The future of theory: should social protection board the big data train?

Cedric Waterschoot

No hmuva, SocArXiv from Center for Open Science

Abstract: Applications of big data have been surging as of late, and the field of public policy does not stand on the sideline while this dramatic wave of new technologies makes its way across the disciplines. However, theory-driven fields may experience radical change, as data fundamentalists claim the end of theory will come due to the nature and practicality of big data. In this paper, the position of social protection is examined with regard to the effects of the already observed shift towards such computational methods. I argue that such dramatic end of theory will not come for social protection policy, as the specialists and theorists take up the role of interpreter of data, performing the needed task of translating the vast collection of information into a useable collection or result. Vital in this position is the contact with the political economy, a task impossible to result in fruitful outcome without the interpreter. To strengthen this position in regard to social protection and big data, two examples are outlined: ‘Citizen Based Analytics’ in New-Zealand and the Big Data Quality Task Team of the UNECE.

Date: 2020-10-19
New Economics Papers: this item is included in nep-big and nep-hme
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://osf.io/download/5f8d459137b6bb0346307542/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:hmuva

DOI: 10.31219/osf.io/hmuva

Access Statistics for this paper

More papers in SocArXiv from Center for Open Science
Bibliographic data for series maintained by OSF ().