of deductive, positivist science, is now an accepted mode of reasoning in these related chemical fields., and Kate McKinney Maddalena.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
13. Velká data jako alternativa výběrových šetření v kvantitativním sociálněvědním výzkumu
- Creator:
- Johana Chylíková
- Format:
- print, bez média, and svazek
- Type:
- model:article and TEXT
- Subject:
- big data, kvalita dat, metodologie, data quality, methodology, survey, epistemology, 18, and 316.4/.7
- Language:
- Czech
- Description:
- The goal of this article is to inform social scientists, especially those of a quantitative orientation, about the basic characteristics of Big Data and to present the opportunities and limitations of using such data in social research. The paper informs about three basic types of Big Data as they are distinguished in contemporary methodological literature, namely administrative data, transaction data and social network data, and exemplifies how they can be utilized by quantitative social research. According to many, questionnaire-based sample survey as the dominant method of quantitative social research has found itself in a crisis, especially as response rates have decreased in most developed countries and public confidence in opinion polling has declined. The author presents the characteristics and specifics of Big Data compared to survey research - a method whose primary distinguishing characteristic is the capacity to quantify individual behaviour, social action and attitudes at the level of populations. In this context, the article draws attention to the differences between Big Data and survey data typically presented in scholarly literature, namely that datasets are not representative of known populations, the values of observed variables are systematically biased, there is a limited number of variables in Big Data sets, there is uncertainty about the meaning of observed values, and social environment has direct influence on the behaviours captured by Big Data. Attention is also paid to such characteristics of Big Data that pose an obstacle to smooth integration of this type of data in the social scientific mainstream. First, the collection, processing and analysis of Big Data is extremely demanding in terms of programming skills, something social scientists typically do not have. Second, the availability of Big Data is limited as they are normally possessed by private corporations, some of which (Facebook, Google) have undoubtedly come to form data oligopolies - and their management is mostly unwilling to share their data with traditional academics. Based on the above-mentioned specifics, differences and limitations, it is argued that Big Data currently do not have the potential of becoming a full-fledged source of social science data and replacing sample surveys as the dominant research method. Finally, the article draws attention to the specifics of different types of Big Data as they are primarily generated for purposes other than social research and result from specific situations framed by existing social relations - and it is from this perspective that Big Data should be viewed by social researchers., Johana Chylíková., and Obsahuje bibliografické odkazy
- Rights:
- http://creativecommons.org/licenses/by-nc-sa/4.0/ and policy:public