(test) Economy impact summary

This is an impact report of the citizen science project zEconomy. The scores displayed summarise the results of the assessment process designed by the MICS project. For more information on how they were calculated, visit https://mics.tools

Project Information

Impact Assesment progress:
80% complete

Rules-based scores

These scores are calculated based on a set of rules written to combine a specific set of impact metrics on the same theme into a single indicator. A higher score means the project is carrying out more activities related to the theme of the indicator and is, therefore, more likely to have a higher positive impact in this area. Rule-based scores are only calculated for specific themes. Overall assessments can be found below in the machine-learning--based scoring. Descriptions and explanations of impact indicators are provided at about.mics.tools/indicators (e.g., the score is low on economic productivity because the project did not include specific aspects related to improving efficiency). Different scores trigger different recommendations presented in the following section. Also, scores are not linked to project objectives; they try to capture a broad range of impacts even if the project does not consider or care about all of them. All scores are out of 42.

Impact Indicators Impact score (max 42) Average score (of projects on platform)
Society Activeness 0 22
Involvement 0 17
Governance Policy 0 13
Sustainable Development Goals 0 16
Economy Economic productivity 420 13
Financial sustainability 42 19
Environment Environmental awareness 0 21
Environmental footprint 0 13
Science Scientific productivity 0 18
Interdiscplinary science 0 21

Recommendations

The following recommendations are determined by the scores the project received in the previous section. The recommendations are based on citizen-science best practice as defined in the current scientific literature and how other projects have taken action to improve their impact in specific areas. Of course, following these recommendations does not guarantee the project will suddenly have a higher impact; it all depends on the specific context of each project, but they might provide helpful inspiration.

Society Activeness

The activeness of participants within a project is an important aspect of citizen science. Efforts should be made to make participants aware they are contributing to a research project through clear communication channels, and to offer them the opportunity to be responsible for their activities. If the project has not measured participants' degree of satisfaction in the process, it might want to consider to consider investigating this further using this paper as a starting point.

Involvement

Participants can contribute to many more phases of a project than collecting or analysing data. Think about other phases of the project participants could be involved with in the future, such as sharing the outputs or assessing impact. Remember that different participants will have different interests, knowledge and availability, so try to offer them different levels of involvement and multiple project activities to take part in.

Governance Sustainable Development Goals

The Sustainable Development Goals are a collection of 17 interlinked global goals designed to be a "blueprint to achieve a better and more sustainable future for all". However, citizen science has a much broader remit, so it is ok that your project does not directly consider them. You can find more information on SDGs here, to see if there are any possible links between their aims and your project.

Policy

It looks like policy influence might not be a priority for the project. Of course, not every project can affect policy and some projects have a large impact on governance without ever interacting with official policy. If you're interested in the idea of citizen science as a form of socio-technical governance you can read more in this paper.

If the project is interested in influencing policy it could find inspiration from example projects in this report. It might not be a viable option if the project has already started, but citizen-science projects most often have success influencing policy when specific policies are considered in the design of the project and policy makers are engaged from the start of the project.

Economy Economic productivity

Well done! Can you give us a loan to improve MICS further?

Financial sustainability

Well done! The project has a high score due to forward thinking in creating an exploitation plan, planning sustainability activities to prolong the projects' influence and fully appraising any recurring costs and maintenance.  

Environment Environmental awareness

Being environmentally aware means understanding how our behaviour impacts the environment and committing to making changes to our activities. The project could do more to educate participants on environmental challenges and contribute to participants' awareness of the natural environment, by explicitly disseminating information on sustainable lifestyles. 

Environmental footprint

The project could  do more to decrease its material footprint, take measures to reduce its polluting emissions, or use a sustainable procurement policy.

Science Scientific productivity

It is important to share the outputs of a citizen-science project - through events, media and publications - otherwise learnings will not extend beyond the sphere of the project. Not every citizen-science project has an academic focus on publications. Neverthesless, by publishing the results of the project in peer-reviewed journals, the project could improve its scientific impact. Try to publish in high impact-factor journals so that the publications will be cited more. Perhaps the project could even support students' disseratations or theses in the future.

Interdiscplinary science

Explicitly promoting interdisciplinary ways of working could increase the impact of the project. There is evidence that interdisciplinarity is statistically significantly and positively associated with research impact (Okamura, 2019), largely through the engagement of a wider audience

Machine Learning Scores

The following scores were calculated using a statistically-driven machine-learning approach, a type of AI that learns to perform a task by analysing patterns in data. This is an experimental approach to citizen-science impact assessment, and the exact reasoning behind the scores is not explainable. The scores represent a best guess of the impact the project is having in each domain. How can you use the score? Well, this platform gives a common framework for impact assessment so you can use the scores: to see how the project's impact evolves over time; to compare the project with others; to report to funders and participants; or for your organisation's internal reporting. All scores are out of 42.

Society 1 Society 1 Governance 1 Governance 1 Economy 42 Economy 42 Environment 1 Environment 1 Science and technology 1 Science and technology 1 max. 42
Total Score 9/42