Rule of law diagnosis tool

This tool helps to diagnose the rule of law in a country. It refers to existing sources of data and to additional methods that can be used in order to assess the rule of law and access to justice.

Rule of Law (RoL) is an ideal, principle and ideology. There is a firm evidence that the level of RoL in a given country or region is associated with economic, social and personal development. In order to facilitate the diagnosis and measurement of RoL we developed a  Rule of Law Diagnosis Tool. The model has been built on the availability of a myriad of indicators and indexes which might be used to answer RoL related questions. Its main purpose is to make the exploration of RoL data easier.

The problem which the Rule of Law Diagnosis Tool addresses is the particularization of the data relevant to RoL. A multitude of information with regard to RoL is scattered across different sources on internet, policy and academic papers, and reports. Multitude of cross-country indexes contain valuable bits of data which if analyzed together can reveal new dimensions of RoL. Despite the significant amount of data and methods available it is rarely organized in a way which offers answers to many of the RoL questions. The principal goal of the Rule of Law Diagnosis Tool is to provide civil society organizations, policy makers, donors, practitioners, academics and other RoL stakeholders with an analytical framework for putting together, analyzing and deriving knowledge from RoL data and information. Often RoL analysis has to be conducted with little resources and in tight time limits. The Rule of Law Diagnosis Tool is constructed as a knowledge tool with which an expert but also a layman can formulate informed answers about RoL questions.

The logic of the Diagnosis model is simple. It breaks down the available data sets and methodologies into categories of indicators. Alongside the traditional categories the Diagnosis Model adds notions such as process and outcome, bottom-up and top-down; de facto and de jure. In this way each datum pertaining to the RoL domain is classified in a manner which facilitates the response to RoL questions of different sorts and types. The classification is flexible. When new measurement needs are identified new categories of indicators can be operationalized and applied to the existing sources of data or methodological blueprints. In order to illustrate how the model can be applied, below we review eight data sets containing RoL relevant indicators as well as two methodological approaches. Each of them is classified according to the proposed taxonomy of indicators. At the end of the process, the Diagnosis Model offers an algorithm for finding answers to questions about diagnosing RoL. The diagnosis need is operationalized as a need for specific set of RoL related data. What the algorithm does is to match the need to the existing indicators. Result of the matching is a matrix of data indicators and/or methodological approaches which can provide an evidence based answer to the existing RoL question.

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