Lecture_05_Participatory_Methods.Rmd

## Lecture 5: Participatory Methods For Qualitative Model Development {#participatory_methods}
<!-- [Participatory methods](#participatory_methods) -->

### Participatory methods

The following video outlines some of the tools that can be used in participatory modeling. Watch the video and answer the questions that follow. 

<iframe width="560" height="315" src="https://www.youtube.com/embed/X2ZjG6o7u3o" frameborder="0" allowfullscreen></iframe>

```{r participatory-methods-01, echo=FALSE}
question("Which of these is considered a modeling principle in decision analysis?",
  answer("Incorporate all important aspects into models", correct = TRUE),
  answer("Build models primarily based on data from expirements and measurements"),
  answer("Model system using all sources of information, including local and expert knowledge", correct = TRUE),
  answer("Explicitly consider uncertainties about inputs, processes and outputs", correct = TRUE),
  incorrect = "Watch [the video](https://youtu.be/X2ZjG6o7u3o).",
allow_retry = TRUE
)
```


Future question: Why might it be useful to think about 'the fox and the hedgehog' when hosting participatory model building workshops?"

### Stakeholder management

The following video covers some definitions, methods and tools and a case study related to stakeholder management in decision analysis. Please watch the videos and answer the questions that follow. These will be helpful in determining which tools/techniques you might use to identify stakeholders in your decision analysis process.

THis will also work, but not in html ![](https://youtu.be/Xax-JxlmQf0)

Note that the youtube link needs to begin with https://www.youtube.com/embed/

<iframe width="560" height="315" src="https://www.youtube.com/embed/Xax-JxlmQf0" frameborder="0" allowfullscreen></iframe>

```{r question-stakeholder-management-01, echo=FALSE}
question("Which of these entities do you think could be a stakeholder?",
  answer("Individuals", correct = TRUE),
  answer("Groups", correct = TRUE),
  answer("Non-human entities like forests", correct = TRUE),
 answer("None of these could be a stakeholder"),
  incorrect = "Watch [the video](https://youtu.be/Xax-JxlmQf0) at slide 6 and try again.",
allow_retry = TRUE
)
```


```{r question-stakeholder-management-02, echo=FALSE}
question("What could you do if there are too many experts identified?",
answer("Keep them all"),
answer("Randomly select a few"),
answer("Use criteria to categorize them and select a  representative group", correct = TRUE),
  incorrect = "Watch [the video](https://youtu.be/Xax-JxlmQf0) and try again.",
allow_retry = TRUE
)
```

### Group discussion reading: 

This week you will Reed et al. (2009) ‘Who's in and why?'.

- Reed, M. S. et al. (2009) ‘Who's in and why? A typology of stakeholder analysis methods for natural resource management’, Journal of Environmental Management, 90(5), pp. 1933–1949. doi: 10.1016/j.jenvman.2009.01.001.

Optional additional Reading: 

Luu, Thi Thu Giang, Eike Luedeling, Cory Whitney, and Lisa Biber-Freudenberger. “Stakeholder Engagement in Agro-Climate Service Planning.” Climate Services 33 (January 2024): 100432. https://doi.org/10.1016/j.cliser.2023.100432.

### Bonus materials: 

[Liberating Structures](http://www.liberatingstructures.com/) by Keith McCandless (and others). 

### Plot the stakeholder analysis in R

Plot stakeholders' experience, availability and expertise in decision analysis with the `ggplot2` `ggrepel` `ggthemes` libraries [@R-ggplot2; @R-ggrepel; @R-ggthemes]. Use the stakeholder data set from our git repository. To run this on your machine, save [this raw csv file](https://raw.githubusercontent.com/CWWhitney/Decision_Analysis_Course/main/data/stakeholder.csv) as `.csv` to your local `.RProj` directory. Then use `stakeholder<-read.csv("stakeholder.csv")` to load the data to your R environment and save it as `stakeholder`.

```{r stakeholder-management-01, exercise=TRUE}

ggplot(data = stakeholder, aes(x = Experience,
                               y = Availability,
                               label = stakeholders,
                               color = Expertise)) +
  geom_point(aes(shape=Gender)) +
  xlab("Relevant Experience") +

 #label names of stakeholders and expand space to show full names
  scale_x_continuous(labels = paste(seq(0, 5, by = 1)),
                     breaks = seq(0, 5, by = 1),
                     limits = c(0, 5),
                     expand = c(0, 1)) +
  scale_y_continuous(labels = paste(seq(0, 5, by = 1)),
                     breaks = seq(0, 5, by = 1),
                     limits = c(0, 5),
                     expand = c(0, 1)) +
  theme(plot.margin = unit(c(1, 1, 1, 1), "cm")) +
  theme(legend.position = "none") +

# Create line to categorize stakeholders
  geom_hline(yintercept=2.5, color="white", size=2) +
  geom_vline(xintercept=2.5, color="white", size=2) +

# Show all names of overlapped values
  geom_text_repel(box.padding = 0.3, max.overlaps = Inf, size = 3) +
  annotate("text", label = "Potential core experts",
    x = 4.5, y = 3.2, size = 5, color = "grey48") +
  annotate("text", label = "Resource persons",
           x = 4.5, y = 0.25, size = 5, color = "grey48")
```

Learn more about using names and [overlapped values](https://ggrepel.slowkow.com/articles/examples.html).