Sensitivity of Radiocarbon Sum Calibration

Martin Hinz

doi:10.5334/jcaa.53

Abstract

Sum calibration has become a standard tool for demographic studies, even though the methodology itself is far from uncontroversial. In addition to fundamental methodological criticism, questions are frequently raised about the sample size and data density required to detect large-scale changes in past populations. This article uses a simulation approach to determine the detection probabilities for events of varying intensity and with varying data density. At the same time, the effectiveness of Monte Carlo-based confidence envelopes as a countermeasure against false-positive results is tested. The results show that the detection of such events is not unlikely and that the Monte Carlo method is well suited to separate signal and noise. However, the nature of the events already observed in this way demands further assessment.

Highlights

In recent years, the use of more or less large collections of 14C data has almost become a standard tool to estimate demographic developments of the past
There is a history of debate on the use of radiocarbon Summed Probability Distributions (SPDs)
The results for weak signals remain at a low level, while those for strong signals number of samples 30 40 50 60 70 80 90 100 200 300 400 500 600 700 800 900 1000 2000 sample density number of samples 30 40 50 60 70 80 90 100 200 300 400 500 600 700 800 900 1000 2000 sample density rise sharply from a sample size of about 200

Summary

Introduction

The use of more or less large collections of 14C data has almost become a standard tool to estimate demographic developments of the past. Increased certainty about the validity of the signal requires either more data or a stronger signal This means that strong demographic fluctuations in the past can be detected with greater certainty even based on smaller amounts of 14C datings, whereby more data would be required in the case of weaker fluctuations. These relationships are fundamental to any kind of statistical hypothesis test. This is a very valuable and useful contribution to the debate Their main case study is the Black Death, whose demographic influence can be adequately understood from written sources. The chosen one serves the authors above all to show that such a devastating event as the Black Death could remain undiscovered by 14C summations

Methods

Results

Conclusion