A new classification of measured temporalities: based on the time axis in nature

Abstract

In causal inference, the concept of temporality (or directionality) has not been fully clarified. Starting from causal thinking, this paper divides the time axis in nature into three time domains and two time points by the occurrence timings of both a real cause and a real effect. This has anchored that causal inference can only be realized in the third domain. The measured temporalities can be divided into five types: cross-first-to-third-domain longitudinal (or experimental temporalities), cross-second-to-third-domain longitudinal, within-domain longitudinal, within-domain reversely longitudinal, and within-domain transversal (or observational temporalities). This new classification encompasses all measurement strategies, either for first or multiple measurements, or timely and delayed measurements. Except that the actual measurement for the cause occurs either before its occurrence (only in experiment) or within the second domain, all other measurements are similar to the act of historical reconstruction or "archaeology" , where the importance of measured temporalities may be inferior to the accuracy of the measurements. From the point of view that research design should integrate bias design, this new classification for measured temporalities based on the time axis in Nature, which has a clear meaning and helps to judge the possible biases in the observation methods, provides a basis for correct causal inferences.