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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
    • ISCO68 to ISCO88
    • ISCO68 to ISCO08
    • ISCO68 to SIOPS
    • ISCO68 to ISEI
    • ISCO68 to EGP11/EGP7/EGP5/EGP3
    • ISCO68 to EGP11-MP
  • ISCO88
    • ISCO88 to ISEI
    • ISCO88 to SIOPS
    • ISCO88 to IPICS
    • ISCO88 to MPS88
    • ISCO88 to EGP11/EGP7/EGP5
    • ISCO88 to EGP11-MP
    • ISCO88 to OESCH16/OESCH8/OESCH5
    • ISCO88 to ISCO88COM
    • ISCO88 to ISCO08
    • ISCO88 to ISCO68
    • ISCO88 to ORDC
    • ISCO88COM to ESEC - ISCO88COM must be 3 digits
    • ISCO88COM to ESEC-MP - ISCO88COM must be 3 digits
    • ISCO88COM to MSEC - ISCO88COM must be 3 digits
    • ISCO88COM to WRIGHT
  • ISCO08
    • ISCO08 to ISCO88
    • ISCO08 to ISEI
    • ISCO08 to SIOPS
    • ISCO08 to Microclasses
    • ISCO08 to IPICS
    • ISCO08 to OESCH16/OESCH8/OESCH5
    • ISCO08 to ESEC - ISCO08 must be 3 digits
    • ISCO08 to ESEC - ISCO08 must be 2 digits
    • ISCO08 to ESEC-MP - ISCO08 must be 3 digits
    • ISCO08 to MSEC - ISCO08 must be 3 digits
    • ISCO08 to ESEG - ISCO08 must be 2 digits
  • ESCO
    • ESCO to ISCO08
  • Extras
    • Translation between major/submajor/minor/unit groups for ISCO68, ISCO88 and ISCO08
    • Repair ISCO variables

Installation

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

# install.packages("devtools")
devtools::install_git("https://code.europa.eu/digclass/digclass.git")

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