The Longest Now

Joseph Reagle is a Wikipedian and a researcher of social collaboration.  He was an early fellow at the Berkman Center before I got involved there, worked on some interesting W3C projects, and joined NYU’s Department of Media, Culture, and Communication where he studied collaboration and Wikipedia.  He turned some of his PhD work into a book on Wikipedia culture, which was just published this month.

“Good Faith Collaboration: The Culture of Wikipedia” is an excellent read, suited for both my mother and for the armchair sociology buff.  Having seen some of the detailed research that went into it, I was pleased to find it organizes that into clear narrative facets, each illuminating part of the whole, without creating artificial story arcs.

The book is careful with its use of language and terminology, self-conscious of when it is sharing a widely understood phrase and when it is creating one that it needs for clarity.  It includes a comprehensive look at Wikipedian writings and coming-of-age debates during the heady period from 2004 to 2006, when much of the texture of current community structures was being formed.  The writing is poetic at times, and I particularly appreciate its comparisons to similar projects across two millennia (we have indeed been collating and collaborating for a long time)

This is also the first extended research into Wikipedian culture to strike what I feel is a carefully-sourced (60 pages of endnotes!) and neutral perspective, giving it a certain… idempotence.  In the tradition of early philosophical wikis, Wikipedia has long hosted a great deal of its own commentary on and analysis of itself and its community, and these existing analyses are given apprporiate historical prominence.  Good Faith Collaboration builds on these on-wiki conversations to offer a balanced look at decision-making within the community, describing the varied and sometimes conflicting views held by groups within the community.

Kudos to Joseph for this work, which I suspect will become a launching point for future community analyses.

There is much more that could be accomplished with the open ten-year history of Wikipedia across its many languages, subprojects, and variants!   One natural expansion (both for Wikipedia and for other long-lived transparent communities) would be to repeat a certain community analysis at regular intervals along a timeline.  We can observe and classify cultural change with a precision and a visualization of propagating memes that would be impossible in more opaque communities (dominated by invisible communication).  This was more true a few years ago than it is today — in the past year many significant documents or ideas were drafted in private, and perhaps not versioned at all, and many conversations left unarchived.  If we are to continue to make this sort of learning and analysis available for future generations, we may need to refocus our energies on public and transparent communication channels.

The Rice University administration seems to be having a very bad summer. A few weeks ago, they secretly planned the sale of KTRU, their nationally-renowned independent campus radio station. They ‘managed to keep their ongoing negotiations completely quiet until about 12 hours before the sale was approved by Houston’s Board of Trustees’. I didn’t realize until today that the sale was considered final — students have been protesting since it became public, and the administration has offered no explanation.

Now last week they leaked the news hinting they would shutting down their promising digital Rice University Press contradicting the will of RUP’s Board of Directors. This, after commissioning an external review that recommended supporting it and integrating it better into the Library and related services — and again, with no public explanation.

I have fond memories of Rice University — I studied there during high school; they supported Connexions in its infancy; friends of mine teach there. (I try not to hold the whole Sidis incident against them.) So it pains me deeply to see this wanton self-destruction. I can’t imagine what they stand to gain from either move — they will lose any money from the sale to discontented KTRU alumni from the radio’s 40-year history. (No one seems willing to support that sale — here is a petition from 350 concerned UH alumni in support of keeping the radio station at Rice.) What gives?

Checking out what Tumblr does right and wrong: I posted a short series of meditations on joy, sharing and knowledge. Let me know what you think.

UPDATED: with details from the German Currywurst Museum.

This Might Be Great. Presidentially great (also an MRE or escargot substitute).

Eugene comments on the similarity to Fleischbutter — and he is spot on.  The meatwater movement has had some of its greatest popularity  in Berlin, at the Currywurst Museum: (there’s more after the break)

Liquid Currywurst on display at the Deutsches Currywurst Museum

While still recovering from a Rein’s Deli hangover, I found myself the subject of the Ragesoss lens last weekend.   Good energy, well captured.

@Ragesoss: It is a mathematical notion applied to ideas. A conceptual space around a theme is full of different concepts, each related to the theme in some way. Such a space can be described in terms of facets that can be used to describe a concept: for instance, you might describe ideas for laying out a garden in terms of their complexity, suitable climate, or total size… or many others. Complexity and size are sometimes linked. You can imagine the conceptual span of a set of facets, or their dependency on one another, as corrolaries of the span and independence of vectors being used as the basis for an abstract space.

A mesh is a limited set of elements that can be used to effectively describe an infinite space of ideas.  Human languages are full of concept meshes.  The easiest to discuss are one-dimensional meshes (ideas that span the spectrum of a single facet):

• color words – the spectrum of visible colors is split into a set of common colors.  this set of names is a casual mesh for the visible color spectrum. (casual in that there is no explicit metric used to determine whether all parts of the visible spectrum are ‘equally’ represented by words)
• shape words – shapes may be described as circular or oval, square or rectangular.  There is a humorous ‘proof’ that the only skew triangle has angles (45, 60, 75) – that all others are roughly equilateral, isoceles, or right.

Higher-dimensional meshes include texture words (smooth, rough, bumpy, prickly, soft, firm, sticky… – covering facets of friction, give, tangible local structure, and more).  Most higher-dimensional meshes in language are incomplete (we rarely form words for concepts whose realizations are not in common use).

If you define a metric for the distance between two points on a spectrum, you can construct an “equally-spaced” subdivision of the space, or a balanced mesh.  This splits a space into a set of characteristic elements (here, concepts) or nodes which can be used to describe anything elsewhere in the space.

Choosing a metric is important and difficult.   For instance, once we found a way to measure color by the wavelength of its light, we could ask for enough common color words such that every frequency of visible light is no more than 50nm from the wavelength of one of the characteristic colors.  In practice, humans see different parts of the color spectrum with differing degrees of sensitivity, and we become familiar with certain constant colors in our environment .  So while the rendered spectrum does not devote much space to Yellow or Orange (in contrast with green and red), we have many more characteristic words for yellows and blues than a straight “wavelength subdivision” would suggest.

It is also difficult to define facets that are independent of one another; but this is not necessary.  It is mainly important for each facet to be easy to observe and agree on.

For a given metric, you can describe the fineness of a mesh in terms of the maximum distance from any concept to the closest characteristic element.  (or sometimes twice that distance – as a description of the “largest” concept that could “slip through” the mesh without including any of the characteristic elements.)  If you have different metrics for each facet, a synthetic combined metric must be created that is consistent with each.

A balanced mesh is then one in which the fineness of the mesh is essentially the same for all subsets of the conceptual space — so, a set of color words that provides equal facility in describing perceived colors at all points on the color spectrum.   (Again, a suitable metric here might be one that stretches out the spectrum in regions perceived very well by the human eye, or colors that come up frequently in human life — the latter a metric that changes with social context.)

One can often have a clear definition of a mesh without having words for some of its characteristic elements.   This happens often with a multifaceted space, where the intersection of well-known values of each facet is an unknown combination that has no word to describe it.   One common way of constructing a balanced mesh involves creating a balanced mesh for each facet, and then defining a concept for every combination of those single-facet ideas.  Building a “complete” set of characteristic concepts can be thought of as mesh completion.  It is a way of thoroughly grokking a space of related concepts.  And the fineness of the resulting mesh is a measure of how effectively one has used language, imagery, or other methods to illustrate the limitless variety possible within the constraints of that conceptual space.

(More after the jump…) (more…)