Work, Employment & Society

BSA_WES2018Just came back from the Work, Employment and Society (WES) conference 2018, that British Sociological Association (BSA) organizes every other year. Perhaps more intimate and newbie-friendly than the main BSA event, this year’s WES in Belfast was also a positive surprise in terms of its academic content. There were several sessions on the so-called ‘gig economy’ (or as one speaker put it, ‘gig economies‘), the effects of digital business models that often go under the name of ‘uberization’, and atypical forms of work.

Some lessons I am taking home:

  • A growing number of researchers are studying platform work – not just the most visible forms of it such as Uber drivers and Deliveroo couriers, but also those who are hidden at home: freelancers and to a lesser extent, micro-workers;
  • The question of how platform workers self-organize, and what can be done to improve their organization capacity, is attracting a lot of attention;
  • Efforts at establishing standards, fairness criteria and forms of social protection for atypical platform workers are gaining momentum;
  • There is a lot we can learn from research in neighboring areas: for example the distinction between employee-friendly and employer-friendly flexible work, initially developed for people in employment, is also helpful here.

What is still missing from the picture is information on the ‘long tail’ of smaller, often national rather than international, platforms, and on the workers (especially micro-workers) who use them. Besides, clients and requesters are little known – on all platforms. Estimating the size of the platform worker population remains an unresolved issue – whether at local, national or international level. A common grievance by researchers is difficulty to access crucial data from commercial platforms that use them as their private property.

Data and theory: substitutes or complements? Lessons from history of economics

EEToday, my chapter on “Formalization and mathematical modelling” is published in a new series of three reference books on History of Economic Analysis (edited by G. Faccarello and H. Kurz, Edward Elgar). The chapter draws heavily on key ideas I developed as part of my thesis on the origins of mathematical economics. But this was a long time ago and reading it again today, I see it in a different light. I notice in particular that economics developed its distinctive mathematical flavour, which makes it neatly stand out relative to the other social sciences, at times in which social research was data-poor – and it did so not despite data paucity, but precisely because of it. William S. Jevons, a 19th-century forefather of the discipline who was clearly aware of the relevance of maths, wrote in 1871:

“The data are almost wholly deficient for the complete solution of any one problem”


“we have mathematical theory without the data requisite for precise calculation”

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