A proposal for the demarcation of theory and knowledge: Of language-dependent and language-independent reality
Research communication in interdisciplinary research projects requires a way of demarcation of theory and knowledge that is easy to communicate, is inconsequential for the framework of concepts, results, and procedures within existing scientific disciplines, and abstains from trying to resolve the dispute between (neo)positivists and constructivists. A simple way of demarcation starts from the notion of language-independent and language-dependent reality. Currently, what passes for knowledge (“news”) and myth (“fake news”) depends, besides on sheer volume and frequency of the messages, increasingly on the internal consistency of (computer) language-dependent reality and decreasingly on language-independent reality. All language is instruction, and knowledge is to know which instructions (that is, theory) are predictive of a result, state, or situation in language-independent reality. Any theory that doesn’t reduce outcome space, or contains one or more empirically/physically impossible instructions, or produces wrong predictions, or falls short of demonstration is not knowledge.
Kampen, J. K. (2020). Metaphilosophy, 51(1). DOI: 10.1111/meta.12398
Reflections on and test of the metrological properties of summated rating, Likert, and other scales based on sums of ordinal variables.
This study aims to contribute to the perpetual controversy on the parametric analysis of ordinal data, by giving a perchance long overdue examination of the widely held notion that sums of ordinal variables (e.g., Likert and summated rating scales) produce measures at ordinal level. In the present study, all 1,048,574 subscales of a well-known and widely applied sumscale, the 20-item CESD scale for depression, were assessed for their metrological properties. It was found that subscales consisting of less than 60% of the items of the original scale have lost all metrological properties of that scale, including ordinality as measured by Kendall’s tau. This result justifies concern about the robustness of measurement scale properties of (shortened) sumscales, and by implication, of the empirical findings based on such scales.
Kampen, J. K. (2019). Measurement, 137, 428-434. 10.1016/j.measurement.2019.01.083
Research design: the methodology for interdisciplinary research framework
Many of today’s global scientific challenges require the joint involvement of researchers from different disciplinary backgrounds (social sciences, environmental sciences,
climatology, medicine, etc.). Such interdisciplinary research teams face many challenges resulting from differences in training and scientific culture. Interdisciplinary
education programs are required to train truly interdisciplinary scientists with respect to the critical factor skills and competences. For that purpose this paper presents the Methodology for Interdisciplinary Research (MIR) framework. The MIR framework was developed to help cross disciplinary borders, especially those between the natural sciences and the social sciences. The framework has been specifically constructed to facilitate the design of interdisciplinary scientific research, and can be applied in an educational program, as a reference for monitoring the phases of interdisciplinary research, and as a tool to design such research in a process approach. It is suitable for research projects of different sizes and levels of complexity, and it allows for a range of methods’ combinations (case study, mixed methods, etc.). The different phases of designing interdisciplinary research in the MIR framework are described and illustrated by real-life applications in teaching and research. We further discuss the framework’s utility in research design in landscape architecture, mixed methods research, and provide an outlook to the framework’s potential in inclusive interdisciplinary research, and last but not least, research integrity.
Tobi, H. & J.K. Kampen (2018), Quality & Quantity 52:1209–1225. DOI: 10.1007/s11135-017-0513-8