In eworx-org/iscoCrosswalks: Crosswalks Between Classifications of Occupations

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
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iscoCrosswalks

The goal of iscoCrosswalks is to map indicators and raw counts from the International Standard Classification of Occupations (ISCO) to the Standard Occupational Classification (SOC) System, and vice versa.

Installation

You can install the development version of iscoCrosswalks from GitHub with:

# install.packages("devtools")
devtools::install_github("eworx-org/iscoCrosswalks")

Example

This is a basic example which shows you how to translate CEDEFOPs "Importance of foundation skills" indicator given in ISCO(2008) to SOC(2010) classification:

• For further details visit CEDEFOPs skills intelligence tool

library(iscoCrosswalks)

library(ggplot2)
foundation_skills[, Skill := gsub(" skills", "", Skill)]
dat <- foundation_skills[order(Skill, -Value)][, head(.SD, 6), by = "Skill"]
ggplot(dat, aes(x = Occupations, y = Value, fill = Skill)) +
  geom_col(alpha = 0.8, width = 0.85) +
  scale_fill_brewer(palette = "Dark2") +
  scale_y_continuous(expand = c(0, 0.1)) +
  coord_flip() +
  facet_grid(rows = vars(Skill), scales = "free_y", switch = "y", space = "free_y") +
  labs(
    title = "Which foundation skills are very important for jobs?",
    subtitle = "Highest level needed for doing their job - ISCO 2008",
    caption = "Source: Cedefop's European skills and jobs survey",
    y = "% of jobs for which foundation skills are important"
  ) +
  theme_minimal(base_family = "Roboto Condensed") +
  theme(
    plot.margin = margin(0.5, 0.5, 0.5, 0.5, unit = "cm"),
    plot.title = element_text(size = 15, face = "bold"),
    strip.text.y = element_text(angle = 270, face = "bold"),
    strip.placement = "outside",
    axis.title.x = element_text(margin = margin(t = 0.5, b = 0.5, unit = "cm")),
    axis.title.y = element_blank(),
    axis.text = element_text(size = 10),
    legend.position = "none",
    panel.grid.major.y = element_blank(),
    )

The percentage of jobs where foundation skills (literacy, numeracy, ICT, and foreign languages) are highly crucial for doing the work is shown in this indicator. It is based on the findings of Cedefop's European survey of skills and jobs.

The Skills Foundation Indicator is exposed also in iscoCrosswalks as an example data-set. It consists of three variables

• Occupations
• Skill
• Value

To perform the transformation, we've added a third column with the preferredLabel from the ISCO taxonomy. In the R terminal, type isco to access the desired labels. Manual entry of preferred labels is suggested for small data. See also the R package labourR for automating the occupations coding, in case of big data-sets.

Inspecting the indicator,

knitr::kable(foundation_skills[seq(1 , nrow(foundation_skills), by = 5), ])

To translate the indicator to SOC classification, iscoCrosswalks has two mandatory column names. Namely, job and value standing for the preferred labels of the taxonomy and the value of the indicator respectively.

Thus, we rename preferredLabel to job, and Value to value.

data.table::setnames(foundation_skills,
                     c("preferredLabel", "Value"),
                     c("job", "value"))

The isco_soc_crosswalk() function can translate the values to the desired taxonomy. The parameter brkd_cols accepts a vector that indicates other columns used for grouping.

Also, since this is a composite score we set indicator = TRUE to use mean value. Instead, if raw counts are given then we set indicator = FALSE to aggregate the units of the hierarchy.

soc_foundation_skills <- isco_soc_crosswalk(foundation_skills,
                                            brkd_cols = "Skill",
                                            isco_lvl = 1,
                                            soc_lvl = "soc_1",
                                            indicator = TRUE)

In the following we visualize the top 6 occupations by Skill, of the projected indicator to the SOC taxonomy.

library(ggplot2)
library(data.table)
soc_foundation_skills[, Occupations := gsub(" Occupations", "", soc_label)]
soc_foundation_skills[, Skill := gsub(" skills", "", Skill)]
dat <- soc_foundation_skills[order(Skill, -value)][, head(.SD, 6), by = "Skill"]
ggplot(dat, aes(x = Occupations, y = value, fill = Skill)) +
  geom_col(alpha = 0.8, width = 0.85) +
  scale_fill_brewer(palette = "Dark2") +
  scale_y_continuous(expand = c(0, 0.1)) +
  coord_flip() +
  facet_grid(rows = vars(Skill), scales = "free_y", switch = "y", space = "free_y") +
  labs(
    title = "Which foundation skills are very important for jobs?",
    subtitle = "Highest level needed for doing their job - SOC 2010",
    caption = "Source: Cedefop's European skills and jobs survey transformed with iscoCrosswalks",
    y = "% of jobs for which foundation skills are important"
  ) +
  theme_minimal(base_family = "Roboto Condensed") +
  theme(
    plot.margin = margin(0.5, 0.5, 0.5, 0.5, unit = "cm"),
    plot.title = element_text(size = 15, face = "bold"),
    strip.text.y = element_text(angle = 270, face = "bold"),
    strip.placement = "outside",
    axis.title.x = element_text(margin = margin(t = 0.5, b = 0.5, unit = "cm")),
    axis.title.y = element_blank(),
    axis.text = element_text(size = 10),
    legend.position = "none",
    panel.grid.major.y = element_blank(),
    )

If the reverse process is required, use the soc_isco_crosswalk() function. The preffered labels of the taxonomy can be inspected in the included dataset soc_groups.

eworx-org/iscoCrosswalks documentation built on May 24, 2022, 2:31 a.m.