The process of selecting individual trees by humans for forest management purposes is the result of a plethora of factors and processes that are hard to disentangle. And yet in the past many textbooks and other publications have maintained that this selection leads to somewhat unanimous results. In this study, we analysed the data of 36 so-called marteloscope experiments from all over Britain, which are managed by the Ae Training Centre (Scotland, UK). Our objective was (1) to establish how much agreement there actually was when asking test persons (raters) to apply two different thinning methods, low and crown thinning. In addition we (2) were interested in understanding some of the processes leading to certain levels of agreement and in relationships between the agreement measures and characteristics of forest structure. Our analysis was based on multivariate statistics, particularly using Fleiss' kappa. This was the first time that an analysis of rater behaviour was performed at such a large scale and it revealed that the general agreement in tree selection in Britain was only slight to fair, i.e. much lower than in medical experiments. The variability of selecting individual trees was considerable. We also found that agreement in tree selection was much stronger in low-thinning as opposed to crown-thinning experiments. As the latter is an important method of Continuous Cover Forestry and British forestry is increasingly adopting this forest management type, our results suggested that there is a need to provide more training. Interestingly the different levels of agreement as identified by Fleiss' kappa could not be explained by measures of forest structure, however, the mean conformity number, a surrogate of Fleiss' kappa, showed correlations and indicated that conformity increased with increasing complexity of tree stem diameter structure.