Zack [42] distinguished these four termsaccording to two dimensions: the nature of what is being processed and the consti-tution of the processing problem.The nature of what is being processed is either information or frames of ref-erence. With information, we mean “observations that have been cognitively pro-cessed and punctuated into coherent messages” [42]. Frames of reference [4, p.108], on the other hand, are the interpretative frames which provide the context forcreating and understanding information. There can be situations in which there is alack of information or a frame of reference, or too much information or too manyframes of reference to process.

Ta b l e 3DERMIS design premises [29]

For our research design, we drew on Walsham [33] and Klein and Myers [13],who provide comprehensive guidelines on how to conduct interpretive case studyresearch in the IS domain.

The problems of managing information and managing frames of reference are“tightly linked in a mutually interacting loop” and require “managing informationand the systems that provide it” [42]. IS have been generally designed to overcomethe information problems from Table 1. Most IS are aimed at either storing and re-trieving information to reduce uncertainty, such as database management systemsand document repositories, or at analyzing and processing large amounts of infor-mation to reduce complexity, such as decision support systems [31]. However, aswe have previously discussed, information related strategies are not always helpfulin coping with a variety of potential meanings.Problems of interpretation and the creation and management of frames of refer-ence, which aids Sensemaking, have generally not been taken into account whendesigning IS. Most IS currently seem tointend the opposite because they aim atreplacing or suppressing the possibility tomake sense of situations.

there is scarce research on how IS can support informa-tion processing challenges—specifically related to Sensemaking—in crisis manage-ment [14]

Sensemaking is about contextual rationality, built out of vaguequestions, muddy answers, and negotiated agreements that attempt to reduce ambi-guity and equivocality. The genesis of Sensemaking is a lack of fit between whatwe expect and what we encounter [40]. With Sensemaking, one does not look at thequestion of “which course of action should we choose?”, but instead at an earlierpoint in time where users are unsure whether there is even a decision to be made,with questions such as “what is going on here, and should I even be asking this ques-tion just now?” [40]. This shows that Sensemaking is used to overcome situationsof ambiguity. When there are too many interpretations of an event, people engagein Sensemaking too, to reduce equivocality.

Decision making is traditionally viewed as a sequential process of problem classifi-cation and definition, alternative generation, alternative evaluation, and selection ofthe best course of action [26]. This process is about strategic rationality, aimed atreducing uncertainty [6, 36]. Uncertainty can be reduced through objective analysisbecause it consists of clear questions for which answers exist [5, 40]. Complex-ity can also be reduced by objective analysis, as it requires restricting or reducingfactual information and associated linkages [42]

The central problem requiring Sensemaking ismostly that there are too many potential meanings, and so acquiring informationcan sometimes help but often is not needed. Instead, triangulating information [34],socializing and exchanging different points of view [20], and thinking back of pre-vious experiences to place the current situation into context, as the retrospectionproperty showed us, are a few strategies that are likely to be more successful forSensemaking.

Just as the information processing challenges from Table 1 are not mutually ex-clusive, Sensemaking and decision making cannot be separated, but instead operatesimultaneously. Meaning must be established and then sufficiently negotiated priorto acting on information [42]: Sensemaking shapes events into decisions, and deci-sion making clarifies what is happening [40].

Weick et al. [41, p. 419] formulate a gripping conclusion on what the sevenSensemaking properties are all about: “Taken together these properties suggest thatincreased skill at Sensemaking should occur when people are socialized to makedo, be resilient, treat constraints as self-imposed, strive for plausibility, keep show-ing up, use retrospect to get a sense of direction, and articulate descriptions thatenergize. These are micro-level actions. They are small actions. But they are smallactions with large consequences.”

The seven different properties of Sensemaking can be captured by the acronym SIRCOPE: Social context, Identity construction, Retrospection, Cue extraction, Ongo-ing projects, Plausibility, and Enactment [17–21, 37–39]

Crisis environments are characterized by various types of information problemsthat complicate the response, such as inaccurate, late, superficial, irrelevant, unreli-able, and conflicting information [30, 32]. This poses difficulties for actors to makesense of what is going on and to take appropriate action. Such issues of informationprocessing are a major challenge for the field of crisis management, both concep-tually and empirically [19].

We use the theory of Sensemaking to study exactly this: how people makesense of their environment, and how they give meaning to what is happening. Sense-making is a crucial process in crises, as the manner and thereby the success of howone deals with crucial events is determined by the grasp one has of a situation.

Value Sensitive Design (VSD) emphasizes consideration of stakeholder values when making design decisions [5]. Applying this rationale to the goal of leveraging the capacity of digital workers during crisis events, we identify design solutions that fit the underlying community dynamics, including current work practices, organizational structures, and motivations of digital volunteer work.

Our research reveals several design opportunities in this space. Importantly, informed by the empirical findings presented here, we argue for situating solutions within current work practices and infrastructures.

Empirical research on historical disaster events shows response efforts taking four different organizational forms: established, extending, expanding, and emerging [3

This distinction enlightens the reading of thegrowing social media and mass emergency lit-erature for three reasons. First, without it, thisnew literature risks undoing decades of work bysocial scientists who have dismantled the mythsof disaster, with a dominant discourse thatincludes panic and unlawful behavior by victims.But in disasters arising from natural hazards, weknow such behaviors are not typical. Massemergencies arising from criminal behavior canhave a much wider range of collective behaviorbecause the source of the hazard is unknown,unpredictable and perhaps more imminentlydangerous

Misinforma-tion arising from natural hazards or exogenousevents might be greater in kind, but less inimpact, with fewer in-common readers as it tra-verses a network that can move a little slowerthan it might in criminal mass emergency events.Because the problem-solving tends to be morediffuse in exogenous events, the same messagemight not reach enough people; in other words,the misinformation might also be thinly diffused.Misinformation in such events is more likely toage out, or not be relevant to enough locations topose a big threat—in other words, all informationin thefirst place is less likely to be categoricallycorrect or incorrect, and as such, it is hard tofindas much value in pursuing the threat of misin-formation in such situations.

Wefindendogeneityandexogeneityof haz-ards to be a meaningful distinction in socialmedia in mass emergencies research, one thatreadily clarifies for a range of researchers andreaders who are outside the social science disci-pline. Just as events that arise from exogenousand endogenous hazards differently impact legal,political, health, and other societal systems, so dothey differently impact social media behavior.8With exogenous events, the culprit is beyondreach, and unstoppable. With endogenous agents,the suspect lies within. Therefore, organizingfeatures of the communication are distinctlydifferent, because the source(s) of the problem(s),the nature of their solutions,and the ability forthe perception of the collective control of theoutcomeare different. Online participation focu-ses on in-common salient problems when theyare present; when the problems are lessin-common and must be addressed in parallel, thecrowd organizes in many smaller groupings and,often endogeneity and exogeneity of hazardspredicts this (Palen & Anderson,2016).

We make this point because we worrythat the very idea of“social media”flattens themany meanings of“crisis”and“emergency”forwhich social sciencefields have worked to pro-vide insight. For example, because Twitter orFacebook are available for use in any kind ofcrises, it is easy to make these applications thesalient concern, and ask“Is Twitter or Facebookbetter in emergency response?,”rather thanquestion how the very nature of emergencyresponse might beg for different forms of infor-mation seeking and reporting. We refer to thisflattening of communication medium and hazardas thesocial media and crisis confound.

Research has demonstrated that data fromsocial media interactions can provide situationalawareness for specific crisis-related tasks anddomains. Using natural language processing (afield of study which enables computers to ana-lyze and understand the human language),machine learning (techniques that provide com-puters with the ability to learn), and crowd-sourcing (the process of accomplishing a task bydividing it into subtasks that can be performed bya large group of people), several research groupshave developed methods and tools for detectingand monitoring epidemics through social mediadata analysis (Brennan, Sadilek, & Kautz,2013;Chen, Hossain, Butler, Ramakrishnan, & Pra-kash,2016; Munro,2011; Olteanu, Vieweg, &Castillo,2015).

ubsequentresearch has focused on developing natural lan-guage processing classifiers that analyzes text tohelp identify tweets contributing to situationalawareness (Corvey, Verma, Vieweg, Palmer, &Martin,2012; Verma et al.,2011), though ingeneral the state-of-the-art of thefield is such thatautomation behind situational awareness deriva-tion is difficult to do dependably. Ireson (2009)assessed the extent to which public forum post-ings could add to situational awareness duringthe 2007floods around Sheffield, UK and foundextractable relevant event information despite theinconsistent quality and conversational nature ofthe posts.

colleagues have begun to elaborate“crises”as amore general dimension which includes disastersand to conceptualize other kinds of crises as well(cf. Quarantelli et al.,2006, p. 16).

There is significant contemporary consensusthat all disasters have origins in human volition;sometimes in complex ways, many factors underhuman control are characterized as the ultimatecause of disasters. There is also growing con-sensus about what might be called the minimumdefining features of disasters. Nearly two decadespast, Quarantelli (2000, p. 682) reported that aconsensus definition could be stated as: disastersare“relatively sudden occasions when...theroutines of collective social units are seriouslydisrupted and when unplanned courses of action”must be undertaken to cope. Most contemporaryresearchers would onlyfind small issue with thiscomposite definition. Quarantelli (2005, p. 339)later stressed that disaster must be understood asan inherently social phenomenon.

Quarantelli (2000, p. 682)identifies defining features as: (1) sudden onsetoccasions, (2) serious disruptions of the routines ofcollective units, (3) evidenced in the adoption ofunplanned courses of action to adjust to the dis-ruption, (4) with unexpected life histories desig-nated in social space and time, and (5) posingdanger to valued social objects. Subsequently, heemphasized that disasters interact with vulnera-bility, reflecting“weaknesses in social structuresor social systems”(Quarantelli,2005, p. 345). Inthis evolving characterization, Quarantelliemphasizes neither an event nor a physical place ortime as necessarily relevant to disasters

There are no unique“ecolog-ical definitions”although a reader can surelyidentify definitions that may be argued to bemore or less macro in scope. Similarly, vulner-ability and resilience are concepts related tocauses, conditions or consequences of disasters(Quarantelli, Lagadec, & Boin,2006); they donot directly define disasters. The role that eco-logical thinking, vulnerability and resiliencemight play in disaster definitions is not asdefining features, but as influences on the designof research addressing disasters.

Quarantelli (2005, p. 342) arguedthat when hazard cycles and agents are the focus,disasters become an epiphenomenon rather thana central target for definition and explanation.

Because there are many definitions, frommany sources, used for many purposes, it isimportant to specify what definitions form thecontent for this chapter. Thus, for this reviewdisaster is a social scientific concept that refers toa particular class of phenomena whose specifi-cation rests in theory-based thinking (cf. Perry,1998). So emergencies and catastrophes are dis-tinct from disasters and not included here(Alexander,2014, p. 127; Perry & Lindell,2007;Quarantelli,2000, p. 68,2005; Rodriguez, Trai-nor, & Quarantelli,2006). Also, research indi-cates that severe disruptions arising from conflictsituations are fundamentally different than thosethat arise from consensus situations (Peek &Sutton,2003, Quarantelli,1993,2005;Singh-Peterson, Salmon, Baldwin, & Goode,2015; Waugh,2006, p. 392). Consistent withthesefindings, disaster definitions consideredhere are those that are separate fromconflict-based occasions.

Ultimately, researchers andtheorists need to embrace Quarantelli’s admoni-tion that a social scientific vision of disastersrequires focus on the key dimensions of theconcept, independent of externalities that mayconstitute causes, conditions for or consequencesof disasters. To build a theory-basis for disasterresearch does require much knowledge of causes,conditions and consequences, but it is critical tobuild such a body of knowledge on a sharedunderstanding of the concept of disaster.

For at least thefirst three decades ofresearch and theorizing, much concern wasdevoted to isolating what constituted the“disas-ter”from associated causes, conditions andconsequences. Over time, researchers havemoved away from an agent-centered,damage-driven, uncontrollable event vision. Inthe context of disaster events, it is now generallyacknowledged that, although agents may beproximal causes, humans“cause”virtually allforms of occasions we label“disasters.”Relativeto the disaster concept itself, most researcherscurrently view social disruption as the keydefining feature or essential dimension. Con-ceptual refinements have attempted to understandindividual, organizational and social systemlevels of disruption and how these may differ orinteract within the context of“disaster”episodes(Quarantelli,2000,2005; Perry & Lindell,2007;Gaillard,2016). There has also been attention tohow (and whether) the disruption feature of dis-asters should be analytically separated fromshort-term, temporary interactions (such asemergent groups) that appear to arise as part ofthe disruption (Stallings,1998; Drabek &McEntire,2003).

Our extensions also have implications for theories ontrust.

Therefore, training should focus on learning how toquickly recognize volunteers’ volition in participating inan emergent group, the tasks they might engage in, andthe support they might need to carry out those tasks.Such training could also help people to recognize thebenefits and dangers of generalized trust. It could alsohelp people to quickly evolve a coordination mecha-nism that does not rely on what people know, but oncompiling and communicating a narrative of the actionsthat volunteers take, so that others are able to assess forthemselves what actions they could take to help.

ur examination suggests that by expandingthe context in which TMS theory is applied to includeemergent response groups, insights can be gained intotheir internal dynamics. The three indicators of the levelof development of a TMS provide a useful frameworkfor organizing these insights in the exhibit.

The urgency of time may make it too onerous forthe extra effort of articulating actions as they are beingperformed, yet most emergency response requires somecommunication.

Explicitly articulated narratives mayalso make clearer that multiple sequences of actions maybe occurring simultaneously, thus resolving role conflictsby allowing multiple ways to accomplish a task

Emergent response groups may also use a mechanismof creating a community narrative (Boland and Tenkasi1995), which is a running narrative of the actions takenand not taken, the decisions made, and the theories inuse. Narratives do not represent a single shared under-standing of a domain; rather they represent the mul-tiplicity of events and actions a community is taking,as members are taking them. Narratives may be articu-lated explicitly or understood implicitly.

Whenemergent response groups first come together, membersare likely not to ask one another about who knows what;instead, they are likely to ask about what is knownabout the situation and about the actions taken thus far(Dyer and Shafer 2003, Hale et al. 2005). The cogni-tive structure that they develop for the group centersnot around people, but on action-based scenarios thateither have been or might be carried out. These scenariosinclude decisions, actions, knowledge, events, and feed-back (Vera and Crossan 2005).

On the surface, the lack of sta-ble membership suggests that a shared mental modelmay not be viable or even desired in emergent responsegroups. Time may be too precious to seek consensus onevents and actions, and agreements may make the groupless flexible to accommodate to changing inputs.

hus, we believe challenges occur in all three indica-tors of the level of development of a TMS—expertisespecialization, credibility, and expertise coordination—requiring a need to consider extending theorizing abouteach indicator for emergent response groups.

Moreland and Argote(2003) suggest that the dynamic conditions under whichthese groups form and work together are likely to havenegative effects on the development of transactive mem-ory.

Research on TMS has identified three indicators of thelevel of development of a TMS (Lewis 2003, Morelandand Argote 2003):1.Memory (or expertise) specialization:the tendencyfor groups to delegate responsibility and to specialize indifferent aspects of the task;2.Credibility:beliefs about the reliability of mem-bers’ expertise; and3.Task (or expertise) coordination:the ability of teammembers to coordinate their work efficiently based ontheir knowledge of who knows what in the group.The greater the presence of each indicator, the more de-veloped the TMS and the more valuable the TMS is forefficiently coordinating the actions of group members.

A TMS can be thoughtof as a network of interconnected individual memorysystems and the transfer of knowledge among them(Wegner 1995). Individuals who are part of a TMSassume responsibility for different knowledge domains,and rely on one another to access each other’s expertiseacross domains. Expertise is defined in the TMS litera-ture to broadly include the know-what, know-how, andknow-why of a knowledge domain (Quinn et al. 1996),what Blackler (1995) refers to as embodied competen-cies. Expertise specialization, then, reduces the cognitiveload of each individual and the amount of redundantknowledge in the group, while collectively providingthe dyad or group access to a larger pool of knowl-edge. What makes transactive memory transactive arethe communications (called transactions) among individ-uals that make possible the codifying, storing, retrieving,and updating of information from individual memorysystems. For transactive memory to function effectively,individuals must have a shared conceptualization of whoknows what in the group.

TMS theory, a theoryof group-level cognition, explains how people in collec-tives learn, store, use, and coordinate their knowledge toaccomplish individual, group, and organizational goals.It is a theory about how people in relationships, groups,and organizations learn who knows what, and use thatknowledge to decide who will do what, resulting in moreefficient and effective individual and collective perfor-mance.

The urgency of the situation meansthat the objective of coordination is to achieve minimallyacceptable and timely action, even when more effec-tive responses may be feasible—but would take longerand use more resources.

hese characteristics require thatemergent response groups adopt specific approaches forknowledge coordination. One such approach commonlydocumented in studies of such groups is their use ofa learn-by-doing (versus decision making) action-basedmodel of coordinated problem solving, in which sensemaking and improvisation are the norm rather than theexception

isaster researchers havedefinedemergent response groupsas collectives of indi-viduals who use nonroutine resources and activities toapply to nonroutine domains and tasks, using nonroutineorganizational arrangements (Bigley and Roberts 2001,Drabek et al. 1981, Drabek 1986, Drabek and McEntire2003, Kreps 1984, Tierney et al. 2001).

Disasters have wideimplications for expertise coordination because the pre-conditions known to facilitate expertise coordination arelimited or nonexistent in disaster response. Such precon-ditions include but are not limited to, a shared goal; aclear reward structure; known group membership, exper-tise, and skills to accomplish the task; and time to sharewho knows what.

Although the con-ventional indicators of efficient coordination—expertisespecialization, credibility in expertise, and coordinationof expertise—are relevant in disaster response, disasterspresent a unique operational environment. Disasters are“events, observable in time and space, in which societiesor their subunits (e.g., communities, regions) incur phys-ical damages and losses and/or disruption of their routine

Experimentation, the third affordance, refers to theuse of technology to encourage participants to try outnovel ideas.

Recombinability refers to forms of technology-enabled action where individual contributors build oneach others’ contributions.

Reviewability refers to the enactment of technology-enabled new forms of working in which participantsare better able to view and manage the content offront and back narratives over time (West and Lakhani2008). By allowing participants to easily and collab-oratively review a range of ideas, technology-affordedreviewability helps the community respond to tensionsin disembodied ideas, because the reviews can provideimportant contextual information for building on others’ideas.

Technology platforms used by OCs can providea number of affordances for knowledge collabora-tion, three of which we mention here: reviewability,recombinability, and experimentation. These affordancesevolve as new participants provide new ways to use thetechnologies, new social norms are developed around thetechnology affordances, and new needs for fresh affor-dances are identified.

Given the fluid nature of OCsand their rapidly evolving technology platforms, and inline with calls to avoid dualistic thinking about tech-nology (Leonardi and Barley 2008, Markus and Silver2008, Orlikowski and Scott 2008), we suggest technol-ogy affordance as a generative response, one that viewstechnology, action, and roles as emergent, inseparable,and coevolving. Technology affordances offer a relationalperspective on human action, where neither the technol-ogy nor the actor is dominant in the sense that the tech-nology does not define what is possible for the actor todo, nor is the actor free from the limitations of the tech-nological environment. Instead, possibilities for actionemerge from the reciprocal interaction between actor andartifact (Gibson 1979, Zammuto et al. 2007). Thus, anaffordance perspective focuses on the organizing actionsthat are afforded by technology artifacts.

third response to manage tensions is to promoteknowledge collaboration by enacting dynamic bound-aries. In social sciences, although boundaries divide anddisintegrate collectives, they also coordinate and inte-grate social action (Bowker and Star 1999, Lamont andMolnár 2002). Fluidity brings the need for flexible andpermeable boundaries, but it is not only the propertiesof the boundaries but also their dynamicity that helpmanage tensions.

We have observed in OCs that no single narrative isable to keep participants informed about the current stateof the OC with respect to each tension. These commu-nities seem to develop two different types of narratives.Borrowing from Goffman (1959), we label the two nar-ratives the “front” and the “back” narratives.

Based on our collective research on to date, we haveidentified that as tensions ebb and flow, OCs use (or,more precisely, participants engage in) any of the fourtypes of responses that seem to help the OC be gen-erative. The first generative response is labeledEngen-dering Roles in the Moment. In this response, membersenact specific roles that help turn the potentially negativeconsequences of a tension into positive consequences.The second generative response is labeledChannelingParticipation. In this response, members create a nar-rative that helps keep fluid participants informed ofthe state of the knowledge, with this narrative havinga necessary duality between a front narrative for gen-eral public consumption and a back narrative to airthe differences and emotions created by the tensions.The third generative response is labeledDynamicallyChanging Boundaries. In this response, OCs changetheir boundaries in ways that discourage or encouragecertain resources into and out of the communities at cer-tain times, depending on the nature of the tension. Thefourth generative response is labeledEvolving Technol-ogy Affordances. In this response, OCs iteratively evolvetheir technologies in use in ways that are embedded by,and become embedded into, iteratively enhanced socialnorms. These iterations help the OC to socially and tech-nically automate responses to tensions so that the com-munity does not unravel.

Tension 5: Positive and Negative Consequences ofTemporary ConvergenceThe classic models of knowledge collaboration in groupsgive particular weight to the need for convergence. Con-vergence around a single goal, direction, criterion, pro-cess, or solution helps counterbalance the forces ofdivergence, allowing diverse ideas to be framed, ana-lyzed, and coalesced into a single solution (Couger 1996,Isaksen and Treffinger 1985, Osborn 1953, Woodmanet al. 1993). In fluid OCs, convergence is still likelyto exist during knowledge collaboration, but the conver-gence is likely to be temporary and incomplete, oftenimplicit, and is situated among subsets of actors in thecommunity rather than the entire community.

ension 2: Positive and Negative Consequencesof TimeA second tension is between the positive and negativeconsequences of the time that people spend contribut-ing to the OC. Knowledge collaboration requires thatindividuals spend time contributing to the OC’s virtualworkspace (Fleming and Waguespack 2007, Lakhani andvon Hippel 2003, Rafaeli and Ariel 2008). Time has apositive consequence for knowledge collaboration. Themore time people spend evolving others’ contributedideas and responding to others’ comments on thoseideas, the more the ideas can evolve

We argue that it is the fluidity, the tensions that flu-idity creates, and the dynamics in how the OC respondsto these tensions that make knowledge collaboration inOCs fundamentally different from knowledge collabora-tion in teams or other traditional organization structures.

As fluctuations in resource endowments arise overtime because of the fluidity in the OC, these fluctua-tions in resources create fluctuations in tensions, makingsimple structural tactics for managing tensions such ascross-functional teams or divergent opinions (Sheremata2000) inadequate for fostering knowledge collaboration.As complex as these tension fluctuations are for the com-munity, it is precisely these tensions that provide thecatalyst for knowledge collaboration. Communities thatthen respond to these tensions generatively (rather thanin restrictive ways) will be able to realize this potential.Thus, it is not the simple presence of resources that fos-ter knowledge collaboration, but rather the presence ofongoing dynamic tensions within the OC that spur thecollaboration. We describe these tensions in the follow-ing section

Fluidity requires us to look at the dynamics—i.e., thecontinuous and rapid changes in resources—rather thanthe presence or the structural form of the resources.Resources may flow from outside the OC (e.g., pas-sion) or be internally generated (e.g., convergence), sub-sequently influencing and influenced by action (Feldman2004). Resources come with the baggage of having bothpositive and negative consequences for knowledge col-laboration, creating a tension within the community inhow to manage the positive and negative consequencesin a manner similar to the one faced by ambidextrousorganizations (O’Reilly and Tushman 2004).

However, failure to examine the critical roleof even the inactive participants in the functioning of thecommunity is to ignore that passive (and invisible) par-ticipation may be a step toward greater participation, aswhen individuals use passivity as a way to learn aboutthe collective in a form of peripheral legitimate partici-pation (Lave and Wenger 1991, Yeow et al. 2006).

Fluidity recognizes the highly flexible or permeableboundaries of OCs, where it is hard to figure out whois in the community and who is outside (Preece et al.2004) at any point in time, let alone over time. Theyare adaptive in that they change as the attention, actions,and interests of the collective of participants change overtime. Many individuals in an OC are at various stagesof exit and entry that change fluidly over time.

We argue that fluid-ity is a fundamental characteristic of OCs that makesknowledge collaboration in such settings possible. Assimply depicted in Figure 1, we envision OCs as fluidorganizational objects that are simultaneously morphingand yet retaining a recognizable shape (de Laet and Mol2000, Law 2002, Mol and Law 1994).

a growing consensus on factors that moti-vate people to make contributions to these communities,including motivational factors based on self-interest (e.g.,Lakhani and von Hippel 2003, Lerner and Tirole 2002,von Hippel and von Krogh 2003), identity (Bagozzi andDholakia 2006, Blanchard and Markus 2004, Ma andAgarwal 2007, Ren et al. 2007, Stewart and Gosain2006), social capital (Nambisan and Baron 2010; Waskoand Faraj 2000, 2005; Wasko et al. 2009), and socialexchange (Faraj and Johnson 2011).

For instance, knowledge collaboration in OCscan occur without the structural mechanisms tradition-ally associated with knowledge collaboration in orga-nizational teams: stable membership, convergence afterdivergence, repeated people-to-people interactions, goal-sharing, and feelings of interdependence among groupmembers (Boland et al. 1994, Carlile 2002, Dougherty1992, Schrage 1995, Tsoukas 2009).

Knowledge collaboration is defined broadly as thesharing, transfer, accumulation, transformation, andcocreation of knowledge. In an OC, knowledge collab-oration involves individual acts of offering knowledgeto others as well as adding to, recombining, modify-ing, and integrating knowledge that others have con-tributed. Knowledge collaboration is a critical elementof the sustainability of OCs as individuals share andcombine their knowledge in ways that benefit them per-sonally, while contributing to the community’s greaterworth (Blanchard and Markus 2004, Jeppesen andFredericksen 2006, Murray and O’Mahoney 2007, vonHippel and von Krogh 2006, Wasko and Faraj 2000).

Online communities (OCs) are open collectives of dis-persed individuals with members who are not necessarilyknown or identifiable and who share common inter-ests, and these communities attend to both their indi-vidual and their collective welfare (Sproull and Arriaga2007).

The situated and emergent nature of coordinationdoes not imply that practices are completely uniqueand novel. On the one hand, they vary accordingto the logic of the situation and the actors present.On the other hand, as seen in our categorizationof dialogic coordination, they follow a recognizablelogic and are only partially improvised. This tensionbetween familiarity and uniqueness of response is atthe core of a practice view of work (Orlikowski 2002).

Recently, Brown and Duguid (2001, p. 208) sug-gested that coordination of organizational knowledgeis likely to be more challenging than coordination ofroutine work, principally because the “elements to becoordinated are not just individuals but communitiesand the practices they foster.” As we found in ourinvestigation of coordination at the boundary, signif-icant epistemic differences exist and must be recog-nized. As the dialogic practices enacted in responseto problematic trajectories show, the epistemic dif-ferences reflect different perspectives or prioritiesand cannot be bridged through better knowledge

nature point to the limitations of a structuralist viewof coordination. In the same way that an organi-zational routine may unfold differently each timebecause it cannot be fully specified (Feldman andPentland 2003), coordination will vary each time.Independent of embraced rules and programs, therewill always be an element of bricolage reflecting thenecessity of patching together working solutions withthe knowledge and resources at hand (Weick 1993).Actors and the generative schemes that propel theiractions under pressure make up an important com-ponent of coordination’s modus operandi (Bourdieu1990, Emirbayer and Mische 1998).

These practices are highly situated, emer-gent, and contextualized and thus cannot be prespec-ified the way traditional coordination mechanismscan be. Thus, recent efforts based on an information-processing view to develop typologies of coordina-tion mechanisms (e.g., Malone et al. 1999) may be tooformal to allow organizations to mount an effectiveresponse to events characterized by urgency, novelty,surprise, and different interpretations.

Our findings also point to a broader divide in coor-dination research. Much of the power of traditionalcoordination models resides in their information-processing basis and their focus on the design issuessurrounding work unit differentiation and integra-tion. This design-centric view with its emphasis onrules,structures,andmodalitiesofcoordinationislessuseful for studying knowledge work.

Boundarywork requires the ability to see perspectives devel-oped by people immersed in a different commu-nity of knowing (Boland and Tenkasi 1995, Star andGriesemer 1989). Often, particular disciplinary focilead to differences in opinion regarding what stepsto take next in treating the patient.

The termdialogic—as opposed to monologic—recognizes dif-ferences and emphasizes the existence of epistemicboundaries, different understandings of events, andthe existence of boundary objects (e.g., the diagnosisor the treatment plan). A dialogic approach to coordi-nation is the recognition that action, communication,and cognition are essentially relational and highlysituated. We use the concept of trajectory (Bourdieu1990, Strauss 1993) to recognize that treatment pro-gressions are not always linear or positive.

A dialogic coordination practice differs from moregeneral expertise coordination processes in that itis highly situated in the specifics of the unfoldingevent, is urgent and high-staked, and occurs at theboundary between communities of practice. Becausecognition is distributed, responsibility is shared, andepistemic differences are present, interactions can becontentious and conflict laden.

xpertisecoordination refers to processes that manage knowl-edge and skill interdependencies

we describe two categories ofcoordination practices that ensure effective work out-comes. The first category, which we callexpertise coor-dination practices, represents processes that make itpossible to manage knowledge and skill interdepen-dencies. These processes bring about fast response,superior reconfiguration, efficient knowledge shar-ing, and expertise vetting. Second, because of therapidlyunfoldingtempooftreatmentandthestochas-tic nature of the treatment trajectory,dialogic coordina-tion practicesare used as contextually and temporallysituated responses to occasional trajectory deviation,errors, and general threats to the patient. These dia-logic coordination practices are crucial for ensuringeffective coordination but often require contentiousinteractions across communities of practice. Figure 1presents a coordination-focused model of patienttreatment and describes the circumstances underwhich dialogic coordination practices are called for.

We found that coordination in a trauma settingentails two specific practices.

Based on a practice view, we suggest the followingdefinition ofcoordination: a temporally unfolding andcontextualized process of input regulation and inter-action articulation to realize a collective performance.

Theprimarygoalispatientstabilizationandini-tiating atreatment trajectory—a temporally unfolding

rauma centersare representative of organizational entities that arefaced with unpredictable environmental demands,complexsetsoftechnologies,highcoordinationloads,and the paradoxical need to achieve high reliabilitywhile maintaining efficient operations.

We sug-gest that for environments where knowledge work isinterdisciplinary and highly contextualized, the rele-vant lens is one of practice. Practices emerge from anongoing stream of activities and are enacted throughthe contextualized actions of individuals (Orlikowski2000). These practices are driven by a practical logic,thatis,arecognitionofnoveltaskdemands,emergentsituations,andtheunpredictabilityofevolvingaction.Bourdieu (1990, p. 12) definespracticesas generativeformulas reflecting the modus operandi (manner ofworking) in contrast to the opus operatum (finishedwork).

In knowledge work, several related factors sug-gest the need to reconceptualize coordination.

Usinga practice lens (Brown and Duguid 2001, Orlikowski2000), we suggest that in settings where work iscontextualized and nonroutine, traditional models ofcoordination are insufficient to explain coordinationas it occurs in practice. First, because expertise is dis-tributed and work highly contextualized, expertisecoordination is required to manage knowledge andskill interdependencies. Second, to avoid error andto ensure that the patient remains on a recoveringtrajectory, fast-response cross-boundary coordinationpractices are enacted. Because of the epistemic dis-tance between specialists organized in communitiesofpractice,theselattercoordinationpracticesmagnifyknowledge differences and are partly contentious.

In this paper, we focus on the collective perfor-manceaspectofcoordinationandemphasizethetem-poral unfolding and situated nature of coordinativeaction. We address how knowledge work is coor-dinated in organizations where decisions must bemade rapidly and where errors can be fatal.

I proposed three new dimensions to considerin conceptualizations of Big Data, which are intendedto nuance and temper some of the grand claims of BigData’s affordances.Key principles from critical and feminist GIS havehere been leveraged to understand the limitations andimpacts of Big Data. Further integration of principlesfrom critical information technologies research willideally seek to show how technologies shape andreproduce uneven social and political relations. Thissort of research can have practical influence on howtechnologies are leveraged, working to ameliorate thepotentially harmful implications of new technologies.More broadly, research critiquing and situating thegeographies of humanitarianism can be integrated intostudies of Big Data digital humanitarianism. Conver-sations around technologies for development andhumanitarianism overwhelmingly bring Western ide-als into non-Western contexts, without considering theimplications of this power relation. Critiquing theserelations should be central to theories of informationtechnologies, with the goal of rectifying and

are certainly not limited to, continued struggles aroundknowledge politics and legitimacy (Burns2014;Elwood and Leszczynski2013), shifting understand-ings of scientific knowledge production (Dalton andThatcher2014; Crampton et al.2013), and increasedneoliberalization of humanitarian aid (Adams2013;Hyndman2009; Polman2010). In other words, theseprocesses take a form specific to Big Data digitalhumanitarianism, and exploring this case sheds greaterlight on these larger-scale processes.

signifies a new epistemology insofar as it portraysevents as discrete and isolated; knowledges as mod-ifiable, categorizable, and abstractable; and locally-situated knowledges as best understood by thoseworking remotely

Not only does the convergence of BigData and humanitarianism depend on a particularsocial shaping of technologies and data, but Big Dataitself embodies particular values, social relations, andepistemologies

Digital humanitarianism can be con-ceptualized as ‘‘the enacting of social and institutionalnetworks, technologies, and practices that enable large,unrestricted numbers of remote and on-the-groundindividuals to collaborate on humanitarian managementthrough digital technologies’’ (Burns2014).

However, discussions of the relationship between BigData and digital humanitarianism tend to be cautiouslyoptimistic. Letouze ́(2012) the challenges facingdigital humanitarianism as falling into five broadcategories: (1) privacy, (2) access/sharing, (3) extract-ing meaning from qualitative text, (4) apophenia, (5)detecting anomalies.

Theseunderstandings of spatial technologies build on les-sons from science and technology studies (STS)research that describes the processes by which dataand technologies come to assume and reify social andpower relations, worldviews, and epistemologies(Feenberg1999; Pinch and Bijker1987; Wajcman1991; Winner1985)

Bor-rowing principles from critical GIS, technologies canbe seen to embody social norms and values (Schuurman2000; Sheppard2005), often reinforcing extant powerdynamics and social inequalities rather than disruptingthem.

. Previously, scholars have generally ignored any notion of time. Now, we need to make explicit our use of time in understanding disaster. Such an application, I believe, will give us a much deeper understanding on defining disaster, how and why such events unfold, and how various social entities attempt to return to normal after the event. Finally, the use of social time in disaster can provide sociologists a deeper look into understanding key theoretical issues related to social order, social change and social emergence, along with voluntaristic versus deterministic patterns of behavior among various units of analysis.

the field. Such a fresh approach possibly improves a wide range of conceptual issues in disasters and hazards. In addition, such an approach would give us insights on how disaster managers, emergency responders, and disaster victims (recognizing that these “roles” may overlap in some cases) see, use and experience time. This, in turn, could assist with a number of applied issues (e.g., warning, effective “response,” priorities in “recovery”) throughout the process of disaster.

Second, I believe that the concept of entrainment could open new doors for understanding post-impact behavior, or the transition from post-impact to pre-impact (or everyday) behavi

The use of social time may also give us a unique view on understanding slow moving disasters (e.g., environmental events, famines and droughts) when compared to sudden impact events. Social time and social disruption provides tools to define disaster without making assessments (i.e., good/bad) of the event.

In this paper I have shown that the application of social time and social disruption to disaster settings (i.e., pre-impact, impact, post-impact) along can provide a unique way to understand disasters. First, by integrating the ideas of event time, social time, and social disruption, we can develop a foundation for creating an empirically based continuum of everyday life/emergency, disaster, and catastrophe. An implication of this approach is that we use specific social criteria (based upon social disruption via the various time concepts) to define the event. As a result, drawing upon social time and social disruption casts a rather wide net in understanding events what we call disa

It should be no surprise recognizing the problematic-theoretical simi­larities between disaster research and its "half-sibling" (e.g., see Wenger 1987), collective behavior. Both disaster research and collective behavior are at a theoretical standstill (e.g., see Aguirre and Quarantelli 1983), and both still rely upon every-day language rather than a broader scheme for describing events (e.g., see Weller and Quarantelli 1973, McPhail 1992). Works by Kreps and Bosworth (1994) and Dombrowsky (1981; 1987), (and perhaps Barton's 1970 classic work) reflect the theoretical attention disaster research needs to build.

The use of disaster periods provides a useful heuristic device for disaster researchers and disaster managers. These various approaches of disaster Phases give researchers an important means to develop research, organize dates, and generate research findings. Similarly, the use of disaster phases benefits disaster managers in attempting to improve their capabilities. Yet, the current use of disaster phases creates broad definitional problems of the field. I show that the current attempts to describe disaster phases are good heuristic devices, but not effective scientific concepts. Yet, scientific, empirical, and theoretical conclusions are drawn from the use of these Phases.

The next logical step to aid analysis would be to cross-tabulate the temporal periods of "before, during, and after" with functional activities. This type of analysis and consideration could be further extended by including both the unit of analysis and various social categories such as social class or ethnicity. This type of three-dimensional approach would also strongly highlight the idea that disaster phases are multilayered. Overall, not only do different groups and units of analysis experience the phases at different times, but that multiple aspects of time (i.e., objective and subjective; before, during, after a disaster) intermesh with specific activities.

We must differentiate whether the use of any phrase refers to temporal or functional aspects of disaster. They should not have multiple meanings

Both researchers and practitioners have seemed to have socially defined some notion of disaster phases for their use. The researchers' job is to create theoretical clarification.

Yet, as Alexander (1982) cautions, good theory must have components of both deterministic and voluntary behavior at all levels of analysis. We do not live in a strictly deterministic world. Thus, as family cycle researchers have learned, we must move with theoretical caution when embracing phases as part of a theoretical model.

Also, with disaster research having strong theoretical ties with the study of collective behavior(Wenger 1987), and with the field of collective behavior often looking at issues related to social change {e.g., riots, social move­ments), another link between disasters and social change has implicitly

The issue of disaster, and phases and social change is an important consid­eration since the "what is a disaster?" debate draws directly upon whether disasters are a "social problem," {e.g., Drabek 1989; Kreps and Drabek 1996), part of a "reconstructionist" approach {e.g., Stallings 1991), or part of social change {e.g., Quarantelli 1987a). I do not see these important aspects of these approaches as contradictory. Interestingly, these three approaches reflect the three main theoretical issues of sociology (see Hinkle 1980): social statics {generally associated with functionalism), social change {generally associated with conflict theory), and social emergence{generally associated with symbolic interactionism).

Cross-cultural disaster research may also provide further insights regard­ing disaster phases.

As the field of collective behavior highlights, individuals in social settings have different perceptions of reality-social settings are not homogeneous (e.g., Turner and Killian I 987).' Thus, to tap further the mutually inclusive, multidimen­sional and social-time aspects of disaster phases, researchers should draw upon multiple publics and their definition of disaster phases.

Consid� e�g the redefinition of disaster phases based on social time may help us WJtb the broader and more important struggle of defining disaster.

Consid� e�g the redefinition of disaster phases based on social time may help us WJtb the broader and more important struggle of defining disaster

D!saster and hazard researchers have recognized the social time aspect of disasters. Dynes_ (1970) alludes to social time regarding the social consequences of a disaster. Dynes observes that social time: is important because the activities of every community vary over a period of time duri�� �e day, the week, the month, and the year. S�c� patterned acuv1nes have implications for potential damage within thecommurnty, for preventative activity within the commu­�ty, for the inventory of the meaning of the disaster, for the rmm�?1ate tasks necessary within the community, and for the mobilizanon of community effort. (Dynes 1970, p. 63)

The Phases Should Reflect Social Rather Than Objective Time Giddens (I 987), although not the first, makes an important theoretical distinction between social and objective time. Giddens defines clock time as the use of quantified units. Clock time represents "day-to-day" structured activities. Typically, studies refer to disaster phases with hours, days, weeks, or years. Social time, however, is contingent upon the needs or opportunities of a society.

Disaster Phases Are Multidimensional Another component of the mutually inclusive nature of disaster phases is that they are multidimensional

Disaster Phases Are Mutually Inclusive As previously indicated, disaster phases overlap. From a theoretical and applied viewpoint, researchers and practitioners must first recognize that disaster phases are not discrete units.

Second, the manner the field handles the issue of disaster phases actually reflects a larger problem in the field. Specifically, how do we define disaster? Kreps (1984, p. 324) comes closest to recognizing the relationship among disaster phases, the theoretical components of disaster (i.e., social order and social action), and the definition of disaster (primarily in a heading in his paper). Unfortunately, he does not elaborate upon the connection of defining disaster and disaster phases. Thus, recognizing and recasting our notion of disaster phases may actually help the field more precisely understand or define "disaster."

Researchers have at times treated the disaster phases as scientific constructs to order data and for scientific analysis. However, as the organizational and family literature show, assumptions based on life-cycle approaches and assumptions often fall outside the realm of appropriate scientific analysis. Here, the phases within the disaster life cycle fall outside the scientific necessity of well-de­fined, mutually exclusive concepts.

One high-level manager involved with the Federal Response Plan made the following reflection about two weeks after Hurricane Andrew occurred: My feeling is that recovery needs to start day one, or even prior to a disaster. It would be wise to set up a group or task force, or a committee. They get together to gather information as the disaster begins. The potential for fragmentation is enormous. It actually goes back to intelligence, damage information. It is difficult to plan for recovery when you do 001 have a sense for how long it could take. You know, recovery has already begun. FEMA has already issued over one million dollars worth of checks .... Anyway, why not have a recovery unit? That would be cool. They should deal the long term recovery within hazard mitigation. In any event that needs to be happening ftom day one.

Finally, the notation of the disaster phases affected emergency-respond­ers' decisions. The lexicon of the four phases appeared to force disaster managers and responders to think and respond in a linear, separate-category fashion. Thus, this paradigm in the end can hurt effective response

Addinonal �g­recovery research by Phillips (1991) shows that different_ categones of disaster victims exit and enter disaster-housing phases at different nmes. She finds that some special-population groups ( e.g., elderly, Hispanics) take a much longer time to transition from temporary to pennanent sheltenng, and from sheltering to temporary and permanent housing than other popu· lation segments.

Of equal importance, both structural-and non­structural-mitigation techniques would lessen dramatically response needs. In essence, effective mitigation and preparation would lessen response time. Logically extended, effective mitigation and preparation when coupled with an effective response could decrease the time for both short-and long-tenn recovery. Tlus analysis further convinced me of the interconnec­tiveness of the disaster periods.

In summary, the ECGs study from DRC showed me that the use of disaster periods created analytical problems. The categories often over­lapped, different groups perceived and experienced the disaster phases differently, and individuals or groups defined differently the actual or potential event

emergent citizen groups (ECGs) in disasters (e.g., Neal I 984, Quarantelli 1985)

Emergency response and recovery is not a linear process; decisions that are made during the emergency phase will impact the recovery process. In practice, however, recovery often takes place in an ad hoc fashion because key decisions are not part of a strategic program to restore services and rebuild communities. (Dumam et al. 1993, p. 30)

Therefore, if disaster researchers wish to improve the theoretical devel­opment of the field dramatically, I argue that we should reanalyze the current heuristic related to the phases.

In fact, the Functions and Effects Study generated the notion that the relationship between mitigation, preparedness, response, and recovery is not even linear. Rather, some preparedness activities (like educating government officials) could really have mitigation effects; and some recovery activities mitigate against future disasters (like using housing Joans to relocate residences out of a flood plain). The Functions and Effects experts hypothesized at least a cyclical relationship among !hese four phases of disaster activity. (National Governor's Association 1979:108)

Others also allude to the fact that these categories are not mutually exclusive. Haas, Kates, and Bowden (1977) make the following important observation:

Despite a positive approach regarding time models, Stoddard concludes the discussion by saying, a simple or complex time model is not comprehensive enough by itself to integrate completely disaster research. Additional con­structs are required for methodological and theoretical compari­sons and liaisons between findings and the various disaster studies. (Stoddard 1968, p. 12)

Since the beginning of the field, disaster researchers have observed various types of disaster periods. Specifically, different events seem to occur at different times related to a disaster. Also, both academics and practitioners assume that these phases exist, and act as if they do exist Yet, in the last 30 years or so, disaster researchers or practitioners have accom­plished little in defining or refining the use of disaster phases. Yet, as I show in the next two sections, both researchers and practitioners have questioned the use of disaster phases since their initial use.

The National Governor's Association Report

Other empirical studies show that the recovery process is not a simple, linear, or cyclical process. Different units or groups may experience, or perceive that they experience, the different stages of recovery I) at different times and 2) at different rates of time.

Overall, recovery studies suggest that subcategories of the recovery process exist. However, different units of analysis (e.g., individual versus group) or different types of groups (e.g., based on ethnicity or social class) may experience the phases of recovery at differing rates. Thus, patterns, phrases or cycles of recovery are not linear.

Phillips' (1991) analysis of housing following the Loma Prieta Earth­quake confirms these different phases. Also, her study shows that different groups of people, often based upon such factors as social class or ethnicity, go through the phases of housing recovery at different times.

The edited work by Haas, Kates, and Bowden ( 1977) illustrates the complexity of the recovery process. Unlike most other overall codification efforts, the above authors explicitly recog­nize that recovery reflects a complex process. They note that people use several subcategories (e.g., restoration, recovery, rehabilitation, redevelop­ment, reconstruction) to describe aspects of the recovery period.

In Drabek's (1986) more recent codification effort, he modifies the disaster phases. His revision reflects the language of the National Governor's Association's 1979 recommendations (i.e., preparedness, response, recovery, mitigation) of disaster phases.

Stoddard argues that the use of time-and-space models in disaster research

By the 1960s, researchers had studied many disasters to allow codifica­tion efforts (Quarantelli and Dynes 1977). For some (e.g., Dynes 1970) disaster periods refer to a temporal category (e.g., before a disaster strikes, while a disaster strikes, after a disaster strikes). In other cases, the use of the phases may refer to functional activities that may or may not also be embedded with temporal considerations (stocking supplies, search and rescue, responding while the disaster strikes, attempting to recovery from the impact). For example, Barton (1970) combines both functional and temporal considerations of disaster. Yet, these and other writers never fully explored the theoretical implications of using the phases in their research

He adds that this phase could be important with sudden impacts, but not as important with slow-moving impacts.

Disasters, Dynes argues, follow a general temporal sequence despite the agent. Dynes em­ploys these phases to argue successfully for an "all hazards" approach to disaster

Mileti, Drabek, and Haas developed their six categories of: 1) preparedness/adjust­ment; 2) warning; 3) pre-impact, early actions; 4) post-impact, short-term actions; 5) relief or restoration, and 6) reconstruction. They justify these categories by noting that "Numerous researchers have documented how activities and nonnative definitions appear to vary across time and vary greatly among events" (Mileti, Drabek, Haas 1975, p. 9). The six phases serve as a central component of the authors' codification effort (it organizes the book chapters). Yet, the authors do not provide a more specific defini­tion for each category. Other theoretical underpinnings in the book receive much more detailed justification (e.g., collective stress, social nature of disaster).

In the context of disaster, social media and other ICTare enablingthe manifestation of a “knowledge commons” [11], a shared information space for victims, onlookers, and the convergent digital volunt

Disasters might be one of the few natural events that override the socio-temporal order; indeed, damage to the routines of social life is a defining characteristic that separates disasters from local emergencies and other disruption

In other words, the articulation work [24], which had to be made explicit previously, became in part implicit by being embedded in the document and in the actions taken upon the document.

Under the stress of the situation, with too many peopledoing too many things at once, the socio-technical infrastructure that underliestheirwork practice wasbreaking down. Star and Ruhleder [25] explain that infrastructure becomes visible only at these points of breakdown. Volunteers directedtheir attention to their social configuration as the critical infrastructure here (the technical infrastructure remains take

Giddens’ theory of structuration explains how social structures, defined as rules and resources or transformational relations, are both the products and the pathways of human action [10]. Employing the concept of duality of structure, Giddens contends that social action both shapes and is shaped by these structures. Orlikowski [20] provides a duality of technology framework for applying structuration theory to research on the role of information technology (IT) within organizational change, whereIT is both the product of human action and a medium of human action, functioning to enable and constrain it. The communication constitutes organization perspective again extends structuration to communicative processes, claiming that communication and the organization co-produce and co-adapt[23], and provides a helpful approach for examining organizing within the virtual organization though the digital traces of its communication [4].

Additional features of the disaster domain are that action is often fast-paced and social structures are emergent [15].

uited. Response and relief work ischaracterized byconvergence of people, information and resources. It is also characterized by improvisation, withvolunteers and formal responders alike innovatively adapting to unique and changing conditions, using resources in new ways, taking on new tasks and assembling into new organizational forms [7,9,15]

Describing the from-scratch conditions of virtual organizing, Finholt et al. write that the “absence of prior structure means group members must develop new structures for sharing information, for example, norms or rules for reporting progress and division of labor” [8p. 292]

relief. Virtual organizations are “geographically distributed [organizations] whose members are bound by a ... common interest or goal, and who communicate and coordinate their work through information technology”[1]

ces. In their study of the digital volunteers who instituted the “disaster desk” in response to the 2011 Peru earthquake,Starbird and Palen [34]reveal how work was restructured in response to the restructuring of the information environment volunteers were working in—which itself was an exasperated response to a confused division of labor and in the end enabled the group to sustain itself relative to its production functions

The desire to assist in disaster events in some way is broad [12, 18], but the mechanisms for enabling action in the form of on-line work or commitment, as with other causes, can beunclear [22, 28, 30].

METHODS

By examiningwork practices, and tracing how those practices are reified in the social-technical organization of a group that is forming and stabilizing as they do the work, we learn not just what this particular group did, but also how the mechanisms by which collective action in digital environments are organizedbottom-up. We also learn how those lessonsaregraduated into prescriptivetop-down direction to sustain and direct future action

Following Orlikowski [29], this analysis unites both practice-based [35]and structurational-basedinterpretations of coordination and social organization [8] to understand the nature of collective work in large, distributed,and emergent groups—groups that havesome existing common motivation to help but have little prior precedent for how that work might be conducted[21]

In the domain of pet advocacy, the latent potential for crowd interaction comes fromintrinsic and extrinsic motivations—we focus on how that potentialwas transformed intoa viable form of distributed, decentralized cooperative work.

As Rosner [35] explains, this goes beyond the “affordances” of objects [28] and instead goes to what the tools represent to their craft and their expert execution of w

Furthermore, tolink this back to the matter of expertise, we see thatexpertise was displayed through material objects:people wore clothing that was consistent with their identification as equine experts (such asboots and cowboy hats),and the Posse memberswore theiruniforms.At the ranch, onejob was to hand out halters and lead ropesto riders. If riders’preferred materials were not available,their expertise allowed them to adapt to what was at

Calling upon media theory, which considers how mass media frames and focusesthekind ofattention an eventreceives,e.g., [4,8], social media can do the same.

priori. Such is the situation with disaster.We easily dismisshow uncertainsituations of disaster areor can become, and how a goalin safety-critical work is to avert situations beforethey become problems. Much of the work in safety-and time-critical matters in CSCW appreciates the implications of this goalon vigilance, mutual awareness, and, of course, error, especially propagated error. It is all too easy to blame “pilot error” when a sequence of preceding systemic conditions took place to set a pilot up for perceiving the problem as he or she did [34,48], including one that warns of hazard. Indeed, disaster can magnifyproblems, not necessarily out of proportion, though that can happen, but rather too so that wefocusonspecific detailswhen many things are happening.

Expertise is a type of embedded knowledgedeveloped within a cultural, social and cognitive environment[6].Expertiseistheability to apply knowledge in different contexts[6], including in emergent situations that require experts to improvise, as Normark and Randall note [29]

Mendonça, et al.[26] and Kendra and Wachtendorf [20] have characterized this as improvisation, whichhas strong parallels to the conversations in CSCW about the nature of situated cognition or situated work [14,44], as well as the relationship between informal as well as formal aspects of work [30,44]

Threaded throughout thesearguments is the idea of distributed cognition particularly as it materializes in the on-the-ground work, but also through prior online preparation.Through this lens, we see how ideation ofsolutions sprung from uncertainexpressions ofproblem statementswhich were quickly forwardedto the local (or local enough) domain experts—horsepeople in Colora

Ethnographic Investigation

Finally, a maincontribution of this research lies in the examination of the solicitation of expertise in a digitally-connected world, where widely distributed and diverse expertise must nevertheless be realized under highly localized conditions.

We see how problem definition, work articulation [37], and the materiality of work[27,35] come together to make the work happen in asocially-, spatially-, and temporally-distributed matter[14].

We see howperformances aroundpaperwork intended to connect the online to the offlineare once again superficial[44], and that the offline work is refiguredat the very endprimarily to communicate its successful completion back to a waiting, online crow

In this online-meets-offline account of cooperative work, we see connections to the classic literature in CSCWaround matters of mutual awareness in safety-critical systems[12]that is partially achieved online andonly “satisficingly”[38] achieved

Disconnection Between Offline & Online ResponseIndeed, amajor criticism of much current crisis social mediaresearch is that it does not consider the relationship between online work and offline or on-the-ground activities(Wulf, et al.[49]is a notable published location, and it isadiscussion often brought up at conferencesand in paper reviews). It is an important conce

n particular, we note how recent extensions to Activity Theory have addressed theoretical shortcomings similar to our five challenges and suggest directions for bridging the gap between everyday practice and systems support

These extensions increase the complexity of the Activity Theory model but also help to explain tensions present in real-world systems such as when one agent plays different roles in two systems that have divergent goals. Furthermore, this approach provides Activity Theory with a similar degree of agility in representing complex, distributed cognition as competing theoretical approaches, such as Distributed Cognition (Hutchins, 1995).

In the world of planning and wicked problems no such immunity is tolerated. Here the aim is not to find the truth, but to improve some characteristics of the world where people live. Planners are liable for the consequences of the actions they generate; the effects can matter a great deal to those people that are touched by those actions.

In dealing with wicked problems, the modes of reasoning used in the argument are much richer than those permissible in the scientific discourse. Because of the essential uniqueness of the problem (see Proposition 7) and lacking opportunity for rigorous experimentation (see Proposition 5), it is not possible to put H to a crucial test.

Here lies a difficulty with incrementalism, as well. This doctrine advertises a policy of small steps, in the hope of contributing systematically to overall improvement. If, however, the problem is attacked on too low a level (an increment), then success of resolution may result in making things worse, because it may become more difficult to deal with the higher problems. Marginal improvement does not guarantee overall improvement.

Of course, for any two problems at least one distinguishing property can be found (just as any number of properties can be found which they share in common), and each of them is therefore unique in a trivial sense. But by "'essentially unique" we mean that, despite long lists of similarities between a current problem and a previous one, there always might be an additional distinguishing property that is of overriding importance. Part of the art of dealing with wicked problems is the art of not knowing too early which type of solution to apply.

In such fields of ill-defined problems and hence ill-definable solutions, the set of feasible plans of action relies on realistic judgment, the capability to appraise "exotic" ideas and on the amount of trust and credibility between planner and clientele that wilt lead to the conclusion, "OK let's try that."

Whenever actions are effectively irreversible and whenever the half-lives of the consequences are long, every trial counts. And every attempt to reverse a decision or to correct for the undesired consequences poses another set of wicked problems, which are in turn subject to the same dilemmas.

With wicked problems, on the other hand, any solution, after being implemented, will generate waves of consequences over an extended--virtually an unbounded-- period of time.

The planner terminates work on a wicked problem, not for reasons inherent in the "logic" of the problem. He stops for considerations that are external to the problem: he runs out of time, or money, or patience.

For wicked planning problems, there are no true or false answers. Normally, many parties are equally equipped, interested, and/or entitled to judge the solutions, although none has the power to set formal decision rules to determine correctness. Their judgments are likely to differ widely to accord with their group or personal interests, their special value-sets, and their ideological predilections. Their assess- ments of proposed solutions are expressed as "good" or "bad" or, more likely, as "better or worse" or "satisfying" or "good enough."

The information needed to understand the problem depends upon one's idea for solving it. That is to say: in order to describe a wicked-problem in sufficient detail, one has to develop an exhaustive inventory of all conceivable solutions ahead of time. The reason is that every question asking for additional information depends upon the understanding of the problem--and its resolution--at that time. Problem understanding and problem resolution are con- comitant to each other. Therefore, in order to anticipate all questions (in order to anticipate all information required for resolution ahead of time), knowledge of all conceivable solutions is required.

The formulation of a wicked problem is the problem! The process of formulating the problem and of conceiving a solution (or re-solution) are identical, since every specification of the problem is a specification of the direction in which a treatment is considered.

By now we are all beginning to realize that one of the most intractable problems is that of defining problems (of knowing what distinguishes an observed condition from a desired condition) and of locating problems (finding where in the complex causal networks the trouble really lies). In turn, and equally intractable, is the problem of identifying the actions that might effectively narrow the gap between what-is and what-ought-to-be.

The manner in which we isolate supposedly discrete "figures" from their surrounding "ground" is also manifested in the way we come to experience ourselves. 52 It involves a form of mental differ­entiation that entails a fundamental distinction between us and the rest of the world. It is known as our sense of identity.

It is boundaries that help us separate one entity from another: "To classify things is to arrange them in groups ... separated by clearly determined lines of demarcation .... At the bottom of our conception of class there is the idea of a circumscription with fixed and definite outlines. "7 Indeed, the word define derives from the Latin word for boundary, which is finis. To define something is to mark its boundaries, 8 to surround it with a mental fence that sepa­rates it from everything else. As evidenced by our failure to notice objects that are not clearly differentiated from their surroundings, it is their boundaries that allow us to perceive "things" at all.

es an entity with a distinctive meaning5 as well as with a distinctive identity that sets it apart from everything else. The way we cut up the world clearly affects the way we organ

The need to substantiate the way we segment time into discrete blocks also ac­counts for the holidays we create to commemorate critical transition points between historical epochs 112 as well as for the rituals we de­sign to articulate significant changes in our relative access to one another-greetings, first kisses, farewell parties, bedtime stories. 113

Most of the fine lines that separate mental entities from one another are drawn only in our own head and, therefore, totally in­visible. And yet, by playing up the act of "crossing" them, we can make mental discontinuities more "tangible." Many rituals, indeed, are designed specifically to substantiate the mental segmentation of reality into discrete chunks. In articulating our "passage" through the mental partitions separating these chunks from one another, such rituals, originally identified by Arnold Van Gennep as "rites of passage,"107 certainly enhance our experience of discontinuity.

Nonetheless, without some lumping, it would be impossible ever to experience any collectivity, or mental entity for that matter. The ability to ignore the uniqueness of items and regard them as typical members of categories is a prerequisite for classifying any group of phenomena. Such ability to "typify"106 our experience is therefore one of the cornerstones of social reality

A mental field is basically a cluster of items that are more similar to one another than to any other item. Generating such fields, therefore, usually involves some lumping.

Such mental geography has no physical basis but we experience it as if it did

Like them, all frames basically define parts of our percep­tual environment as irrelevant, thus separating that which we attend in a focused manner from all the out-of-frame experience44 that we leave "in the background" and ignore.

A frame is characterized not by its contents but rather by the distinctive way in which it transforms the contents' meaning.

Framing is the act of surrounding situations, acts, or objects with mental brackets35 that basically transform their meaning by defining them as a game, a joke, a symbol, or a fantasy

Crossing the fine lines separating such experiential realms from one another involves a considerable mental switch from one "style" or mode of experiencing to another, as each realm has a distinctive "accent of reality. "30

Temporal differentiation often entails an experience of disconti­nuity among different sorts of reality as well.

Temporal differentiation helps substantiate elusive mental dis­tinctions. Like their spatial counterparts, temporal boundaries often represent mental partitions and thus serve to divide more than just time.

In order to endow the things we perceive with meaning, we normally ignore their uniqueness and regard them as typical mem­bers of a particular class of objects (a relative, a present), acts (an apology, a crime), or events (a game, a conference).2 After all, "If each of the many things in the world were taken as distinct, unique, a thing in itself unrelated to any other thing, perception of the world would disintegrate into complete meaninglessness. "3 Indeed, things become meaningful only when placed in some category.

The perception of supposedly insular chunks of space is probably the most fundamental manifestation of how we divide reality into islands of meaning. Examining how we partition space, therefore, is an ideal way to start exploring how we partition our social world

By ignoring the diversity and discord of the ‘goals’ of theparticipants involved, the differentiation of strategies, and the incongruence of theconceptual frames of reference within a cooperating ensemble, much of the currentCSCW research evades the problem of how to provide computer support for peoplecooperating through the establishment of a common information space.

On the one hand, the visibility requirement is amplified by this divergence. Thatis, knowledge of the identity of the originator and the situational context motivat-ing the production and dissemination of the information is required so as to enableany user of the information to interpret the likely motives of the originator. On theother hand, however, the visibility requirement is moderated by the divergence ofinterests and motives. A certain degree of opaqueness is required for discretionarydecision making to be conducted in an environment charged with colliding inter-ests. Hence,visibility must be bounded.