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AbstractThe main question of metasemantics, or foundational semantics, is why an expression token has the meaning (semantic value) that it in fact has. In his reading of Ludwig Wittgenstein's later work, Saul Kripke presented a skeptical challenge that threatened to make the foundational question unanswerable. My first contention in this paper is that the skeptical challenge indeed poses an insoluble paradox, but only for a certain kind of metasemantic theory, against which the challenge effectively works as a reductio ad absurdum argument. My second contention is that as a result of rejecting the theory which entails a paradoxical outcome, we will see that the foundational question essentially involves a temporal dimension. After arguing that the skeptical challenge gives us a strong reason to adopt a historical view of meaning, I shall further argue against certain authors who claim that meanings not only have histories but futures as well, or that the meaning of a word may change retroactively in time as a consequence of counterfactual change in its future use. The major aim of the paper is thus to bring together the arguably interrelated debates about the skeptical challenge and temporal externalism in philosophy of language.

AbstractAccording to the causal-historical theory of reference, natural kind terms refer in virtue of complicated causal relations the speakers have to their environment. A common objection to the theory is that purely causal relations are insufficient to fix reference in a determinate fashion. The so-called hybrid view holds that what is also needed for successful fixing are true descriptions associated in the mind of the speaker with the referent. The main claim of this paper is that the objection fails: reference fixing of natural kind terms can be purely causal. The main argument draws inspiration from recent theoretical advances made in metaphysics of kinds by Marion Godman, Antonella Mallozzi, and David Papineau. The main claim is that their notion of super-explanatory properties may explain how reference of many kind terms can be fixed purely causally.

AbstractWe propose an approach for the planning of longitudinal covariate measurements in follow‐up studies where covariates are time‐varying. We assume that the entire cohort cannot be selected for longitudinal measurements due to financial limitations, and study how a subset of the cohort should be selected optimally, in order to obtain precise estimates of covariate effects in a survival model. In our approach, the study will be designed sequentially utilizing the data collected in previous measurements of the individuals as prior information. We propose using a Bayesian optimality criterion in the subcohort selections, which is compared with simple random sampling using simulated and real follow‐up data. Our work improves the computational approach compared to the previous research on the topic so that designs with several covariates and measurement points can be implemented. As an example we derive the optimal design for studying the effect of body mass index and smoking on all‐cause mortality in a Finnish longitudinal study. Our results support the conclusion that the precision of the estimates can be clearly improved by optimal design.

Background The decreasing participation rates and selective non-participation peril the representativeness of health examination surveys (HESs). Methods Finnish HESs conducted in 1972–2012 are used to demonstrate that survey participation rates can be enhanced with well-planned recruitment procedures and auxiliary information about survey non-participants can be used to reduce selection bias. Results Experiments incorporated to pilot surveys and experience from previously conducted surveys lead to practical improvements. For example, SMS reminders were taken as a routine procedure to the Finnish HESs after testing their effect on a pilot study and finding them as a cost-effective way to increase participation rate especially among younger age groups. Auxiliary information about survey non-participants can be obtained from many sources: sampling frames, previous measurements in longitudinal setting, re-contacts and non-response questionnaires, and record linkage to administrative data sources. These data can be used in statistical modelling to adjust the population level estimates for the selection bias. Information on the characteristics of non-participants also helps to improve targeting the recruitment in the future. Conclusion All methods discussed and recommended are relatively easy to incorporate to any national HES in Europe except the record linkage of survey data from administrative data sources. This is not feasible in all European countries because of non-existence of registries, lack of an identifier needed for record linkage, or national data protection legislation which restricts the data use. ; peerReviewed