Following the entry into force of the Paris Agreement in November 2016, governments around the world are now expected to turn their nationally determined contributions into concrete climate policies. Given the global public good nature of climate change mitigation and the important cross-country differences in marginal abatement costs, distributing mitigation efforts across countries could substantially lower the overall cost of implementing climate policy. However, abating emissions abroad instead of domestically may face important political and popular resistance. We ran a lab experiment with more than 300 participants and asked them to choose between a domestic and an international reforestation project. We tested the effect of three informational treatments on the allocation of participants’ endowment between the domestic and the international project. The treatments consisted in: (1) making more salient the cost-effectiveness gains associated with offsetting carbon abroad; (2) providing guarantees on the reliability of reforestation programmes; (3) stressing local ancillary benefits associated with domestic offset projects. We found that stressing the cost-effectiveness of the reforestation programme abroad did increase its support, the economic argument in favour of offsetting abroad being otherwise overlooked by participants. We relate this finding to the recent literature on the drivers of public support for climate policies, generally pointing to a gap between people's preferences and economists’ prescriptions.
The openEHR specifications are designed to support implementation of flexible and interoperable Electronic Health Record (EHR) systems. Despite the increasing number of solutions based on the openEHR specifications, it is difficult to find publicly available healthcare datasets in the openEHR format that can be used to test, compare and validate different data persistence mechanisms for openEHR. To foster research on openEHR servers, we present the openEHR Benchmark Dataset, ORBDA, a very large healthcare benchmark dataset encoded using the openEHR formalism. To construct ORBDA, we extracted and cleaned a de-identified dataset from the Brazilian National Healthcare System (SUS) containing hospitalisation and high complexity procedures information and formalised it using a set of open-EHR archetypes and templates. Then, we implemented a tool to enrich the raw relational data and convert it into the openEHR model using the openEHR Java reference model library. The ORBDA dataset is available in composition, versioned composition and EHR openEHR representations in XML and JSON formats. In total, the dataset contains more than 150 million composition records. We describe the dataset and provide means to access it. Additionally, we demonstrate the usage of ORBDA for evaluating inserting throughput and query latency performances of some NoSQL database management systems. We believe that ORBDA is a valuable asset for assessing storage models for openEHR-based information systems during the software engineering process. It may also be a suitable component in future standardised benchmarking of available openEHR storage platforms.
Choosing the right professional that has to meet indeterminate requirements is a critical aspect in humanitarian development and implementation projects. This paper proposes a hybrid evaluation methodology for some non-governmental organizations enabling them to select the most competent expert who can properly and adequately develop and implement humanitarian projects. This methodology accommodates various stakeholders’ perspectives in satisfying the unique requirements of humanitarian projects that are capable of handling a range of uncertain issues from both stakeholders and project requirements. The criteria weights are calculated using a two-step multi-criteria decision-making method: (1) fuzzy analytical hierarchy process for the evaluation of the decision maker weights coupled with (2) technique for order preference by similarity to ideal solution to rank the alternatives which provide the ability to take into account both quantitative and qualitative evaluations. Sensitivity analysis have been developed and discussed by means of a real case of expert selection problem for a non-profit organisation. The results show that the approach allows a decrease in the uncertainty associated with decision-making, which proves that the approach provides robust solutions in terms of sensitivity analysis.
