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DIGCLASS

The DIGCLASS R package aims to make translation between occupational social classes easy and comprehensive. It facilitates the translation of the International Standard Classification of Occupations (ISCO) from 1968, 1988 and 2008 to a wide range of social class schemes.

This package is a work in progress and has implemented currently these translations:

  • ISCO68
  • ISCO88
  • ISCO08
  • ESCO
  • Extras

Installation

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

# install.packages("devtools")
devtools::install_github("cimentadaj/DIGCLASS")

Example

Here’s an example of translating ISCO68 to ISEI and EGP class schemas:

library(DIGCLASS)
library(dplyr)

# Internal data for the European Social Survey round 6
# containing different ISCO variables
ess %>%
  transmute(
    isco68,
    isei = isco68_to_isei(isco68),
    egp = isco68_to_egp(isco68, self_employed, emplno),
    egp_labels = isco68_to_egp(isco68, self_employed, emplno, label = TRUE)
  )
#> # A tibble: 48,285 × 4
#>    isco68 isei  egp   egp_labels                            
#>    <chr>  <chr> <chr> <chr>                                 
#>  1 5890   35    6     'IVb: Self-employed with no employees'
#>  2 2120   67    2     'II: Lower Controllers'               
#>  3 7200   34    8     'VI: Skilled Worker'                  
#>  4 9310   32    8     'VI: Skilled Worker'                  
#>  5 6220   16    10    'VIIb: Farm Labor'                    
#>  6 6220   16    10    'VIIb: Farm Labor'                    
#>  7 9595   24    9     'VIIa: Unskilled Worker'              
#>  8 6000   46    11    'IVc: Self-employed Farmer'           
#>  9 6000   46    11    'IVc: Self-employed Farmer'           
#> 10 6220   16    10    'VIIb: Farm Labor'                    
#> # ℹ 48,275 more rows

The nomenclature of the function is {origin}_to_{destination} where origin is the origin class schema and destination is the destination class schema. The usual workflow is for you to type, for example isco and then hit TAB to get auto-completion on all possible translations.

For those class schemas that have labels, the label argument returns the labels instead of the class codes.

Steps to add a new translation

  1. Add two csv files respectively in data-raw/social_classes/labels/ and data-raw/social_classes/translation/ containing the labels and translation for the two schemas.

  2. Run the script data-raw/social_classes.R (with the root directory in data-raw/)

  3. Add a new function inside R/ with the convention {origin}_to_{destination}() where origin and destination are the class schemas we’re translating. Please have a look at other translation to recycle common functions to do translations.

  4. Add proper documentation to the function

Other R packages

This package has benefitted greatly from other open source packages that already pave the way for translation between social class schemas. In particular, we’ve learned a lot and borrowed code from all of these packages:

Funding

This project has been funded through the European Commission’s JRC Centre for Advanced Studies and the project Social Classes in the Digital Age (DIGCLASS): https://joint-research-centre.ec.europa.eu/tools-and-laboratories/centre-advanced-studies/digclass_en