###Mia Ridge, Citizen History and its Discontents, IHR Digital History Seminar, 18 November 2014
Live notes, so an incomplete, partial record of what actually happened.
Tags: dhist
Stream/video: https://www.youtube.com/watch?v=epIaXcBrFhI
My asides in []
[8 on the live stream]
Citizen history often becomes crowdsourcing.
Motivation: intrinsic, personal, behind the scenes access, close encounters with material.
But basically, transforms input content into output content.
Citizen Science often indistinguishable from crowdsourcing (processing) but sometimes data analysis and design taking place.
Participatory model closer to citizen science/history - deeper change to practice more skills.
Long practice of course of advocational history (prefer that to 'amateur'...)
Database design embedded in OU and Oxford distance learning courses on local history.
Communities of practice: social learning system with knowledge acquired through participation - observing historians through as they do what they do key to learning for citizen historians [does that mean we are doing undergraduate teaching wrong?]
Discussion online only part of the discussion that happens...
Who is not represented in online communities? Those without the time to contribute but with the time to read, observe, consume.
Examples...
FreeBMD started in 1998. Free indexes of births, death, marriages - grassroots project, official involvement at their behest http://www.freebmd.org.uk/ (citzen history, not crowdsourcing)
OldWeather (crowdsourcing that became citizen history) - nice example of curiosity generated by interaction with digitised sources - forums as place where projects go beyond the scope, where guides created - people discovering or rediscovering interest in history. Hard to replicate.
<script async src="//platform.twitter.com/widgets.js" charset="utf-8"></script>#dhist @mia_out on the distinction between citizen history and simple crowdsourcing: projects are contributory, collaborative or co-creative
— Peter Webster (@pj_webster) November 18, 2014
Operation War Diary - actively uses the term citizen history, but some queries not being picked up - speaks to the absence of experts to pick up the question - project wants to generate data for academic, but no framework for support, no allocated resources, no expert voices, so what can we make of that data? - and when support there they are labelled as 'historian' - what does that means for the other participants?
Children of the Lodz Ghetto (Holocaust Museum) - explicitly citizen history - what happens if we trust the public with tasks of the museum? - type what you see, help undertake research tasks, often with multi-lingual archives, I think this person here is the same as this person there - scaffolded small task workflow - trying to get people to move from a question, to a datapoint, to a narrative - and checking for accuracy... (sensitive issue) so people are challenged to reflect on their process - great project, but very resource intensive
Conclusions...
Access powerful. Online space for discussions important. Expert input transformational - but expertise do not need to be academic. Absent expert though problematic.
Zooniverse - serendipitous discoveries identified in the early stages are probably still happening, but the experts perhaps aren't there to see them...
Who sets the rules is very important.
Many organisation still more comfortable with broadcast the dialogue. Challenges of shared authority aren't for everyone.
<script async src="//platform.twitter.com/widgets.js" charset="utf-8"></script>#dhist my take-home so far is the more resource the institution commits to these projects, the better the result. Not simply a cheap option
— Peter Webster (@pj_webster) November 18, 2014
Structural issues around over-promising expectation.
<script async src="//platform.twitter.com/widgets.js" charset="utf-8"></script>#dhist five competing models of citizen history project from @mia_out http://t.co/NxU1Y5VgwF (slide 25)
— Peter Webster (@pj_webster) November 18, 2014
Tension between desire for productivity and creating communities of practice - especially for organisations that can't fund digitisation but can fund crowdsourcing.
[Tension here between more than just access to resources being clearly exciting to budding citizen historians/scientists and that for institutions, the data generation, the crowdsourcing is often key - citizen history, engagement, nice by-product... But then you need the citizen history to get the crowdsourcing... I'm also wondering how exciting that data created is to the folks that make it, given emphasis on access to data these days...]
Calling people who transcribe citizen historians as the effect of flattening the expertise of the historian, and undermines the work of 'genuine' citizen historians.
Striking that term citizen historian invoked when institutions need something... But then perhaps does attract those who wouldn't be a volunteer. In sum, labels are important.
Q: attempts to measure impact of citizen science projects
Honesty around failure perhaps lacking.
Q: opportunities to meet in person important for some, how much do projects consider that?
Value in in-person meeting clear, but tough. Some exploring value of self-organising.
Q: around always needing to be aware of those who are not represented, how far to projects try and seek them out?
Forums for general chit-chat often embedded in projects. Welcoming new posters with intro threads. Or can email offline, as some don't like making mistakes in public.
Q: crowdsourcing as a term not sexy enough to get funding now... change... do things always have to change?
Story of source material more important than the method for getting people, and the impact of the project
Q: how much to these communities care about using the data that they make?
They do!
Q: Marine Lives - use of social media and the role of that in drawing in experts, different communities
Static URLs without paywalls are so important.
Q: what is the future?
More sophisticated conversations with funders.
Q: ethics of taking jobs from the transcribers?
The alternative is that things don't get digitised. Machines are taking jobs. But perhaps people don't notice until their job is taken.
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