A resources model for distributed sensemaking

In the field of Naturalistic Decision Making, the Data-Frame Model (DFM) has proven to be a popular and useful way of thinking about sensemaking. DFM provides a parsimonious account of how ‘sensemakers’ interact with the data in their environment in order to make sense of what is happening. In this paper, however, we argue that it is useful to elaborate DFM in several ways. We begin by arguing for the idea of sensemaking as a quest for coherence, an idea that we see as entirely consistent with the DFM. We then present some examples of sensemaking studies and use these to motivate a Distributed Resources Model of Sensemaking. This model uses the notion of resources for action, as resources that can be flexibly drawn upon in both choosing courses of action and accounting for the actions of oneself and of others (as opposed to prescriptions or mechanisms that determine behaviour in any strict way). It describes resources involved in sensemaking in terms of three domains: Knowledge and Beliefs, Values and Goals, and Action. Knowledge and beliefs are concerned with how things are; Values and Goals are concerned with how things are desired to be; and Action provides the means for redressing the gap. Central to the model is the idea that these resources can be distributed across a cognitive work system across actors and representational media. Hence, it aims to provide a framework for analysing sensemaking as Distributed Cognition

An approach to human-machine teaming in legal investigations using anchored narrative visualisation and machine learning

During legal investigations, analysts typically create external representations of an investigated domain as resource for cognitive offloading, reflection and collaboration. For investigations involving very large numbers of documents as evidence, creating such representations can be slow and costly, but essential. We believe that software tools, including interactive visualisation and machine learning, can be transformative in this arena, but that design must be predicated on an understanding of how such tools might support and enhance investigator cognition and team-based collaboration. In this paper, we propose an approach to this problem by: (a) allowing users to visually externalise their evolving mental models of an investigation domain in the form of thematically organized Anchored Narratives; and (b) using such narratives as a (more or less) tacit interface to cooperative, mixed initiative machine learning. We elaborate our approach through a discussion of representational forms significant to legal investigations and discuss the idea of linking such representations to machine learning

Exploring leaders\u27 sensemaking of emergent global norms for open science: a mixed methods discourse analysis of UNESCO’s multistakeholder initiative

In November 2021, all 193 United Nations Member States adopted the United Nations Educational, Scientific, and Cultural Organization’s (UNESCO) Recommendation on Open Science (UNESCO, 2021a), which signaled a shared commitment to globally recognized standards for open science. However, as with other normative instruments established by intergovernmental organizations (IGOs) such as UNESCO, the ways in which local, national, and regional leaders will implement the recommendation can and will vary (Finnemore, 1993). Top-down and bottom-up coordination across international stakeholders in the research system is critical for the framework to be effective in driving global policy implementation and enabling sustained research culture change. Such international coordination necessitates an understanding of the complex economic, socio-political, and cultural dimensions that exist among these stakeholders and may influence local implementation efforts and norm-setting (Martinsson, 2011; Nilsson, 2017). This mixed methods study explores leaders’ sensemaking of emergent global norms for open science through public discourse during the development of UNESCO’s recommendation. The central research question is: How did institutional leaders make sense of emergent global norms for open science during UNESCO’s multistakeholder initiative? The study is situated at the intersection of systems thinking, global norms, and sensemaking, using a social constructionist lens. A synthesis of study findings draws two conclusions: That there is evidence in the discourse of accelerating self-organization toward open science among Member States who responded to UNESCO’s call for commentary on the draft recommendation; and that there is also evidence in the discourse of a degree of instability around prospective norm diffusion and internalization of the Recommendation on Open Science (2021a) related directly to matters of implementation. The tension between emergence and instability is well documented throughout the literature across complex systems, global norms, and sensemaking. Therefore, the study supports the ongoing exploration of global norms development and, specifically, the critical progression from norm emergence to norm diffusion. Given the theoretical coherence of complex systems, global norms, and sensemaking as evidenced throughout the findings, the novel integrative analytic frame that was developed during the design of this study may support other global norms development studies

Den kompetente endringsagent: Innovasjon i distribuerte organisasjoner

Formålet med avhandlingen er å bidra med kunnskap om hvordan endringsagenter bistår med læring og kunnskapsflyt i innovasjonsprosesser i distribuerte organisasjoner. Distribuerte organisasjoner er geografisk spredt, og makt, kunnskap og autonomi er distribuert til den enkelte node. Distribuering av disse elementene kan føre til motstridene behov, forventinger og krav fra de ulike nodene. Disse motsetningene kan forstås som paradokser som skaper en opplevd avstand i organisasjonen, ved at nodene tolker og anvender kunnskap ulikt. Ettersom kunnskap kan forstås som det viktigste råstoffet for innovasjon, er det avgjørende at nodene har en opplevd nærhet, slik at de kan ivareta læring og kunnskapsutveksling. Ved hjelp av fem artikler og «kappa» belyser avhandlingen endringsagentens kompetanse til å styrke den opplevde nærheten for å ivareta og utvikle læring, kunnskapsflyt og innovasjon. Avhandlingen er basert på en kvalitativ casestudie, der det er benyttet intervju, observasjon, gruppediskusjoner og dokumentanalyse. Denne trianguleringen har bidratt til et omfattende empirisk grunnlag som har generert dybdekunnskap omkring endringsagentens innvirkning og støttefunksjon i lærings- og kunnskapsprosesser i distribuerte organisasjoner. Resultatene viser at mellomlederen og HR som endringsagenter balanserer paradokser og tilpasser seg ulike distribuerte miljøer, og at personlige egenskaper er avgjørende for å lykkes. Funnene viser at det ikke er noen standardisert praksis for hvordan endringsagenter støtter innovasjonsprosesser i en distribuert organisasjon. Avhandlingen gir derfor en dypere forståelse av paradoksene endringsagenten håndterer. Den kompetente endringsagent trenger ferdighetene til å balansere nærhet/avstand mellom nodene – for å ivareta et nødvendig spenningsnivå. Spesielt kunnskapen om hvilke barrierer som må brytes ned, og hvilke som må bestå for å ivareta balansen mellom generalisering og spesialisering av kunnskap er viktig for å ivareta innovasjonsgrunnlaget. Den karismatiske evnen til å motivere til endring, samt en holdning om at kommunikasjonen må tilpasses ut ifra nodenes persepsjonsnivå, er også viktig kompetanse for å lykkes som endringsagent i en distribuert organisasjon. Avhandlingen har bidratt én overordnet debatt. Debatten retter et kritisk blikk på de statiske fasene i endring, og fremhever en mer aktiv endringsagent. Gjennom sin praksis viser endringsagenten oss sin kompetanse til å balansere nodenes paradoksale behov, forventinger og krav. Dette gir en ny forståelse for hvordan endringsagenter fremmer nærhet og derigjennom bidrar i debatten i nærhets- og avstandsteoriene, hvor endringsagenten kan sees på som en nærhetsfaktor som styrker innovasjonsgrunnlaget.Abstract The purpose of the thesis is to contribute with knowledge about how change agents assist with learning and knowledge flow in innovation processes in distributed organisations. Distributed organisations are geographically dispersed where power, knowledge and autonomy are distributed to the individual node. Distribution of these elements can lead to conflicting needs, expectations and demands from the various nodes. These contradictions can be understood as paradoxes that create a perceived distance in the organisation, where the nodes interpret and apply knowledge differently. As knowledge can be understood as the most important raw material for innovation, it is crucial that the nodes have a perceived proximity to ensure learning and knowledge exchange. With the help of five articles and a "kappa", the thesis looks at the change agent's competence to strengthen this perceived proximity to increase learning, knowledge flow and innovation. This thesis is based on a qualitative case study where interviews, observations, group discussions and document analysis have been used as methodological techniques. This triangulation has contributed to an extensive empirical basis that has generated unique indepth knowledge about the change agent's support function in distributed organisations. The results show that the middle manager and HR as change agents balance paradoxes and adapt to different distributed environments; they also demonstrate that personal characteristics are crucial for success. The findings reveal that there is no standardised practice for how change agents support innovation processes in a distributed organisation. The thesis therefore provides an increased understanding of the paradoxes the change agent handles. The competent change agent needs the skills to balance proximity/distance between the nodes in order to ensure a necessary level of tension. In particular, the knowledge of which barriers must be broken down, and which must remain in order to safeguard the balance between the generalisation and specialisation of knowledge, is important for the basis for innovation. The charismatic ability to motivate change and the facility to adapt communication based on the nodes' perception are important competences for a change agent in a distributed organisation. This thesis has contributed to one overall debate. The debate takes a critical look at the static phases of change and highlights a more active change agent. Through his practice, the change agent shows us his competence to juggle between roles in order to balance the nodes' paradoxical needs, expectations and demands. This gives a new understanding of how change agents promote proximity and contribute to the proximity and distance theories where the change agent is a creator of innovation.publishedVersio

A resources model for distributed sensemaking

In the field of Naturalistic Decision Making, the Data-Frame Model (DFM) has proven to be a popular and useful way of thinking about sensemaking. DFM provides a parsimonious account of how ‘sensemakers’ interact with the data in their environment in order to make sense of what is happening. In this paper, however, we argue that it is useful to elaborate DFM in several ways. We begin by arguing for the idea of sensemaking as a quest for coherence, an idea that we see as entirely consistent with the DFM. We then present some examples of sensemaking studies and use these to motivate a Distributed Resources Model of Sensemaking. This model uses the notion of resources for action, as resources that can be flexibly drawn upon in both choosing courses of action and accounting for the actions of oneself and of others (as opposed to prescriptions or mechanisms that determine behaviour in any strict way). It describes resources involved in sensemaking in terms of three domains: Knowledge and Beliefs, Values and Goals, and Action. Knowledge and beliefs are concerned with how things are; Values and Goals are concerned with how things are desired to be; and Action provides the means for redressing the gap. Central to the model is the idea that these resources can be distributed across a cognitive work system across actors and representational media. Hence, it aims to provide a framework for analysing sensemaking as Distributed Cognition