I’m here at the Citizen Cyberscience Summit for the next two days. Expect quite a few notes (although probably not all session!).
Lessons in crowdsourcing.
Nothing new under the sun. Science shaped by forces that have existed a long time, and we understand them. Works on calculation and making mathematical models work. That has long history as being citizen science, going back 200 years. Take large task, divide into small exchangeable jobs, send out into the world with instructions on how to do them. Charles Babbage wrote extensively about this in the 1830s.
Babbage was thinking about this because of his computing machine, how can you split big tasks up? Activity is largely about starting something, drive is towards radical organisation that moves towards convention, where you have people who lead, follow, varying levels of skill.
Babbage’s discussion, prime example he worked off, Gaspard DeProny, French Revolution, labour was very cheap. DeProny got 100 people to do maths tables, required for surveying.
~100 years later, 1875, post American Civil War, lots of people out of work, women who were widows, organised group of computers, i.e. women, who put together the Harvard Star Catalogue. Then again in 1907 by US Naval Obs.
And again in 1938 during the Great Depression – 450 people working at tables with paper and pencils doing calculations for scientists or government. Maths Tables Project.
A few people have adding machines, they are the leaders.
A NYC computing office, Columbia Uni Stats Computing Lab, 1930, had 6 employees.
Most of the Maths tables computers hadn’t been to high school, organised by arithmetic opersations e.g. – or +.
Often drew from poor classes at that time: blacks, women, Irish, Jews.
Planners had a doctorate or masters, operated 1938 – 1948, remnants existed til 1964.
Most scientists/engineers didn’t have access to computers until mid-60s when they had timeshare. Some not until the 70s. They worked with a worksheet, that was planned, a bit like programming. Early programmers were called planners, coding was called planning. Instructions, so workers didn’t need to understand what they were doing.
Built 28 volumes of tables, e.g. powers of integers, exponential functions.
Discovered there were particular skills, and started to look for specific calculations that were good for generating revenue, e.g. OSRD calcs, microwave radar tables, explosion calcs; LORAN navigation tables (precursor of GPS); general science calcs, e.g. Hans Bethe paper on Sun. First test of linear programming.
Labour economics. As you build skills, people want to use their skills and want to be rewarded for that skills. They want to advance. WPA studied labour and skill as a way of building identity.
Aspirational issues: Everyone wanted to be special.
Special Computing Group, had a room to themselves, had machines, almost all were women, and everyone wanted to move up to the special computing group. They started offering courses at lunch to develop those skills. Once they had completed that, were were opportunities outside. So lots of places they could apply those skills. Best measure of ability was the skill of the group.
They recognised that losing members of the group, breaking it up would damage the organisation. Started to have difficulty getting work, so soliciting work from scientists.
Gertrude Blanch, PhD, chief mathematician. Ran the computing group. Had to take everyone who came in the door, had to find ways to enforce discipline, e.g. people who didn’t think about carrying the ten, or who couldn’t concentration. Calculations were done 3 – 10 times each, didn’t just duplicate for sake of it.
“People doing hand calculations computing the same number the same way make the same mistakes” – Babbage
So did same calculation in different ways to ensure accuracy.
Crucial issue: How do citizen scientists relate to professionals? Professionals build walls around themselves.
National Academies of Science said they wanted to be of use to the gov’t, and help scientific work. WPA sponsored a lot of science. Internal comms of Nat Academies are ’embarassing at best’. Group realised it was in a position it didn’t want to be in, and internal memos had one set of reasoning that repeats:
“Scientists are successful people. The poor, are not successful, because they are poor. Therefore can conclude that hte poor are not scientific. Ergo, maths tables project is not scientific, ergo their work is not good.”
NAS wanted the budget for the maths tables and wanted to do it “right” and ‘well”. But they could never have replicated it with students as budget wouldn’t cover it.
Handbook of Mathematical Functions: Largest selling science book in history.
Gertrude Blanch, finished PhD in 1934, was Jewish, was never going to be employed by anyone, but doing the maths tables project lead her to be employed by the Air Force, worked on supersonic air flow, jet nozzles.
The thing that we are doing is building skill amongst the general populous can never be overlooked.
Maths group had droped form 450 people to 120 as labour costs were higher. But claimed 120 was as efficient. by 1946, group had fallen to 60 people with specific skill, but still as efficient. People have titles, skills, identifiable expertise.
- We are creating skill, not just exploring the universe and doing science,
- Get people who want to be identified with project, part of their identity.
- Builds org with hierarchy, divisions of labour based on skill
- Encourage aspiration
DeProny users Adam Smith as justification, first 2 ch of Wealth of Nation, division of labour, identifying people with skill. Forces that shape these orgs and relationships that will support science, there is also a political economy that shapes it. which builds skill but divides jobs, creates leaders and followers. Must deal with science self-defining as enclosed domain.