IDEAS home Printed from https://ideas.repec.org/a/spr/astaws/v12y2018i3d10.1007_s11943-018-0231-2.html
   My bibliography  Save this article

Eine Hilfsklassifikation mit Tätigkeitsbeschreibungen für Zwecke der Berufskodierung
[An auxiliary classification with work activity descriptions for occupation coding]

Author

Listed:
  • Malte Schierholz

    (Institut für Arbeitsmarkt- und Berufsforschung (IAB)
    Universität Mannheim)

Abstract

Zusammenfassung Berufsklassifikationen sind anhand der ausgeübten Tätigkeit gegliedert und entsprechend wird auch in Umfragen zur Erfassung des Berufs nach der „beruflichen Tätigkeit“ gefragt. Obwohl sich diese Abfrage auf die Klassifikation bezieht, wird bei der Kodierung von Antworten nur selten auf die tätigkeitsbezogenen Definitionen von Berufsklassifikationen zurückgegriffen. Stattdessen erfolgt die Kodierung meist indirekt, indem Kodierer Berufsbenennungen aus einem Kodier-Index auswählen. Da viele Berufsbenennungen aber unpräzise sind und nur unzureichend die ausgeübte berufliche Tätigkeit beschreiben, kann es dabei zu fehlerhaften Kodierungen kommen. Als alternative Vorgehensweise wird eine tätigkeitsorientierte Hilfsklassifikation zur Verwendung in computergestützten Vorschlagssystemen vorgestellt, die im Internet zum Download verfügbar ist. Dies unterstützt Kodierer, die passendste Tätigkeit ohne den Umweg über Berufsbenennungen auszuwählen. Die neue Hilfsklassifikation basiert auf der deutschen Klassifikation der Berufe 2010 und der Internationalen Standardklassifikation der Berufe 2008 und soll eine simultane Kodierung in beide Klassifikationen ermöglichen. Da zur Nutzung der Hilfsklassifikation Detailkenntnisse über die ausgeübte berufliche Tätigkeit des Befragten nötig sind, ist der größte Nutzen beim Einsatz während des Interviews zu erwarten, wenn Befragte die für sie passendste Tätigkeit selbst auswählen.

Suggested Citation

  • Malte Schierholz, 2018. "Eine Hilfsklassifikation mit Tätigkeitsbeschreibungen für Zwecke der Berufskodierung [An auxiliary classification with work activity descriptions for occupation coding]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 12(3), pages 285-298, December.
  • Handle: RePEc:spr:astaws:v:12:y:2018:i:3:d:10.1007_s11943-018-0231-2
    DOI: 10.1007/s11943-018-0231-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11943-018-0231-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11943-018-0231-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Schierholz, Malte, 2014. "Automating survey coding for occupation," FDZ Methodenreport 201410_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. repec:iab:iabfme:201410(en is not listed on IDEAS
    3. Peter Elias, 1997. "Occupational Classification (ISCO-88): Concepts, Methods, Reliability, Validity and Cross-National Comparability," OECD Labour Market and Social Policy Occasional Papers 20, OECD Publishing.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Schierholz, Malte & Gensicke, Miriam & Tschersich, Nikolai, 2016. "Occupation coding during the interview," IAB-Discussion Paper 201617, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    2. Tijdens Kea, 2014. "Dropout Rates and Response Times of an Occupation Search Tree in a Web Survey," Journal of Official Statistics, Sciendo, vol. 30(1), pages 23-43, March.
    3. Massing Natascha & Wasmer Martina & Wolf Christof & Zuell Cornelia, 2019. "How Standardized is Occupational Coding? A Comparison of Results from Different Coding Agencies in Germany," Journal of Official Statistics, Sciendo, vol. 35(1), pages 167-187, March.
    4. Malgorzata Mikucka, 2016. "How to Measure Employment Status and Occupation in Analyses of Survey Data? (Jak mierzyc status zatrudnienia i pozycjê zawodowa w analizach danych sondazowych?)," Problemy Zarzadzania, University of Warsaw, Faculty of Management, vol. 14(60), pages 40-60.
    5. Michael Fritsch & Michael Stützer, 2012. "The Geography of Creative People in Germany revisited," Jena Economics Research Papers 2012-065, Friedrich-Schiller-University Jena.
    6. Latorre, Maria C., 2014. "CGE analysis of the impact of foreign direct investment and tariff reform on female and male wages," Policy Research Working Paper Series 7073, The World Bank.
    7. Kässi, Otto & Lehdonvirta, Vili, 2018. "Online labour index: Measuring the online gig economy for policy and research," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 241-248.
    8. Gweon Hyukjun & Schonlau Matthias & Kaczmirek Lars & Blohm Michael & Steiner Stefan, 2017. "Three Methods for Occupation Coding Based on Statistical Learning," Journal of Official Statistics, Sciendo, vol. 33(1), pages 101-122, March.
    9. Necker, Sarah & Voskort, Andrea, 2014. "Intergenerational transmission of risk attitudes – A revealed preference approach," European Economic Review, Elsevier, vol. 65(C), pages 66-89.
    10. Rafael Muñoz de Bustillo & Enrique Fernández-Macías & José-Ignacio Antón & Fernando Esteve, 2011. "Measuring More than Money," Books, Edward Elgar Publishing, number 14072.
    11. Ikudo, Akina & Lane, Julia & Staudt, Joseph & Weinberg, Bruce A., 2018. "Occupational Classifications: A Machine Learning Approach," IZA Discussion Papers 11738, Institute of Labor Economics (IZA).
    12. Latorre, María C., 2016. "A CGE Analysis of the Impact of Foreign Direct Investment and Tariff Reform on Female and Male Workers in Tanzania," World Development, Elsevier, vol. 77(C), pages 346-366.
    13. Fauser, Margit & Liebau, Elisabeth & Voigtländer, Sven & Tuncer, Hidayet & Faist, Thomas & Razum, Oliver, 2015. "Measuring Transnationality of Immigrants in Germany: Prevalence and Relationship with Social Inequalities," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 38(9), pages 1497-1519.
    14. Leuze, Kathrin, 2010. "Smooth Path or Long and Winding Road? How Institutions Shape the Transition from Higher Education to Work," EconStor Books, ZBW - Leibniz Information Centre for Economics, number 251573, June.
    15. Han, Seong Won, 2016. "National education systems and gender gaps in STEM occupational expectations," International Journal of Educational Development, Elsevier, vol. 49(C), pages 175-187.
    16. Fritsch, Michael & Stuetzer, Michael, 2008. "The Geography of Creative People in Germany," MPRA Paper 21965, University Library of Munich, Germany.
    17. Wunder, Christoph & Schwarze, Johannes, 2006. "Income Inequality and Job Satisfaction of Full-Time Employees in Germany," IZA Discussion Papers 2084, Institute of Labor Economics (IZA).
    18. L. Cattani & K. Purcell & P. Elias, 2014. "SOC(HE)-Italy: a classification for graduate occupations," Working Papers wp963, Dipartimento Scienze Economiche, Universita' di Bologna.
    19. Roger Penn & Paul Lambert, 2001. "SOR Models and Ethnicity Data in LIS and LES: Country by Country Report," LIS Working papers 260, LIS Cross-National Data Center in Luxembourg.
    20. Kea Tijdens & Brian Fabo, 2014. "Using Web Data to Measure the Demand for Skills," Discussion Papers 21, Central European Labour Studies Institute (CELSI).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:astaws:v:12:y:2018:i:3:d:10.1007_s11943-018-0231-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.