Tag Archives: sociomaterial

The Twitter Experience

For all the structuring effects of the Twitter functional features, the Twitter experience is generally perceived as a private one as only the individual user can see their Twitter feed, as they have structured it, on their particular screen configuration (Gillen and Merchant 2013). This aspect of the individualisation and heterogeneity of public and open textual communication adds to the complexities of interpreting, analysing and making sense of Twitter. Gillen and Merchant’s (2013) discussion of the capacity of Twitter users to organise the flow of discourses they are presented seems to ignore both the algorithmic impositions of, for example, Trending terms in that interface as well as the effects of the content of individual Tweets being perceived as a coherent informational flow or a chaotic mess of impressions (or both). The Twitter user experience is not an isolated or individualised one but is, rather, an entanglement of heterogeneous intentions, business logics, coded protocols, algorithmic outputs, collective norms and individual perceptions.

It is this entanglement between the human and material that opens, closes and patterns or orders the particular uses of Twitter. Twitter is constantly and actively made and remade in the intra-actions of user behaviours, hardware, coding, algorithms and visual design, rather than Twitter being a neutral utility or passive instrument.

Making & Breaking Rules in IT Rich Environments

These are my notes taken during the presentation and then tidied up a bit in terms of spelling and sense – so they may well be limit, partial and mistaken!

Prof Kalle Lyytinen, Case Western Reserve University.

The welcome came from Robin Williams noting that Kalle has a wide range of  appointments and  research interests and often acts as abridge builder across different subject disciplines and between American and European research communities. Kalle has been particularly supportive around research in IT infrastructures and in supporting the development of research communities on IT infrastructure.

Kalle starts the presentation with a discussion of the background of this paper that has been developing over the last five years. His research is positioned within science and technology studies (STS) but with a more behaviourist focus. This paper investigates issues of regulation which is fundamental to social interactions through establishing what is and is not acceptable behaviour within a specific context.

The example of the Securite Generale fraud by Jerome Kerviel who fooled the control systems to undertake fraudulent trading resulting in losses for the bank of approximately €5bn. This fraud was contrasted the old fashioned approaches to bank robbery and the regulatory regimes aimed at preventing such robberies to highlight that digital banking require new and different regulatory regimes.

IT systems embed rules that have regulatory functions on access to and the use of resources. Yet a key concern remains with how social actors comply with and work around these rules. So this research is concerned with how IT can be seen as materially based organisational regulation in interaction with the social.

What is a rule? Rules tend to be defined as a purely social statement on the expectations on behaviours by participants in a system and it is assumed that such rules are generally reciprocal. The expectations should create stabilities of behaviour yet are not mechanistic and so variances occur through misunderstanding, reinterpretation and resistance. For organisations, what is key is the materiality of rules through systems, processes, expressions in space design and so forth, that also generate stability over space and time. Regulation combines social and material components intertwined in a practice that decrease variance in behaviours and also facilitate the coordination of collective action.

Regulation is a meeting point of tensions between structure and agency raising questions on, for example, centralisation vs decentralisation of decision-making.

An IT system is a dynamic and expansive resource through which regulatory power is exercised by materialisation of rules. Rules are stored, diffused, enforced through IT. Rules encode and embed rules (Latour 1996, 2005) while rules become more complex through IT systems that allow complex combinations of rules. IT can track, record and identify events on a large scale and high speed and low cost – which is where big data can help identify and enforce new rules. Through IT, regulation becomes less visible as it is embedded in, for example, user-interfaces.

The example of high frequency trading and how IT rules are established that limit what types of trades can be operationalised – see Lewis’ Flashboys book.

Regulation has three dimensions: 1. the Rules that are materialised as a 2. IT artefact that is interdependent on 3. practices. Rules are coupled overtime with practices (such that the rule may be forgotten as it is embedded in the IT artefact.

IT regulation research in 1970s to 90s viewed regulation as oppressive and deterministic and in 1990s+ research was more concerned with deviation in practice. Alot of research in regulation positioned IT as a contextual variable while a much smaller number looked specifically at the IT in terms of materialisation, enactment of rules in practices and in the temporal aspects (Leonardi 2011). So research on IT and Regulation is limited.

Research to focus on sources of co-existence of multple IT based regulations generating heterogeneous and conflicting regulations so has multiple consequences.

Our focus is on practices of maintaining and transforming rules that mediate collective activity. Regulations are based on three types of origins: (i) autonomy where people agree on behaviours; (ii) control-orientated, explicit rules and laws based; or (iii) joint. The research is interested in practices in IT rich environments as rules become more invisible as they are ‘inscripted’ in to technology and/ or material. The same rule can be embedded in different ways, eg, speeding rules embedded in speed bumps and/ or in vocal warning from speedometer.

The study was a 7 year longitudinal study of regulatory episodes in a virtual learning environments. How teaching and learning behaviours are regulated through the VLE. Data was gathered from email logs, interviews and document analysis. The analysis focused on critical incidents, simple statistics and lexical analysis of emails.

The research questions were: 1. what is the focus of the regulatory episodes and 2. what was the temporal coupling between regulation and behaviour. The VLE provides a rich environment with alternative forms of regulation, dynamic in terms of wider changes in higher education, rules embedded in the application and how it is used.

Five types of regulatory episodes, all of which changed over time:

1. functional – restrictions on how users use the VLE based on the functionality of the VL

2. Tool orientated – specific tools are imposed for specific activities

3. Role orientated – which roles can use which aspects of the VLE

4. Procedure orientated – where learning processes such as course activities are practiced in new ways

5. Opportunity orientated.

Material regulation is dominant in functional and tool orientated rules while the social was dominant in role and procedure orientated rules.

The complexity of the multiplicity of rules and sources of rules led to confusion and difficulties in enforcing rules but, with low levels of constraint, were also sources of innovation in practices. Also, increasing the formal limits of the IT systems generated conflict over the rules.

As the operationalisation of the VLE continued over time so the complexity and volume of rules increased.

Over time the central administration of the university asserted increased control over the VLE for purposes of efficiency and uniformity of provision but also to legitimise its existence. But this increased control also removed a lot of local innovations. The materialisation of the rules in the VLE enabled greater centralised control. But also that IT choices then limits what future flexibility may be possible.

 

 

Digital Scholarship day of ideas: data

Live notes from the day.

Starting the day with Dorothy Meill, Head of CHSS introducing the third annual day of ideas as a forum for those interested in digital scholarship across the University and College. Today has a mixture of internal and external speakers. Also mentions the other digital HSS activities including the website and the other events listed there.
Todays’ focus is on data as a contested but popular term. What does it mean for HSS and what traction does it have in the humanities and what currency does big data have for humanities and what are the implications for the computational turn for digital scholarship?
The event is being streamed on the website and the presentations will be posted there later.

Sian Bayne introducing Annette Markham as a theorist of the internet and is currently at Aarhus University. Her focus is on ethnographic research and the ethics of online research. She also has a good line on paper titles.

Annette Markham asking “‘Data’ what does that mean anyway?”. For the last five years or so she has been particularly pushing at thinking about method to better represent the complexities of 21st Century life. She works with STS, informatics, ethnographers, social scientists, linguists, machine learning scholars etc. The presentation is based on a series of workshops published in First Monday special issues October 2013.
Annette argues that we need to be careful about using the term data as it assumes we’re all meaning the same term. Taking a post-humanist perspective or at least non-positivist stance. It is our repsonsibility to critique the word “data”. For other researchers, data and big data are terms that seem unproblematic.

Annette is providing an overview of the debates on data and a provocation to start the day. Asking what does method mean for our forms of inquiry requires ‘method’ to be looked at sideways or from above and below ‘method’ to take account of  the epistemological and political conditions for inquiry. Such conditions include funding constraints and demands around, for example, developing evidence bases and requirements for the archiving of data. But the latter is problematic in terms of capturing and tracing ethnographic research and ‘data’. Also look below ‘method’ in terms of the practices of inquiry that involve the gathering and analysing of data as well as the practices of “writing up”.
The notion of framing inquiry (Goffman) involves drawing attention to some things and excludes others – those outside the frame. Changes the frame changes the focus of inquiry and perspective of the phenomenon. Different images such as frames, a globe/ sphere, a cluster of connected nodes (sociogram or DNA) are used to critique the notion of a ‘frame’. A frame guides our view of the world but is often invisible until it is disrupted. So it is important to make the frame visible.
The term data acts as a frame but is highly ambiguous yet is often perceived as being universally understood, eg, not visible as a framing mechanism.
How are our research sensibilities being framed? To understand the question, we need to ask how are we framing culture, objects and processes of analysis and how do we frame legitimate inquiry. Culture is framed in internet studies through the changes due to the internet, as a networked culture but also how our understanding of the internet as embodied informational spaces. Interfaces developed from an interest in architecturalised spaces towards standardised interfaces to simplification as represented by Google. This is linked to the rise of commercial interests in the internet. the frame of objects and processes of inquiries has not changed much and not changed sufficiently. Inquiry involves entangled processes of social interaction online yet methods remain largely based on 19th century practices. Research models are generally based on linear processes (deductive) which acts to value linear research over messy and complex. We are still expected to draw conclusions for example. The framing of legitimate inquiry has gone backwards from the feminist work on situated knowledge and practice in the 1960s towards evidence and solutions based practices.
So what is data? An easy term to toss around to cover a lot of stuff. It is a vague term and arguably powerful rhetorical term shaping what we see and think. The term comes from 18th century sciences and popularised via translation of scientific works. As a term, ‘data’ was used as preceding an argument or analysis so data is unarguable and pre-existing – it has an “itness”. Data cannot be falsified. Data as a term refers to what a research seeks and needs for inquiry. Yet there are alternative sociological approaches involving the collection of ‘material’ to construct ‘data’ through practices of interpretation. So a very different meaning from ‘data’ as more widely used.
Refers to boyd and Crawfords 2011 provocations on big data and Baym’s 2013 work arguing that all social metrics are partial and non-representative and thereis ambiguity involved in decontextualising material from its context.
Technology now pervasive in everyday life as repsented in a Galaxy S II advert. Experiences are flattened and equalised with everything else and than flattened again as informational bits that can be diffused shared through technology.
Humans as data argument. She has nothing against data and computational analysis as such analysis is important and powerful. But wants to critique the idea that data speaks for itself and that human interaction with technology produces just data. Not all human experience is reduceable to data points. Data is never raw, it is always filtered and framed. Data operates in a larger framework of inquiry and other frameworks of inquiry exist that do not focus on data. Rather, this is inquiry that is focused on the analysis of phenomena involving play around with understanding that phenomena (not data).
Data functions powerfully as a term and acts as a frame on inquiry and this should be subject critique. Inquiry can and should be playful and generative in its entanglements with ‘the world’.

Q: what is the alternative to data? What is human experience reducible to?
A: that’s not the key question. We don’t want to think in terms of reduction which is how data generally frames inquiry.

 

This talk was followed by a fascinating use of crowd-sourced data coding by Prof Ken Benoit. This included completing an analysis of a UKIP manifesto during the course of the talk via cloudflower.

Space & flows of practice: exploring the relationship between Web 2.0 technologies and a practice perspective on HRD.

Here is a paper abstract accepted for the upcoming UFHRD conference in Brighton:

This paper explores through an analysis of technology enhanced professional learning (TEPL) using social software a practice based approach to understanding and framing human resource development (HRD) and communities of HRD practitioners. Social software has been described as employing web 2.0 technologies in supporting ‘digital social networks’ supporting interactions between social entities (Kieslinger & Hofer 2007, p7) through computer-mediated-communication to form online communities (McAfee 2009). These technologies can include applications such as blogs and micro-blogs, discussion forum, wikis, etc. (Wagner & Bollojou 2005). The use of social media to enable collaborative and peer-to-peer professional development activities has become increasingly common in recent years (McCulloch, et al 2011; Bingham and Conner 2010).

The practice perspective perceives learning and knowledge as relational processes (Cook & Brown 2005) where learning is understood as a social, collective and active process. Learning and knowledge are not possessed (Cook & Brown 2005) but rather are something that people do together (Geiger 2009). In the context of TEPL it can be seen that the main mechanism of practice is textual (Koole 2010). Hakkarainen (2009) points specifically to technologies that generate epistemic artefacts providing a material representation in the digital world of agents’ intangible ideas. Online, such artefacts can be seen specificially as text or discourse objects (Bartel & Garud 2003). So through TEPL using social software, practices are interactions between people and these discourse objects (Orlikowski 2007; Hussenot & Missonier 2010). This interaction can be understood as a process of learning where actors in a network (Aceto et al 2010, p6):

…learn by making and developing connections (intentionally or not) between ideas, experiences, and information, and by interacting, sharing, understanding, accepting, commenting, creating and defending their own opinions, their viewpoints, their current situations and their daily experiences.

Furthermore, such objects and interactions generate consequences that are separate from the intentions of the original authors (Alvesson and Skoldberg 2009, p234).

Lawless et al (2011) describe human resource development as a social and discursive construct. HRD as a can be seen as a practice that is defined by how it is discussed and what discursive resources are mobilised in the practice of HRD (Francis 2007).

This paper explores how HRD practices are assembled in networks (Fenwick 2010) in open online environments for TEPL. The study research sites are two regular open Twitter “chat” events focused on HRD practices and as a learning resource for participating in the events. The research approach uses Actor-Network Theory as a socio-material and practice framework operationalised using Discourse Analysis. The research analyses the interactions between people and discursive objects to explore how HRD practices are identified and framed.

The research finds that specific networks evolved within the “chat” events as actors sought the enrolment of others through processes of translation (Mitev 2009). The dominant discourses of HRD as performance based were replicated (Lawless, et al 2011; Francis 2007). Common discursive repertoires between the two sets of event participants were identified and a number of common viewpoints taken as black-boxed “givens” that acted as obligatory passage points for participants to pass through to be enrolled in specific networks. Clear positions of identity discourses emerged to differentiate members from “others” outside the specific communities (Bragd et al 2008). Noted ‘other’ actors included (pejoratively) ‘management’ and ‘regulations/ compliance’ requirements. A distinction could also be noted in how certain HRD practices were discussed as being for a more particular group of actors able to engage effectively in self-directed learning as against those perceived as lacking the competences to engage in such learning activities.

Rather than realizing the democratic potential of the “architecture for participation” of web 2.0 (Martin et al 2007), the research found that strategies for the containment or management of discursive struggles were often mobilised (Alvesson & Deetz 2000; Alesson & Wilmott 2002) to generate a “co-ordinated management of meaning” (Oswick & Robertson 2009, p186) in the framing of HRD practices. So, as has been argued with workplace learning in general, these open environments for professional development are socially constructed and regulated learning spaces (Billet 2004, p320). Discourse objects act as boundary objects (Denham 2003), a space of negotiation, translation and tensions between actors where (Antonacopoulou 2005, p5):

…tensions capture both the socio-political forces as well as the ‘elasticity’ and fluidity of organizing as different processes and practices connect to provide new possibilities.

Furthermore, the framing of HRD practices could not be identified through the development of a single discourse object but rather as an accumulation of micro-practices of individual actors (Pachler & Daly 2009). So the learning network assemblages framing HRD practices can be understood as textscapes (Keenoy and Oswick 2004) whereby HRD practices can be understood in a particular way in that particular virtual space at that particular time. Thus, a focus of analysis is placed on what Scardamalia & Bereitner (2008) termed ‘ideational content’ focusing on the linkages and patterns between utterances rather than specific text objects themselves. Actors could be identified operating as generalisers summarizing and “black-boxing” certain practices while localisers attempting to translate generalized practices to local micro contexts (Nicolini 2009). So HRD practice can be framed as rhizomatic (Cormier 2008) in that is shaped, reshaped and negotiated by actors in the practice at that time and space.

So it is suggested here that HRD practices can be conceived as the practices of the bricoleur who (Wiseman 2000):

…works with materials that are always second hand … The bricoleur is in possession of a stock of objects (a “treasure”). These possess “meaning” in as much in as much as they are bound together by a set of possible relationships, one of which is concretised by the bricoleur’s choice.

This paper argues that analysing the discursive strategies of actors in open web 2.0 spaces provides an opportunity to analyse discourses of HRD practices as they emerge through the interaction of actors within networks; that these networks and learning practices extend beyond specific organisational or institutional boundaries and that these discursive practices are rhizonomic and hence what can be framed as practices of HRD is in a constant state of fluidity. HRD practices can be understood as bricolage whereby HRD practice is constantly in an “interactive moment” (Shotter 1993, p3). However, it is also suggested that such networks of HRD practices are sites of discursive struggles that can be (unconsciously) contained to inhibit expansive learning (Fuller & Unwin (2004) and constrain new opportunities.  Furthermore, this paper argues that HRD practices and practitioners need to engage with the flows of knowledge interactions and artefacts as they form wider networks of learning that flow beyond, across and between the traditional boundaries of the organisational structure.