Wednesday, January 09, 2013

Reading :: Networked

Networked: The New Social Operating System
By Lee Rainie and Barry Wellman

I have been meaning to review this book for a while—I probably finished it in July—but I have been put off by the sheer amount of work it deserves. Let's see if I can do it justice.

In this book, the authors explore how networks among people have transformed how we connect with each other, both personally and electronically.

Chapter 1 summarizes the book's main argument pretty well. People "have become increasingly networked as individuals, rather than being embedded in groups. In the world of networked individuals, it is the person who is the focus: not the family, not the work unit, not the neighborhood, and not the social group" (p.6). They term networked individualism "an 'operating system' because it describes the ways in which people connect, communicate, and share information" (p.7). Its characteristics are

  • personal
  • multiuser
  • multitasking
  • multithreaded (p.7).
It requires new strategies and skills for solving problems (p.9). And it involves a "triple revolution":
  • We can reach beyond tight groups (p.11)
  • We have new communication power and information-gathering capabilities (pp.11-12)
  • Information and communication technologies (ICTs) are a "bodily appendage," always accessible (p.12).
Here, the authors italicize their main points; I'll just bullet them:
  • "Many meet their social, emotional, and economic needs by tapping into sparsely knit networks of diverse associates rather than relying on tight connections to a relatively small number of core associates." (p.12)
  • "Networked individuals have partial membership in multiple networks and rely less on permanent memberships in settled groups" (p.12)
  • "A key reason why these kinds of networks function effectively is that social networks are large and diversified thanks to the way people use technology" (p.13)
  • "The new media is the new neighborhood" (p.13)
  • "Networked individuals have new powers to create media and project their voices to more extended audiences that become part of their social worlds" (p.13)
  • "The lines between information, communication, and action have blurred. Networked individuals use the internet, mobile phones, and social networks to get information at their fingertips and act on it, empowering their claims to expertise (whether valid or not)" (p.14)
  • "Moving among relationships and milieus, networked individuals can fashion their own complex identities depending on their passions, beliefs, lifestyles, professional associations, work interests, hobbies, or any number of other professional characteristics" (p.15)
  • "At work, less formal, fluctuating, and specialized peer-to-peer relationships are more easily sustained now compared with the past, and the benefits of boss/subordinate hierarchical relationships are less obvious" (p.15)
  • "The organization of work is more spatially distributed" (p.16)
  • "Home and work hae become more intertwined than at any time since hordes of farmers went out into their fields" (p.16)
  • "While ICTs have shattered the work-home dividing line, they have also breached the line between the private and public spheres of life" (p.17)
  • "New expectations and realities about the transparency, availability, and privacy of people and institutions are emerging" (p.17)
  • "In the less hierarchical and less bounded networked environment—where expertise is more in dispute than in the past and where relationships are more tenuous—there is more uncertainty about whom and what information sources to trust (p.18).
With that summary in mind, the authors dive into the rest of the book.

In Chapter 2, "The Social Network Revolution," the authors discuss social networks (in the sociological sense, that of relationships among individuals) (p.21). They identify several major trends:
  • Widespread connectivity (pp.22-27), including more ground and air travel, more telecommunications and computing, and more commercial and social interconnectedness due to trade.
  • Weaker group boundaries (pp.27-30), due to changes in family composition, roles, and responsibilities; the rise of ad hoc, informal networks over structured and bounded voluntary organizations; and the fragmenting of media markets.
  • Increased personal autonomy (pp.31-34), due to increased work flexibility; falling barriers related to ethnicity, gender, religion, and sexual orientation; and the rise of IRAs and the decline of defined benefit pensions.
Although people still think they're in groups, the authors say, they're really in networks (p.35). In networked sociality, boundaries are more permeable, interactions occur with diverse others, hierarchies are flatter and more recursive (p.37). The authors provide a table comparing group-centered society with networked individualism (p.38).

In Chapter 3 and 4, "The Internet Revolution" and "The Mobile Revolution," the authors turn to the rise in Internet and mobile connectivity, discussing how these changes connected us in different ways. In particular, mobile devices make us hyperconnected (p.95) and hypercoordinated (p.99), and norms have not caught up to practice (p.105). For instance, "mobile hyperconnectivity in fuzzily bounded public-private space" can lead to problems such as private conversations overheard in public spaces as well as questions of who should and shouldn't be in the loop.

In the next section, the authors address how networked individualism works. In Chapter 5, "Networked Relationships," they describe communities as fluid personal networks, noting a post-WWII shift from door-to-door to place-to-place communities (p.122). With the triple revolution, we're undergoing another shift, from place-to-place to person-to-person (p.123). "Their networks are sparsely knit, with friends and relatives often loosely linked with each other" (p.124). And the authors suggest thinking in terms of "a networked self: a single self that gets reconfigured in different situations as people reach out, connect, and emphasize different aspects of themselves" (p.126). In their personal networks, communities become sparsely knit—most members aren't directly connected—and specialized—different network members help each other with different types of support (p.135).

In Chapters 6 and 7, "Networked Families" and "Networked Work," the authors note similar changes in the family. Lifelong marriage has gone the way of lifelong employment. Work involves multiple teams and multiple purposes (pp.171-172). Work trends include 
  • globalization of work, consumerism, travel (p.172)
  • a shift from atom work to bit work (p.172)
  • the internet and mobile revolutions (p.173)
  • the ability to work at a distance (p.173)
  • the resulting trend toward mobile work using primarily laptops and smartphones (p.173)
These trends especially affect workers whose organizations are "permeable"; workers directly connect with each other, and their work structure is "more flexible, laterally coordinated, team based, and boundary spanning" (p.177). Information is the key asset, and its flow is critical for success (p.178). Networked organizations have familiar characteristics:
People often work in multiple projects with different teams. This allows firms to assemble ad hoc teams with diversified talents and perspectives. As workers shift among teams, they can develop cumulatively larger networks of expertise that are "glocal," with both local interactions and global connectivity. Instead of submitting to the traditional hierarchical ode of authority, workers have more discretion about the work they jointly accomplish. Networked organizations have advantages for boundary spanning, as employees work and network between work groups and organizations—and at times, between continents. (p.181)
In these organizations, the structure tends to be flatter, with fewer reporting relationships, and more informal (p.182).

Networked work also involves more work from home (p.186).

Let's leave it there. The authors have plenty more to say: about networked creators (Ch.8), networked information (Ch.9), how to thrive as a networked individual (Ch.10), and the future of networked individualism (Ch.11). But I'm most interested in the analysis above, which is so worthwhile that I regret sitting on this review for so long. If you're interested in networked individualism, certainly take a look at this book.

Reading :: Explorations in Information Space

Explorations in Information Space: Knowledge, Actor, and Firms
Edited by Max H. Boisot, Ian C. MacMillan, and Kyeong Seok Han

I just reviewed Boisot et al.'s Collisions and Collaboration, and in that review I discuss Boisot's I-Space in detail. This collection further discusses and applies I-Space.

The book's purpose is "to provide some theoretical perspective on the nature of organizationally relevant knowledge and to indicate the kind of research that might generate empirically testable hypotheses and hence to further the development of a knowledge-based theory of the firm" (p.6). The I-Space is central to that theorizing, meant to provide insight into "the nature of information and knowledge flows in any system" (p.7). The authors assume that "the speed and extent to which information diffuses within a population of agents is a function of how far that information has been structures" and that "information only becomes knowledge if it gets internalized and becomes part of the recipient's expectational structure—that is, if it affects the recipient's belief structure taken as disposition to act" (p.7).

For me, the interesting stuff started in Chapter 4. The authors start by claiming that "How far knowledge gets articulated determines how speedily and extensively it can be shared" (p.109). Although economics has taken the default assumption that markets underlie all other forms (p.109), Boisot et al. argue that "the heterogeneity of organizations, not their homogeneity, had to be taken as a default assumption when analyzing organizational strategies" (p.110). Since organizations are characterized by heterogeneity, articulation and sharing are thus impeded, and so "transaction costs and benefits remain heavily stacked against the kind of articulation of knowledge that would be required to make the choice of markets either ubiquitous or even symmetric with that of organizations" (p.110). So, they conclude, "in the beginning there was the organization" (p.110).

Given this assumption, the authors outline E-Space (epistemic space), with the axes of codification and abstraction. At the most uncodified, concrete corner, we get embodied knowledge; at the opposite corner, we get abstract symbolic knowledge; and in the middle, we get a band of narrative knowledge (p.123). The authors then add the axis of diffusion in order to produce the familiar I-Space—and we now see that embodied knowledge tends to be the least diffused, while abstract symbolic knowledge tends to be the most diffused (p.131). That is, the more well-compacted and abstract knowledge is, the more mobile and fluid it tends to be. Yet at the same time, codification and abstraction involve data losses (p.131).

Boisot et al. claim implications for economics. For our purposes, the most interesting one is that, below a certain threshold of codification and abstraction, a shared context between sender and receiver favors hierarchies rather than markets (p.136).

Chapter 5 continues exploring the nature of organizations. Here, Boisot discusses the evolution of bureaucracies from Gemeinschaft (local, personalized) to Gesellschaft (large, ubiquitous, impersonal) (p.147). Boisot pegs this shift to the printing press, which provided information storage and diffusion (p.148). Similarly, Boisot argues, modern ICTs might favor options other than bureaucratic hierarchies and competitive markets to other options, such as clan-like networks (p.150).

To make this argument, Boisot discusses bureaucracies, markets, fiefs, and clans in the same terms that he discussed them in Collisions and Collaboration. He adds that we can think of three types of complexity:

  • Codification: Descriptive complexity
  • Abstraction: Computational complexity
  • Diffusion: Relational complexity (p.155)
"We hypothesize that building effective institutional structures in market and clan regions widens the complexity region and helps to stabilize it while simultaneously reducing the size of the region in the I-Space from which they chaotic regime can 'attract' transactions—that is, its basin of attraction" (p.159). Furthermore, modern ICTs shift the diffusion curve because of two effects:
  • The diffusion effect: "at any given level of codification and abstraction, more information will reach more people per unit along the diffusion scale than hitherto" (p.160)
  • The bandwidth effect: "any given proportion of the population located at some point along the diffusion scale can be reached at a lower level of codification and abstraction—that is, at a higher bandwidth—than hitherto" (p.160). 
In fact, "the rightward shift in the diffusion curve appears to privilege both market institutions over bureaucratic ones and clan-like institutions over fiefs" (p.161). Evidence for markets-over-bureaucracies: "the average size of firm in the United States has actually been falling over the past thirty years" due to outsourcing (p.161). Evidence for clans-over-fiefs: "the emergence of interpersonal networks and relational contracting between firms" (p.161). 

I don't think I've sufficiently assimilated Boisot's work to relate it well to other frameworks I've examined. But I am really intrigued by this line of reasoning, particularly Boisot's consideration of how ICTs change the landscape of organizations. If you're similarly intrigued, take a look. 

Reading :: Collisions and Collaboration

Collisions and Collaboration: The Organization of Learning in the ATLAS Experiment at the LHC
Edited by Max Boisot, Markus Nordberg, Said Yami, and Bertrand Nicquevert

I picked this book up primarily because it was one of the few recent books out there to use the term "adhocracy"—a term that I'm currently researching for a project. But it turns out that Boisot is quite well known for his writings on information and strategy (though not so well known in the circles where I typically read and publish, alas). After reading this book, I can understand why: his I-Space framework is useful for thinking through the relationships between organizational characteristics and the circulation of information.

Let's talk about I-Space first, then get back to the book project.

I-Space is depicted as a three-dimensional space, a cube with three axes:

  • Codification: from very uncodified to very codified information. "Codification is indexed by the amount of data-processing required to distinguish between categories and to assign events to these" (p.33).
  • Abstraction: from very concrete to very abstract information. "Abstraction is indexed by the number of categories required to perform a given categorical assignment." (p.33)
  • Diffusion: from very concentrated to very diffuse. Here, we're talking about the degree to which information can be diffused over time. "The greater the degree of codification and abstraction achieved for a given message, the larger the population of agents that can be reached by diffusion  per unit of time." (p.34)
Within this three-dimensional space, Boisot et al. say, we can map a social learning cycle. This cycle follows six phases:
  1. Scanning
  2. Codification
  3. Abstraction
  4. Diffusion
  5. Absorption
  6. Impacting (p.39)
Mapped in I-Space, the social learning cycle typically looks like an S-curve. But it looks different for each organization, since each organization's I-Space tends to be different—that is, different organizations have different characteristics of codification, abstraction, and diffusion. Indeed, "to the extent that individual agents can each belong to several groups, each locatable in its own I-Space, they will participate in several SLCs that interact to form eddies and currents" (p.38).  

In fact, if we map parts of the I-Space to cultures and institutional structures, we find that different structures have different "homes" in the I-Space:

Fiefs. These thrive in situations with concrete, undiffused, uncodified information. Characteristics:
  • "Information diffusion limited by lack of codification to face-to-face relationship." 
  • "Relationships personal and hierarchical"
  • "Submission to superordinate goals"
  • "Hierarchical coordination"
  • "Necessity to share values and beliefs"
Bureaucracies. These thrive in situations with abstract, undiffused, codified information. Characteristics:
  • "Information diffusion limited and under central control"
  • "Relationships impersonal and hierarchical"
  • "Submission to superordinate goals"
  • "Hierarchical coordination"
  • "No necessity to share values and beliefs"
Markets. These thrive in situations with abstract, diffused, codified information. Characteristics:
  • "Information widely diffused, no control"
  • "Relationships impersonal and competitive"
  • "No superordinate goals—each one for himself"
  • "Horizontal coordination through self-regulation"
  • "No necessity to share values and beliefs"
Clans. These thrive in situations with concrete, diffused, uncodified information. Characteristics:
  • "Information is diffused but still limited by lack of codification to face-to-face relationship." 
  • "Relationships personal but non-hierarchical"
  • "Goals are shared through a process of negotiation"
  • "Horizontal coordination through negotiation"
  • "Necessity to share values and beliefs" (p.49)
These different institutional types are similar to those of Ronfeldt's TIMN, Cameron and Quinn's Competing Values Framework, and Mintzberg's categories of structures, but they're defined via the three axes in the I-Space. Essentially, Boisot et al. are arguing that certain institutional structures thrive because they best adapt to specific conditions in a given I-Space. 

Yet they also posit that modern information and communication technologies (ICTs) are shifting the curve, making it easier to diffuse messages and thus to reach more people at a lower level of codification and abstraction (pp.50-51). This shift is a big deal. Up to this point, to be widely diffused, knowledge had to be highly codified and abstracted—something that naturally favored bureaucracies and markets, which are set up for those conditions. But due to ICTs, the shift in the curve might favor clans as well as markets, to the comparative detriment of bureaucracies (p.51). "Over time, this is likely to favor clan-like network cultures that have a tendency to closure ... rather than the more open market processes" (p.51).

So there's the I-Space framework. In this collection, Boisot (who is listed as an author on every chapter) and his coauthors apply this framework to the ATLAS collaboration, a complex multunational scientific organization that uses ATLAS, a high-energy physics detector at CERN; it forms part of the Large Hadrion Collider (LHC) (p.8). This organization coordinates without central managerial authority (p.55). 

In Chapter 3, the authors examine the ATLAS collaboration as an adhocracy, drawing from Mintzberg to identify the structure and then locating it "to the right of the region in the I-Space labeled 'clans'" (pp.74-75)—that is, further diffused than clans are. "As a geographically dispersed, loosely coupled adhocracy, the ATLAS Collaboration extends beyond the bounds of clan cultures as conventionally understood. Yet ... it remains driven in large part by clan values and practices" (p.74). Later, in Chapter 4, the authors add: 
As a loosely coupled adhocracy, ATLAS operates to the right of clans along the diffusion scale of the I-Space, in the region where, on account of the lack of structure of the knowledge being exchanged and the large number of interacting players, things could quickly become chaotic. The collaboration remains culturally cohesive, however, held together by shared commitments, norms, and a common focus on an infrastructure of boundary objects that over time deliver a clan totem: the detector itself. (p.114).
Boisot et al. credit modern ICTs for the success of ATLAS' adhocracy: "It is mainly the bandwidth effect [in which more people can be reached per unit of time] that makes giant adhocracies like the ATLAS Collaboration possible, and that is likely to give birth to a new scientific culture" (p.257). For instance, such adhocracies can involve "a re-personalization of science, a move away from the impersonality of anonymous peer reviewing and journal publications as the only way to get on and towards the building-up and exploitation of personal networks" (p.263). Via ICTs, "the culture of clans can be extended to more loosely coupled and geographically scattered adhocracies" (p.264).

Let's inject a bit of caution here. Many of the authors are involved in ATLAS or other aspects of CERN; this collection is not (exclusively) an outsider's account and shouldn't be considered a set of studies per se. In tone, the contributions are often a bit congratulatory.

But on the other hand, the collection does a great job of explaining and illustrating I-Space. If you're interested in how organizations work, or how I-Space works, this book is a good solid introduction with some intriguing analysis.

Reading :: Writing Ethnographic Fieldnotes

Writing Ethnographic Fieldnotes, Second Edition
By Robert M. Emerson, Rachel I. Fretz, and Linda L. Shaw

I've been meaning to read this book for a while. It didn't disappoint—although it's not a perfect book.

First the plusses.

Field notes are an essential part of ethnography, the main way of collecting data and beginning the analysis. And like any essential tool, field notes have developed into several variations, with different strengths and applications. Yet in many ethnographic textbooks, the discussion of field notes is relatively underdeveloped. Yes, we're told to write things down. But what things? When? How? How do we process field notes? How do we turn them into an analysis? Ethnographers and other qualitative researchers can generate an enormous amount of text, but may not be consistent enough to examine the same thing over time, or may not be organized enough to extract consistent insights from that writing.

That is, field notes don't simply involve writing down what the ethnographer sees, hears, and experiences. There's enough in a minute of observation to fill a book if one were meticulous enough. Field notes have to interpret and record what the ethnographer believes is the most important information, and they have to do this consistently in order to generate comparable data over time. That's tough.

In this book, the authors systematically address various aspects of field notes—from jotting to creating scenes, from stylistic considerations to member meanings, from coding to memoing, and finally to inserting fieldnotes into an ethnography. At each point, the authors provide plentiful examples and discuss the different sorts of choices ethnographers make as they write.

And that brings us to the minus—the drawback to the book. Field notes tend to be detailed, and the book similarly dives into the details of producing and processing them—often too quickly, without doing enough to surface and signal the overall structure of each chapter. I had to read each chapter with one finger on the first paragraph, flipping back periodically to remind myself what these particular details were meant to address.

But that's a relatively small issue. If you are interested in learning more about field notes, put Post-Its on the appropriate pages and dive into this book.

Topsight > Triangulation tables

In previous posts in this series, I've discussed two meso-level analytical constructs, two constructs for making sense of what we see minute-by-minute in people's work. Handoff chains help us to envision regular sequences, while resource maps let us see the connections among the information resources that people use.

Think of your research site as a football game. In handoff chains, the camera follows the ball, tracing through the series of handoffs and tosses that move it downfield. In resource maps, the camera follows the game, watching systemic dynamics and tactical changes as players and artifacts all over the field continuously reconfigure themselves.

Can we follow the ball and the game? Can we find a way to coordinate these two models? Sure: That's what we use triangulation tables to do. They allow us to triangulate data: to compare the stories that we get from different sets of data in order to make sure they agree.

Triangulation tables are based on Bruno Latour's sociotechnical graphs, but they've been adapted to mesh together what we learn from handoff chains and resource maps. For the messy details, see the paper that Zachry, Hart-Davidson and I put together a few years ago:

Spinuzzi, C., Hart-Davidson, W., & Zachry, M. (2006). Chains and ecologies: Methodological notes toward a communicative-mediational model of technologically mediated writing. SIGDOC  ’06: Proceedings of the 24th annual international conference on Design of communication (pp. 43–50). New York, NY, USA: ACM Press.

You can also see it at work in my book Network.

The basic idea is pretty simple: we put together a series of tables or matrixes that relate the chain of sequences to the resources used at each point in the sequence. We start with the individual visit, then expand to the group, then to larger units.

In our implementation, triangulation tables are tables in which 

  • columns represent communicative events from the handoff chain
  • rows represent different points of comparison - different data sources, different participants, or different groups
  • cells contain information resources that are used for a given communicative event within a given point of comparison

For instance, here's a triangulation table in which the researcher examines a single participant's work, using two different data sources (field notes from the observation and the post-observation interview). Notice that this table helps us relate communicative events from the handoff chain to the resources from the resource map. And it helps us to see how our field notes differ from the participant's account. It helps us to triangulate the two data sources: we can see how closely they line up and where they disagree or are partial. See the italics in each cell: these are texts that are mentioned in just one account.

Table 1. A triangulation table for a single participant.

Communicative events

Prepare for callContact customer and discuss billRecord notes on call
Arnold - Field notescollections list, annotations on collections list, database screen for customerdatabase screen for customer's collections informationPhone call to customer, collections list,database screen for customer's collections informationdatabase screen for customer's collections informationfax cover sheetsticky note, collections list
Arnold - Interviewcollections list, annotations on collections list, bankruptcy noticesspiral notebook,phone calls from coworkersBills, phone call to customercollections list, annotations to collections listdatabase notesdatabase screen for customer

Now suppose we do the same thing for multiple participants. We can collapse the list of texts from both data sources into one list for each participant, then compare the participants -- and we begin to turn up similarities and differences in how individual participants work. Triangulating at this level helps us to do the following:

  • figure out which texts are "core" texts, the bare minimum for executing each communicative event
  • spot innovations that one participant uses and others don't

For instance, in Table 2, Clara uses a text that the others don't use: a log of previous customer interactions. Does this log function as a substitute for some of the texts that others use, such as Arnold's spiral notebook? The triangulation table helps us to spot differences and reexamine our data - including our copies of the spiral notebook and the log - to answer questions about how participants work differently. Through this triangulation, the table helps us to catch innovations and workarounds, showing how these substitute for other texts.

Table 2. A triangulation table for multiple participants.

Communicative events

Prepare for callContact customer and discuss billRecord notes on call
Arnoldcollections list, annotations on collections list, database screen for customer, database screen for customer's collections information, bankruptcy notices, spiral notebook, phone calls from coworkersPhone call to customer, collections list, database screen for customer's collections information, billsdatabase screen for customer's collections information, fax cover sheet, sticky note, collections list, annotations to collections list, database notes, database screen for customer
Billcollections list, annotations on collections list, database screen for customer, database screen for customer's collections information, bankruptcy noticesPhone call to customer, collections list, database screen for customer's collections information, bills, spiral notebook of call logdatabase screen for customer's collections information, collections list, annotations to collections list, phone call to supervisor
Claracollections list, annotations on collections list, database screen for customer, database screen for customer's collections information,log of previous customer interactionsPhone call to customer, collections list, database screen for customer's collections information, log of previous customer interactionsdatabase screen for customer's collections information, collections list, annotations to collections list, log of previous customer interactions

If the organization is large enough, you may triangulate to spot differences in how groups do their work. Groups can be

  • participants doing the same work at different locations
  • participants taking on the same role at the same location and in the same workflow
  • participants at the same location, working in the same role, but with different characteristics (training, experience, access to technology)

For instance, if a company has two offices, it's common for the offices to develop different ways of doing things due to different technologies,  training, backgrounds, expectations, or innovations. A group-level triangulation table can help you spot those differences as well. Table 3 shows how two offices might handle the same communicative events differently - and how the second office has managed to use one text to substitute for many.

Table 3. A triangulation table for different groups.

Communicative events

Prepare for callContact customer and discuss billRecord notes on call
Group Acollections list, annotations on collections list, database screen for customer, database screen for customer's collections information, bankruptcy notices, spiral notebook, phone calls from coworkersPhone call to customer, collections list, database screen for customer's collections information, billsdatabase screen for customer's collections information, fax cover sheet, sticky note, collections list, annotations to collections list, database notes, database screen for customer
Group Bcollections list, customer folder with contact information and last billPhone call to customer, customer folder with contact information and last bill, calendarcustomer folder with contact information and last bill, Word template, email
The triangulation table helps you to easily relate information from the other two analytical constructs and spot differences. It's a way to manage complexity so you can get a handle on the meso level. Which is great, because we're almost ready to move to the micro level—the level of habits and reactions. More on that soon.