diff --git a/mapping_draft.Rmd b/mapping_draft.Rmd index b27ea57..779cab8 100644 --- a/mapping_draft.Rmd +++ b/mapping_draft.Rmd @@ -748,24 +748,21 @@ ggplot(data=allgroups_gathered, # write.csv(simd_percents_only, "derivedData/simd_percents_only.csv", row.names=FALSE) ``` +```{r create_simd_jitterplot} +# simd jitterplot +# jitterplot option, from Teutonico 2015, p. 63 +# https://ggplot2.tidyverse.org/reference/geom_jitter.html +``` + ```{r create_simd_boxplot} # simd boxplot -# Work in progress below - uncomment when ready. -# simd_df <- data.frame(simd) -# ggplot(simd, aes(x=cond, y=rating, fill=cond)) + geom_boxplot() +# ggplot(data=allgroups_gathered, aes(x=simd_category, y=rank)) + +# geom_boxplot(stat="identity") + +# facet_grid(~group_type) -# clustered bar charts -# convert to long format - -# library(reshape2) -# simd_percents_only_long <- melt(simd_percents_only, id.vars = "simd_rownames", measure.vars = grep("^12", names(simd_percents_only), value = TRUE)) - -# qplot(data=simd_percents_only_long , geom="bar", fill=(factor(simd_rownames))) - -# jitterplot option, from Teutonico 2015, p. 63 -# https://ggplot2.tidyverse.org/reference/geom_jitter.html +# TODO: add calculations inline to text below using data ``` Another crucial point of assessment relates to the relation of Eco-Congregation communities to the Scottish Index of Multiple Deprivation. This instrument aggregates a large variety of factors which can lead to deprivation including crime rates, employment levels, access to services (implicating remoteness), and literacy. By assessing ECS, Transition, and dtas against the deprivation scale, we can assess whether eco-congregations fall within particular demographics and also whether the fully aggregated SIMD measurement provides a useful point of comparison for our purposes. The SIMD essentially divides Scotland into 6407 geographic zones and then ranks them based on their relative deprivation. This data set can be split into any number of groups, but for our purposes we have settled on Quintiles, splitting the SIMD data set at every 1302 entries. We then measured where each transition group, ECS, and dtas fell within these zones and calculated how they fell into these five quintiles, from more to least deprived. @@ -782,6 +779,47 @@ Proximity to these areas was the next concern, because many of these designation So what did I discover? The results were inconclusive. First, it is important to note that on the whole, Eco-Congregations tend to be more urban than place of worship taken generally at a rate of nearly 3:1 (5.4% of Eco-Congregations lie in areas currently designated as "Very Remote Rural Areas" whereas nearly 15% of places of worship lie in these areas), so what I was testing for was whether this gap was smaller when specifying these various forms of "wild" remoteness. For our narrowest measurements, there were so few sites captured as to render measurement unreliable. There are, for obvious reasons, 0 sites located within any of SNG's core wild areas. Similarly, there are very few of our activist communities located within SSSI's (only 5 places of worship out of over 4k, 2 transition towns, (or 2%) and 7 community development trusts (3%)). However, expanding this out makes things a bit more interesting, within 50 metres of SSSI's in Scotland lie 3 Eco-Congregations (or just under 1%), which compares favourably with the 61 places of worship (or just 1.5%) far exceeding our ratio (1:1.5 vs. 1:3). This is the same with our more anachronistic measure of "scenic areas," there are 7 eco-congregations within these areas, and 175 places of worship, making for a ratio of nearly 1:2 (2.1% vs. 4.3%). Taking our final measure, of forested areas, this is hard to calculate, as only one Eco-Congregation lies within either native or generally forested land +```{r wilderness_data_prep} + +https://gateway.snh.gov.uk/natural-spaces/connectors/licence.html?t=opengovernment + +# Download data for SSSI: +# http://gateway.snh.gov.uk/natural-spaces/dataset.jsp?dsid=SSSI + +if (file.exists("data/National_Forest_Inventory_Woodland_Scotland_2017.shp") == FALSE) { +# download.file("", destfile = "data/SSSI_SCOTLAND_ESRI.zip") +unzip("data/SSSI_SCOTLAND_ESRI.zip", exdir = "data") +} + +sssi <- st_read("data/") + +st_within(ecs, sssi) + +# Download wild land areas: +# https://gateway.snh.gov.uk/natural-spaces/dataset.jsp?dsid=WILDLAND + +if (file.exists("data/National_Forest_Inventory_Woodland_Scotland_2017.shp") == FALSE) { +# download.file("", destfile = "data/WILDLAND_SCOTLAND_ESRI.zip") +unzip("data/WILDLAND_SCOTLAND_ESRI.zip", exdir = "data") +} + +wildland <- st_read("data/") + +# Download data for National Forest Inventory: +# Note: UK-wide data is here: https://opendata.arcgis.com/datasets/bcd6742a2add4b68962aec073ab44138_0.zip?outSR=%7B%22wkid%22%3A27700%2C%22latestWkid%22%3A27700%7D + +if (file.exists("data/National_Forest_Inventory_Woodland_Scotland_2017.shp") == FALSE) { +download.file("https://opendata.arcgis.com/datasets/3cb1abc185a247a48b9d53e4c4a8be87_0.zip?outSR=%7B%22wkid%22%3A27700%2C%22latestWkid%22%3A27700%7D", + destfile = "data/National_Forest_Inventory_Woodland_Scotland_2017.zip") +unzip("data/National_Forest_Inventory_Woodland_Scotland_2017.zip", exdir = "data") +} +forest_inventory <- st_read("data/National_Forest_Inventory_Woodland_Scotland_2017.shp") + +ggplot() + + geom_sf(data = forest_inventory) + +``` + # Appendix A ```{r pander_admin_table} diff --git a/mapping_draft.html b/mapping_draft.html index 08dc47e..46e3196 100644 --- a/mapping_draft.html +++ b/mapping_draft.html @@ -245,13 +245,13 @@ $(document).ready(function () { Figure 1

Figure 1

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Figure 2Figure 2

+

Figure 2Figure 2

Given the way population and places of worship are unevenly distributed across Scotland it is important to represent data in terms of relative distribution. For this study, we attempted to “normalise” our data in two different ways, (1) as shown by Figure 2 above, by taking population figures from the 2011 census (see data sheet in Appendix A) and (2) by adjusting relative to the number of places of worship in each council region.13 The latter of these two can yield particularly unexpected results. Thus, of the 4048 “places of worship” in Scotland, the highest concentration is actually the region, with 435, second is 329 (). Rank of Council Areas by population and number of places of worship is also included in Appendix A.

We can use this data to normalise our figures regarding Eco-Congregation Scotland communities and this draws the presence in Edinburgh of ECS communities into even sharper relief, as Edinburgh, though ranked second in terms of population and fifth in terms of places of worship, ranks first for the presence of all ECS congregations and awarded ECS congregations. However, taking population as the basis for normalisation first, we find that Edinburgh is far from the most prominent outlier. In trying to communicate this difference for a lay-audience, we have chosen to list this difference as a multiplier (i.e. there are 2.x times as many congregations as their share of population and an average figure of congregations might allow for) as this conveys the difference in a straight-forward way. Outliers where the disparity between their relative share of the total ECS footprint and their relative share of population is different by a positive ratio of more than double include the Orkney Islands (3.7 times more eco-congregations than their expected average share based on population), Argyll and Bute (admin_lev1[CODE=S12000023]$ecs_pop_factor 4.2x), Stirling (2.76x), and Perthshire and Kinross (2.18x). Interestingly, there are no outliers whose relative share of the total footprint of ECS is double or more in the negative direction (see Appendix A chart for full numbers).

Turning to the total of 4048 “places of worship” in Scotland, we find a slightly different picture of the relative concentration of Eco-Congregations in Scotland. In this case, the outliers are

Whereas our initial measurements indicated a prominent lead for Edinburgh, by normalising our data in this way we can highlight the stronger-than-expected presence of several others that might otherwise escape notice because they lie in a region with significantly lower population or numerically less places of worship. Taking the PointX data on “places of worship” in Scotland, we find a less dramatic picture, but also a slightly different one. The positive outliers include East Renfrewshire (3.4x) Edinburgh (2.9x), Stirling (2.2), West Lothian (1.9x) and Aberdeen (1.5x). Again, negative outliers are far less dramatic, with only Midlothian possessing a ratio of more than 100% negative difference from the number of “places of worship” at 1.5x fewer.

-

Figure 4Figure 4Figure 4

+

Figure 4Figure 4Figure 4

We can compare the representation in these various regions against our comparison groups to see how other community-based organisations cluster in Scottish administrative districts. Here there are some significant contrasts. Scottish Community Development trusts are most intensely concentrated in the Highlands and Argyll & Bute. But, this is consistent with all the other categories, Eco-Congregations, Places of Worship, and dtas are all over-represented in this area, varying only by the degree. Edinburgh is different, here we find that Eco-Congregations and Transition projects are over-represented, while dtass are under-represented. Finally, the highlands are another strong contrast, here we find a very strong over-representation by transition towns and dtass while the representation of Eco-Congregations is relatively close to the population share for that area. The two areas of greatest contrast for Eco-Congregations from the other groups are unsurprising, Edinburgh is the location of the ECS offices, while Stirling is the area in which ECS first began (see Appendix B for full data).

@@ -351,7 +351,7 @@ $(document).ready(function () {

Of all the groups surveyed in this study, Eco-Congregation Scotland is the most heavily concentrated in large urban areas (33.53%), exceeding by almost 50% the rate for all places of worship (22.96% in large urban areas). Transition is a much more modest 20% and development trusts a bit lower at 15%. It is interesting to note that the rate of ECS concentration in these large urban areas matches the level of overall population distribution (34.5%). On the other end of the scale, Eco-Congregation Scotland is the least concentrated in remote rural areas (with 3.93% on level 7 and 5.44% on level 8 on the urban-rural scale), though again, they correlate roughly to the general population distribution (3.2% and 2.9% respectively). Places of worship outpace both the population of Scotland and the footprint of Eco-Congregation Scotland, with 14.98% in very remote rural areas, but this is exceeded by transition at 16.47% and both by Scottish community development trusts at 32.14%. So while Eco-Congregation Scotland correlates roughly with Scottish population distribution across the urban-rural scale, it has a considerably more urban profile than either of the other two groups surveyed.

-Figure 9 +Figure 9

Figure 9