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dogesr
to work with
Venetian doges tenuresSince Venetian doges were elected for life, it was apparently a
conscious design by the electoral college (composed, after a series of
lot drawings and designations of 41 nobles from the Maggior Consiglio)
to choose them in such a way that their terms would not last too long
(Smith, Crowley, and Leguizamon 2021).
Using data from dogesr
(Merelo-Guervós 2022), we will, in this
vignette, see to what extent that happened and if there was some
evolution during the time the Republic of Venice existed
This will import the data from the dogesr
package into
the data.doges
data frame. We are interested in the
Doges
and Years
variables. Let’s create a data
frame out of that:
Several doges only were able to stay alive during the same year
Michele Morosini |
Nicolo Donato |
Francesco Corner |
And quite a few during one year or less
doges.one.year <- unique(doges.all.years[doges.all.years$years <= 1,])
knitr::kable(doges.one.year[order(doges.one.year$years),],col.names=NULL)
71 | Michele Morosini | 0 |
107 | Nicolo Donato | 0 |
115 | Francesco Corner | 0 |
2 | Domenico Leone | 1 |
3 | Felice Cornicula | 1 |
4 | Teodato | 1 |
5 | Gioviano | 1 |
6 | Giovanni Fabriciaco | 1 |
8 | Galla Gaulo | 1 |
19 | Pietro I Candiano | 1 |
28 | Vitale Candiano | 1 |
58 | Marino Zorzi | 1 |
63 | Marino Faliero | 1 |
65 | Giovanni Gradenigo | 1 |
80 | Nicolo Marcello | 1 |
85 | Marco Barbarigo | 1 |
93 | Marcantonio Trivisan | 1 |
100 | Sebastiano Venier | 1 |
109 | Francesco Contarini | 1 |
111 | Nicolo Contarini | 1 |
114 | Carlo Contarini | 1 |
117 | Giovanni Pesaro | 1 |
131 | Marco Foscarini | 1 |
So it effectively looks like most doges effectively had a short shelf life. As a matter of fact, the doge that staid in power the longest was
doge | years | |
---|---|---|
75 | Francesco Foscari | 34 |
Francesco Foscari was elected when he was 50, defeating Pietro Loredan. After being in power for 34 years, he was the only doge forced to abdicate after the serrata or new rules electing the doges.
We can see whether this has any kind of influence using now several
functions provided by the dogesr
package next.
doges.years
This can be analyzed a but further with a function provided by
dogesr
, doges.years
. This filters part of the
original data, leaving only data needed to work with the doges’ terms
(or years)
Doge | Century | Start | End | Family.doge | Years | |
---|---|---|---|---|---|---|
68 | Francesco Foscari | 15 | 1423 | 1457 | Foscari | 34 |
33 | Domenico I Contarini | 11 | 1041 | 1071 | Contarini | 30 |
16 | Pietro Tradonico | 9 | 837 | 864 | Tradonico | 27 |
20 | Pietro Tribuno | 9 | 888 | 912 | Pietro | 24 |
45 | Pietro Ziani | 13 | 1205 | 1229 | Ziani | 24 |
10 | Maurizio Galbaio | 8 | 764 | 787 | Galbaio | 23 |
52 | Pietro Gradenigo | 13 | 1289 | 1311 | Gradenigo | 22 |
21 | Orso II Participazio | 10 | 912 | 932 | Participazio | 20 |
46 | Jacopo Tiepolo | 13 | 1229 | 1249 | Tiepolo | 20 |
78 | Leonardo Loredan | 16 | 1501 | 1521 | Loredan | 20 |
First thing we can note is that, among the top 10, there is only one, Leonardo Loredan, who was elected after the aforementioned Francesco Foscari. This was, according to everyone, an unexpected event (Wikipedia contributors 2022), and he was chosen by the minimum needed to get elected. So he was really an outlier. The distribution in bins of 5 years, below, shows how infrequent was a term of more than 10 years.
In fact, doges’ years of ruling were as short as the life of the common dog.
The distribution is skewed because it includes the first years of the institution. This is the distribution by centuries
doges.years$Century <- as.factor(doges.years$Century)
ggplot(doges.years, aes(x=Century,y=Years))+geom_boxplot()
There seems to be a clear difference before and after the thirteenth century; there is also a return to longer tenures by the end of the Republic, in the 18th century. Was there a real difference?
doges.years$pre.serrata <- TRUE
doges.years[doges.years$Start >= 1297,]$pre.serrata <- FALSE
means <- aggregate(Years ~ pre.serrata, doges.years, mean)
medians <- aggregate(Years ~ pre.serrata, doges.years, median)
ggplot(doges.years, aes(x=pre.serrata, y=Years))+geom_boxplot(notch=T)+
stat_summary(fun=mean, geom="point", shape=20, size=3, color="red", fill="red") +
geom_text(data = means, aes(label = round(Years, 2), y = Years + 2), size = 3) +
geom_text(data = medians, aes(label = round(Years, 2), y = Years - 1), size = 3)
This difference is significant, as indicated by the Wilcoxon test
wilcox.test(doges.years[doges.years$pre.serrata == T,]$Years, doges.years[doges.years$pre.serrata == F,]$Years )
#>
#> Wilcoxon rank sum test with continuity correction
#>
#> data: doges.years[doges.years$pre.serrata == T, ]$Years and doges.years[doges.years$pre.serrata == F, ]$Years
#> W = 2467.5, p-value = 0.001425
#> alternative hypothesis: true location shift is not equal to 0
As indicated by (Smith, Crowley, and Leguizamon 2021), there seems to be evidence that supports the existence of “informal” limits on the terms of doges of the the Republic of Venice. In their paper they indicate 1172 as a departure point for the term “limits”, when the Maggior Consiglio was formed. According to the figure above, there does not seem to be a significant difference between the XII and XIII century in terms of tenure. However, 1297 does seem to be a watershed event, with all terms after that being significantly different to terms prior to it. We can conclude, then, that the Serrata, closing of the Maggior Consiglio to all but a few patrician families, was in fact the event that marked the shift to electing older doges.
This vignette also shows how, using dogesr
, it becomes
significantly easier for everyone with the skill to work with the R
language to reproduce or work upon results related to life terms and
other Venetian doges data.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.