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Purpose, processes, partnerships, and products: four Ps to advance participatory socio‐environmental modeling

Overview of attention for article published in Ecological Applications, December 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

Mentioned by

twitter
24 tweeters

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
74 Mendeley
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Title
Purpose, processes, partnerships, and products: four Ps to advance participatory socio‐environmental modeling
Published in
Ecological Applications, December 2017
DOI 10.1002/eap.1627
Pubmed ID
Authors

Steven Gray, Alexey Voinov, Michael Paolisso, Rebecca Jordan, Todd BenDor, Pierre Bommel, Pierre Glynn, Beatrice Hedelin, Klaus Hubacek, Josh Introne, Nagesh Kolagani, Bethany Laursen, Christina Prell, Laura Schmitt Olabisi, Alison Singer, Eleanor Sterling, Moira Zellner

Abstract

Including stakeholders in environmental model building and analysis is an increasingly popular approach to understanding ecological change. This is because stakeholders often hold valuable knowledge about socio-environmental dynamics and collaborative forms of modeling produce important boundary objects used to collectively reason about environmental problems. Although the number of participatory modeling (PM) case studies and the number of researchers adopting these approaches has grown in recent years, the lack of standardized reporting and limited reproducibility have prevented PM's establishment and advancement as a cohesive field of study. We suggest a four-dimensional framework (4P) that includes reporting on dimensions of: (1) the Purpose for selecting a PM approach (the why); (2) the Process by which the public was involved in model building or evaluation (the how); (3) the Partnerships formed (the who); and (4) the Products that resulted from these efforts (the what). We highlight four case studies that use common PM software-based approaches (fuzzy cognitive mapping, agent-based modeling, system dynamics, and participatory geospatial modeling) to understand human-environment interactions and the consequences of ecological changes, including bushmeat hunting in Tanzania and Cameroon, agricultural production and deforestation in Zambia, and groundwater management in India. We demonstrate how standardizing communication about PM case studies can lead to innovation and new insights about model-based reasoning in support of ecological policy development. We suggest that our 4P framework and reporting approach provides a way for new hypotheses to be identified and tested in the growing field of PM. This article is protected by copyright. All rights reserved.

Twitter Demographics

The data shown below were collected from the profiles of 24 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 74 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 22%
Researcher 13 18%
Unspecified 11 15%
Student > Master 9 12%
Professor 8 11%
Other 17 23%
Readers by discipline Count As %
Environmental Science 26 35%
Unspecified 21 28%
Agricultural and Biological Sciences 8 11%
Social Sciences 6 8%
Earth and Planetary Sciences 4 5%
Other 9 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 August 2018.
All research outputs
#1,041,416
of 12,960,324 outputs
Outputs from Ecological Applications
#289
of 2,224 outputs
Outputs of similar age
#36,658
of 272,909 outputs
Outputs of similar age from Ecological Applications
#10
of 38 outputs
Altmetric has tracked 12,960,324 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,224 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one has done well, scoring higher than 82% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 272,909 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.