1. Measuring the very long, fuzzy tail in the occupational distribution
InGRID workshop New skills new jobs: Tools for harmonising the measurement of occupations
Amsterdam 11 February 2014
Kea Tijdens

2. What is the very long tail?
Distribution NL labour force over 193 occupational groups (3 digit level ISCO-08, CBS Statline)

3. Two ways of measuring occupations in surveys
Open-ended question
‘What is your occupation?’ is typically asked in an open-ended survey question with office-recoding
because in a country the stock of job titles may exceed 100,000 and the occupational distribution has a very long tail
Closed survey question
presenting items (occupations, job titles) for self-identification:
a limited list of items (e.g. in PAPI)
a search tree with many items (only CAPI or CAWI)
semantic matching using a lookup database with very many items
no list/database will cover all possible responses, because the number of possible items is not known
provides respondent a hint what kind of answer the survey is looking for (> no responses at various levels of aggregation)
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4. Research objective Objectives What percentage of respondents
can identify their occupation via a search tree?
uses the text box?
Once using the text box, what percentage
could have identified their occupation in the search tree?
which occupations are absent in the search tree?
To what extent should the search tree’s database include the long tail occupations > what is the optimum size of a database?
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5. Data and methods Data from LISS panel …
The LISS (Longitudinal Internet Studies for the Social Sciences) panel is administered by CentERdata (Tilburg University)
The LISS panel is a probability-based online panel
For our project, LISS panel repeated in Oct-2009 the WageIndicator web survey on work and wages, selection workers in paid employment (n = 3444)
Occupation question with search tree
Used 3-step search tree for question ‘What is your occupation?’
step 1: 23 entries, for example ‘Guards, army, police’
step 2: 207 entries
step 3: approx. 1,700 occupational titles, all coded ISCO-08
Each 3rd level list allowed to tick ‘other’, followed by a text box
Note: search tree hierarchy does not follow ISCO hierarchy > designed for classification, not for self-identification
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6. About the search tree WageIndicator web survey WageIndicator websites
WageIndicator web survey on work and wages (start in NL in 2001) =>> continuous, volunteer survey posted on all WageIndicator websites, currently in 75 countries
Web survey uses search tree for self-identification of occupation, because the alternative (open question) requires office coding =>> too expensive & too time demanding
Database adapted to ISCO-08 in EurOccupations project (‘07-09)
WageIndicator websites
WageIndicator websites publish information about wages, labour law and career, attracting large numbers of visitors (20 mln 2012)
Survey data used for the websites’ Salary Check, providing wage estimates per occupation (group of occs)
Salary Check uses the same search tree as in web survey
WageIndicator receives irregular s of visitors: ‘why is my occupation not included?’ (recently for UK: ‘estates manager’)

7. Use of the text box What percentage of LISS respondents
can identify their occupation via a search tree?
uses the text box?
Once using the text box, what percentage
could have identified their occupation in the search tree?
Initial
3444
100%
Drop out 18 1%
Identified occ in 3rd step
2313
67%
Ticked other
1113
32%
… of which could have identified occ
497
14%
… of which occ was absent in search tree
600
17%
… of which unidentifiable text 16

8. The long tail in the search tree
2313 respondents who ticked an occupation in the search tree,
in total 584 occupations from the 1,700 titles

9. The long tail
600 respondents who ticked ‘other’ and whose job title could not be coded into the database, together 479 occupational titles

10. Conclusion A search tree and the very long fuzzy list of occupations …
the current search tree reduces the coding load with 2/3
the remaining 479 uncoded occupational titles challenges to increase the database to almost 2,300 titles
among these 479 some are too aggregated titles and need specification, e.g. project leader
a joint search tree + semantic matching becomes a condition for using self-identification with a search tree in a survey
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11. The end Thank you for your attention! Comments invited
For more information
21 November 2019