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In several context ranging from medical to social sciences, rater reliability is assessed in terms of intra (-inter) rater agreement. The extent of rater agreement is commonly characterized by comparing the value of the adopted agreement coefficient against a benchmark scale. This deterministic approach has been widely criticized since it neglects the influence of experimental conditions on the estimated agreement coefficient. In order to overcome this criticism, in this paper a statistical procedure for benchmarking is presented. The proposed procedure is based on non parametric bootstrap confidence intervals. The statistical properties of the proposed procedure have been studied via a Monte Carlo simulation.