Wednesday, February 25, 2009
Apprenticeships: an economic history
Contemporary art and design practices - even if now taught in art and design departments in modern universities - bear some relation to the institutions of apprenticeships that developed over hundreds of years in several European countries. A seminar at Said last week raised some interesting questions about what we think we know, and what we actually know, about such apprenticeships. Tim Leunig of LSE, an economic historian, gave a wonderful seminar for the Centre for Corporate Reputation drawing on his work into apprentices in London in the pre-modern period. Given access to a huge set of data (produced a man whose job allowed him time to input vast amounts of data from historical records) about 161,000 London apprentices between 1420-1930, Leunig and colleagues found out some interesting things which challenged their - and my - assumptions about how people were trained in pre-industrial societies in England.
Looking specifically at records from 1600-1750 from 760 London companies (eg vintners, grocers) whose members were masters offering seven-year apprenticeships, Leunig and colleagues found, to their surprise, that
- kinship relations and local connections were not important in how young men chose their masters in London;
- nor were their fathers' trades important in the decisions they made about what to become apprentices in; and
- nor did the distance of their village or town from London have that much of an impact either.
There remain questions about how these young men did make decisions about who to pick to be their masters and what information they had available. But this research suggests that these young men made choices that were not encumbered by things we associate with pre-modern societies - such as kinship and location. Like "modern" apprentices, they made other kinds of choices.
Being of an ethnographic orientation myself, I must confess I have never really "got" quantitative research before. But now I do! The way these scholars framed questions around the data set, crunched numbers to produce something meaningful, and then told a clear story about it was an inspiring piece of scholarship.