We’ve been working on a project (can’t say with whom) to mash together a whole bunch of the data we’ve been amassing (in terms of graduate destinations, careers resources, generic careers information) in the form of a webservice delivering facts and figures and suggestions about the jobs graduates in particular degrees do, the average wage, some of the employers and the best resources to start looking for information about those particular careers. It’s all wrapped up with a series of our articles on application forms, networking etc etc…
I’m very excited about it – the deadlines have been horrendous but we should have it out in the open later this month.
A lot of it draws on our careers resource Careers Tagged, which has turned out to have a way too complicated user interface (though a lot of people feed back that they still find it very useful) but the data and tagging engine for which is driving a lot of our current projects, including this one and our new Job Online, which uses Careers Tagged. Careers Tagged’s engine looks at a job selected by a user and suggests other relevant vacancies, along with a set of online resources to find out more about the background to a particular sector. The tagging behind it is crowd-sourced but from a very select crowd – the careers information offices and advisers who work for us. So the relevancy of the hits is surprisingly high. Not so much crowd-sourcing, perhaps, as tribe-sourcing, to loosely adapt a concept from the Tuttle peeps.
The trouble with crowd-sourcing seems to me to lie in two areas – face-validity and subject expertise. Whilst there are a lot of great community driven resources for careers information (e.g. Wikijobs), a lot of the information is patchy or biased. Specialties tend to be under-represented, for example. So for Careers Tagged, we worked on the assumption that if we had enough careers information professionals involved, we’d be able to broadly cover covers period with a fair certainty that individual biases would be averaged out and that the information/resources highlighted would be of a consistently high standard. Tribe-sourcing, then, is using a group of loosely affiliated people to generate a product from their combined common interest – the assumption is that each person in the tribe either knows something about the subject or work area and has no ego about being corrected. If we ever manage to finish anything around these parts, it’s generally due to tribe sourcing.
Don’t get me wrong – I’m a great believer in the Wikipedia concept and users can already add their own tags to Careers Tagged if they want. But without that core tribe of contributors, we wouldn’t have anything.
There’s probably another post to be written about the relation of tribes to our organisational habits, good and bad, at some point, though any number of bloggers (e.g. Michael Bauwens at P2P, the inevitable Seth Godin, Joe McKendrick at FastForward) have written far more authoritatively on this.
Filed under: KM, experts, jobsites, mashups | Leave a Comment »