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Apologies to my seminar colleagues for my absence today. I've been hanging with some digital humanists lately, and they told me last-minute about this conference on public history. So I hopped into the car and made my way down to Baltimore last night, to learn about the ins and outs of digital exhibits. I'm hoping to launch a digital exhibition project with my students this semester to explore a geneaology of zombie discourses. Again, my apologies. - Jamie

In our interview with Matt, now tragically lost to the vagaries of technological interfaces, Matt talked about his ambition to host a conference on negative results in robotics, in which attendees would be expected to share videos of robots not doing what they're meant to do.

I have his keynote speaker ready to go. https://www.youtube.com/channel/UC3KEoMzNz8eYnwBC34RaKCQ

Andy, Tim, and Matt think this guy is cool: https://bl.ocks.org/mbostock

Notes

Cronin, "Collaboration in Art and in Science"

Attribution, authorship, acknowledgement

Romantic individualism again: I almost want to put in a good word for it. What does romantic ideology do for us/with us/to us independent of the ways in which it is an important part of our labor systems or commodity value? Surely we find it emotionally rewarding in some fashion at times, quite aside from how it secures us a job or professional success (or denies that to us).

Collaboration seems a poor word for something like an atelier system or a system of coproduction with clear hierarchies embedded in it. It may feel just or good to try and claim that the entire system of coproduction has created or authored a work, but this is also brutally deprofessionalizing and I think dispiriting. Acknowledging hired hands is good, but failing to see the heterogeneity of roles in an assembly or coproduction strikes me as more ideological than descriptive. I suspect that if we were quick to proclaim a commons in every research project and artwork, we would create something like the flight of the upper middle-class from the public sphere, those who could escape a commons would escape it. Though this points to the incentive systems.

Linked to Lassiter on collaborative ethnography

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Bonilla, "Nature of Co-Authorship: Note on Recognition Sharing and Scientific
Argumentation"


Collaboration doesn't equal co-authorship; why do scientists instead of keeping them separate. Argues that this is because of the rhetoric of science.

This reminds me very much of the argument in Lamont, How Professors Think, of the sources of epistemological alignment and that the social forms and practices of those disciplines are pushed to mirror some of the epistemological (even ontological) premises of the discipline. If the discipline imagines itself to be highly aligned in those terms, there is a rhetorical need to perform that alignment. This might imply that the humanities is almost intrinsically driven to perform something like romantic individuality.

We are starting to see two meta-types of collaboration. The collaboration of "unsettlement" that looks for collaborators to antagonistically engage, to bring very different kinds of fundamental insights/ideals/goals/sensibilities into an assembly so as to bring the final result to something unexpected or interesting; the collaboration of alignment, that looks to multiply the capacities of individuals by aligning them in parallel within a very large project whose nature is considered to be intrinsically or ontologically prior to the decision to collaboration. In the first case, if the unsettled collaborators don't get together, then some interesting work that would not have otherwise existed comes into existence; in the second case, if the aligned collaborators don't get together, a problem which already exists doesn't get solved or understood.

Interesting example of this that touches on the author's modeling of authorship. In my field, people may be reluctant in some sense to use another person's ethnographic fieldnotes or interview transcripts, because there' s a sense that one own authority over the subject is tied up in the phenomenology of having been part of the making of those notes. The scientific authorship that Bonilla is describing is the opposite: the recognition is assured through the citation of other authors papers, as collective claim.

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Lander talk

Praising basic research seems like the main point?

But maybe what I was getting at with the cite to Benkler: do attribution problems change or go away in relationship to basic research? If we publish basic research, aren't we collaborating with many many people futureward in a way that will almost inevitably be uncredited? The idea of a commons or a public is key here too.

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Wolfers, "When Teamwork Doesn't Work For Women"

Ok, so this is a big thing to talk about. On one hand, it seems like the sort of thing that a formal rule-based approach to credit in relationship to a formal style of attribution would or should resolve, but on the other hand, if it is deeply embedded into cognitive-level perspectives, then what?

For example, you could get a better co-authoring formalism and find it doesn't economists from saying, Ok, but this article by a man actually did this thing first, so the female economist's work (co-authored or not) doesn't count.

actually seen that in history

about who is regarded as an originator or starting point of a particular argument or idea, and thus whose work can be discounted or undercounted.

But is the problem counting? Credit itself? Using produced works as a metric of labor accomplished?

Lots to talk about here.


Assessing Interpersonal Skills

Curious about neuroatypicality here.

Also curious about whether there are collaboration architectures that reduce the need for such interpersonal skills; what kills collaobrations. Connect to the Wolfers: aren't these dominance/power skills? I'm thinking about the brutal fights over who created Twitter or Apple computers

the collaborators who move to monetize or own, but Wozniak definitely needed Jobs too, without him it wouldn' t have gone anywhere.

A quick thought on Black Mountain, Cadava, and others:

I'm beginning to think that some of our readings push hard on the kind of open forms of "equity" that often organize faculty life at Swarthmore. E.g., most of the best collaborations or imaginations of collaboration in the humanities we've read about presuppose some process that collects only people with productive affinities with one another--differences in outlook, sure (the source of being 'unsettled') but not wide-open or random.

Week 2: On Understanding Our Research Identities

Matt and Josh did a great job walking me through Josh's research. I wanted to share the notes I wrote about Josh's research while reading one of his published articles and compare them to what I understand after the conversation.

Here's the notes, written the morning before the Week 2 meeting:


Notes on Joshua Brody et al, “Property Testing Lower Bounds Via Communication Complexity”, Computational Complexity 21:2012

“Communication complexity” seems very key to Josh’s research as a whole. I wonder if there is a way for me to understand or grasp it as a concept via complex systems theory or other definitions of complexity that I’m a bit familiar with, or to otherwise understand what qualifies communication as complex in computation/information theory. Does seem as on p. 312 that various formalizations of complexity as a concrete definable (mathematical) characteristic or property are in play in Josh’s work.

“property testing”: from Wikipedia (https://en.wikipedia.org/wiki/Property_testing)
“In computer science, a property testing algorithm for a decision problem is an algorithm whose query complexity to its input is much smaller than the instance size of the problem. Typically property testing algorithms are used to decide if some mathematical object (such as a graph or a boolean function) has a "global" property, or is "far" from having this property, using only a small number of "local" queries to the object.
For example, the following promise problem admits an algorithm whose query complexity is independent of the instance size (for an arbitrary constant ε > 0):
"Given a graph G on n vertices, decide if G is bipartite, or G cannot be made bipartite even after removing an arbitrary subset of at most edges of G."
Property testing algorithms are important in the theory of probabilistically checkable proofs.”

What do I think I understand about property testing algorithms? Using small ‘local’ queries to determine a mathematical object is in fact “big”? Understanding what the "big" object is? Making the "big" object usable or tractable by just 'pinging' a few slices or selections of it? Is that a good translation?

“Communication complexity framework has been extensively studied”. This is an interesting moment in anybody’s scholarship—the identification of the space that the scholars are operating within that makes their work useful/original/important in relationship to the spaces or concepts that are well understood or thoroughly studied. “This approach turns out to be quite fruitful, both for proving new bounds and for giving simpler proofs of known bounds in property testing”. I should ask if there are other rivalrous approaches, or who has used the approach that Josh and his co-authors sketch here.

In terms of collaboration, how did this one come together? Is this because Josh proved Theorem 1.4 in his 2011 work?
Would be interested just in talking about how theorems in this kind of research iterate? Are there moments of sudden or unexpected intellectual disjunction? Big intuitive leaps? Or is the next task or job clearly iterable out of the last one accomplished?

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So compare to what I learned through conversation with Josh and Matt.

1. The prospect of the conversation was somewhat terrifying! Though thank god I at least understand accurately what a Boolean variable is. Perhaps more soberingly, I do not have an entirely clear grasp of what a function is, which is roughly like saying in a humanities context that I don't know what words and grammar and books are exactly.

2. But I am now way, way clearer on what Josh researches, how he researches it, what the relationship between his research is and other work in his field, on the process of his collaboration with other researchers, on the goals and ambitions of his research. One of the things I walk away from after Friday is thinking that for all that I believe that non-face-to-face information mappings of the work of our colleagues might produce a good kind of "continuous partial attention" to each other, there's really no substitute for the opportunity to ask questions in a dialogue, especially the kind of dialogue where it's ok to ask a mix of simple (even simple-minded) questions and more sophisticated ones.

Something I'd really like to read with the seminar in a future week: the Valve Employee Manual. Closely related in some ways to the Cadava interview and the Biagioli "projects instead of discipline" argument. http://www.valvesoftware.com/company/Valve_Handbook_LowRes.pdf

Personal notes from Tim Burke in preparation for first session, in response to the questions sent to us.

1 & 2: (how might what we read affect our approach to collaboration)
Black Mountain suggests value of isolation and the need for some prior alignment of sensibility. Reminds me that the bad thing about massively multiplayer-games might be that they push together too many strangers with too many incommensurable views about the purpose of their presence in the game, leading to lots of negative attempts to protect from unwanted collaboration.

Do R&D models in industry or elsewhere produce better results from research collaborations (re: Bozeman et al.) Might there be something that isn’t property-based but isn’t knowledge-based? Project-based? Output-based? Maker-based? Increments to expression? Increments to production? “Hyperauthorship” an interesting idea.

p. 18 Bozeman et al typologies of collaboration types is really fertile for discussion

The damage that the myth of the solitary genius does us! So bad! But it has such deep consequences that the Inge essay doesn’t even get to. Interesting paradox, though: the collaboration that was strongest when the myth of the solitary genius was strongest (editorial, etc.) is now most absent when the figure of collaborative authorship is most celebrated.



3: (thought experiment: what to do to answer these questions)

Find people with direct experience of some of the possibilities I’m imagining.

Would like to hear more from scientists about actual workflow of co-authoring; the things that aren’t spoken of to public view (etiquette, annoyances, etc.)


4. (What does the reading make you want to track down and read):

Scholarship on hyperauthorship; I want to read more about ghostwriting and other forms of ‘invisible collaboration’ but also the Stillinger book again. Can I get account of Inge and Stillinger impact on literary scholarship? Seems to me that this view has not changed much rhetorically? Or that we deal with collaboration by talking about systems, etc. (history of the book) rather than modes of literary/knowledge-making labor?



5. (other things reading could cite)
Still really interested in crowdsourcing, open-source, etc. models for collaboration, which are I think genuinely different than these examples in both impact and structure.

6. (How did you take notes?)

These are my notes! I wish they were better. I need to stabilize note taking practices, really. Collaborative note-taking would be an interesting thing to talk about--esp. how to keep it from being something more like 'minutes for a meeting'. Notetaking that meshes multiple styles of note-taking? That doesn't try to be an objective 'voice of the group' or a detached observer?

7. (Discussing these readings with students)

First question I would have for students is why most of them (legitimately I think) hate group projects/group work. That seems like a big thing for us to talk about--why collaboration seems like such a great idea (or an important skill) but often is unpleasant, burdensome or risky.