Speaker
Description
In the Humanities and Social Sciences, Big Data, and technologies of the Digital Humanities have helped to substantiate academic work. For the portability of data however, attributes and values require definitions to preserve their intended meaning through time and space. The standard practice of researchers to rely on ontologies, even for the study of cultures and societies, however, is colonial: It assumes a single truth, relying on individually seen variables. Many notions, from initiation rite to burial, from food to tool, or from disease to health are conceptualized differently, depending on the community, village, region, language, religion, or discipline of the researcher. This is because knowledge of natural, psychological and social phenomena is complex and includes interlocking cycles of multiple factors. In such complex views, classifying a snake as prey or predator, wind as harmful or beneficial, milk as healthy or unhealthy depends on the specific complex of conceptualized interactions. And it is this variety of conceptualizations that is one of the nuclei of studies in the Humanities and Social Sciences.
In this light, we investigate the potential and actual role of definitions for research in the SSAH in a) binding together a set of attributes and values in their mutual dependence as specified in the definition, and b) as a way to summarize or label different or even contradicting historical and contemporaneous conceptions. We propose to include these conceptions as essential component of data-sets, as definitional space of the attributes and values and for the empirical falsification.
Our endeavor starts by classifying and analyzing types of definitions as used in relation to research in the SSAH, using examples from the century-old struggle to define “culture” or Culture. In other words, we set out to create a dataset which for one or several definitions of culture collects and describes tabular data. These data have been collected directly from cultural sites, such as housings, temples, graveyards etc. all over Asia for 15 years, documenting through photos cultural practices and the way they change through migration, time, and space. This data set also recollects artifacts documented in old good paper books published 40 years ago. With such a span of data addressing cultural anthropology, the question of how to design a good definition of Culture becomes unavoidable.
Carl Popper, among others, distinguishes nominal definitions of a word, e.g. “culture”, from essential definitions of a notion, e.g. Culture. The first type of definition answers the question “when to use a word”, the second the question “what is it what we talk about”.
In Social Sciences, the essence of a notion, e.g. of Culture, is not fixed by a genome or a formula. It remains the construct of a theory. The use of essential definitions thus has been criticized as being unnecessary in addition to the obligatory formulation of a theory: In most academic publications, essential definitions don’t match the theory and are therefore not evaluated in the same way as the theory. In this case we speak of weak essential definitions. In this paper, we want to counter this criticism of essential definitions. We argue that essential definitions that match a theory, a type we will call a strong essential definition or heuristic definition, if carefully crafted, projects smoothly into the design of attributes, values and their interrelations for operationalization, data collection and data analysis. Heuristic definitions help to focus and conceptualize, to plan the empiric evaluation and eventually can be falsified and discarded. We claim that they should be the beginning of each academic enterprise and the roots for the compilation of portable data-sets.