This is the official video from the Australian Society of Archivists of my presentation on Engaging Expert Knowledge Outside the Profession which I renamed Disrupting Archival Educationat the 2017 annual conference.
I spoke this presentation from very brief talking points which is a VBL (very big deal) for me as I have had to learn not to completely freak out about public speaking. This also means I do not have a script or transcript of this talk.
I intend to submit a publication about my ideas about Disrupting Archival Education to Archives & Manuscripts. Watch out for it! I am keen to hear from everyone about these ideas as it seems that there is some pushback from employers about various aspects of archival and LIS (Library and Information Science) education more broadly, as I saw at the recent RAILS conference in Adelaide.
One key sticking point for at least one employer was that they wanted the ability to hire people with grad certs and diplomas rather than those with Masters. The person couched this reasoning in the term “diversity” which was mortifying to hear. Diversity to me means hiring people from various backgrounds and understanding and identifying silences and silencing structures in the work we do (e.g. white supremacy). To hear diversity used as a reason to hire underqualified librarians (which is what I consider the grad certs and diplomas being) was appalling. Which brings me to the point of this blog post:
Appropriation of Criticality
It was not the first or last co-opting of terms to suit a different agenda. I also heard a simplisitic co-opting of the term ’emotional labour’ in a presentation. These instances raised several questions and issues for me (as well as made me angry as hell) about challenging people in a public forum. At ASA, RAILS and the Critical Archives conference I attended a couple of weeks ago I witnessed an appropriation of criticality which left me feeling very uncomfortable.
Broadly, appropriation and a general lack of understanding included:
head bobbing and general agreement at the notions of criticality being expressed but there is little or no evidence of actual change in the profession;
an acceptance of the meaning criticality but an absence of defining, explaining or interrogating it (there were some amazing exceptions);
expressions of paternalistic, and what I considered deeply troubling representation of marginalised peoples, that were couched in terms of partnered research.
I decided to be non-specific about where these incidents happened and perhaps this is the wrong thing to do. And so this brings me to what I can do as an audience member, professional, researcher, peer and concerned person in these situations.
I did sometimes ask questions of the presenter but I did not challenge them on their assumptions, their language, and their structural biases. What do I say that will not upset the people who are presenting? I don’t want to upset them. But maybe that is what has to be done? They are doing a job and trying to do it well. But it is also no excuse. This kind of research is perpetuating paternalistic, colonial, disempowering and racist systems and structures. In short, white supremacy. Its essential we challenge ourselves and each other in supported environments.
What is the solution? Mentoring. Real partnerships. Challenging your own assumptions. Understanding language and expression. Disrupting archival education. Disrupting ourselves.
I am not saying I am a perfect communicator and the video below is likely to reveal my own biases (I have not watched it yet). But I am working on changing and exploring what it is like to not judge, assume, dismiss and deny people their rights, autonomy, and culture through the systems I work within.
This week I am teaching the second part of a unit on access, reference and community engagement as part of an archives concepts and practices class for undergrads and postgrads. I was presenting on the ICA Universal Declaration on Archives and in particular how archives are conceptualised via protection, preservation, usability, and authentic evidence. The Declaration focuses on the competence of archival management and the role of the archivist and institution in this role. The Declaration also talks about access in relation to being open yet constrained by legal frameworks and the rights of individuals, creators, owners and users.
And while I am saying this I realise a few things:
Subjects of records are not specifically included or mentioned. This is one of the biggest areas of contest and discussion in the archival field. With specific relation to people who want to use or have access to records related to human rights, redress, and healing. Sometimes subjects of records are actually the owners of records but no one tells them they are. (A story for another time).
The entire Declaration is about the archival profession and archival institutions, not archives. Or as Verne Harris would say ‘Archive’. From my perspective archives are those spaces where people engage with memory-making. They may not be literally passed on from one generation to another, but they may have some continuing value for that person or others who interact with the Archive. Generations of cultural stories are archives. How we understand what to do in social media is part of the memory or archive of how social media is constructed. Archives are about memory and remembering. Sharing and passing along an understanding. It does not have to be about handing over artefacts. The evidence of culture is everywhere. Not just in documents.
I heard a story about access to archives and the records they contain while under a grossly inhumane regime. Those working in institutional archives figured out ways to get restricted records accessible to the people who needed them to find out where people went, what decisions were being made and so on. What does pertinent laws, as stated on the Declaration on Archives mean anyway?
I remember having similar conversations to those points I wrote above about the Declaration on Archives when it was published. I like the poster and I teach with it every semester, but it needs some rethinking about what archives mean to people. And that the Archive is about people, not about documents, so how is it possible to construct a Universal declaration that includes these critical points of view?
And while I am watching Tim Sherratt’s Keynote from last year’s ASA conference I am reminded on Eric Ketalaar’s thoughts on how access ‘enables use’ and that ‘we have a right to know’. Last week in class we examined the NAA records to look for decisions about records and access to them, noting that it was a challenge. Yet we also saw the week before that the CRS provides an extremely useful understanding of context in records (links to other entities in time and the recordkeeping that created the records). But it does not document adequately the actions and implications of archives being about people (and potentially their access and use by people for people-centred reasons such as human rights). There is lots to say about description and the role it plays, but description is a system to follow. Recordsearch is a system that we see and interact with. How description is implemented and how those descriptions can be accessed and seen is vital to how archives play a role in society. That is what Tim is talking about (but I am only 10 minutes in – can’t wait to hear what is next).
Below is a post I wrote in December last year while I was still in the US. I recall feeling very nervous about posting these reflections and so chose not to. Now I am out of that particular country and system, I can’t see why I was feeling that way.
But you know, I do know why. I now can see why I made that decision back in wooly wintery snowy December. And in recognising this I can see and feel that I made the right decision to return to Australia. Some things are exactly the same and I want to work through what they are but some are so incredibly different that I feel like I can finally express myself.
Below is an image of some Kangaroo Paw at my current university. It is the official West Australian state flower.
Last week I attended the Australian Society of Archivists Annual Conference. One of my jobs was to talk about the cultural perspectives of technologies. I talked about algorithms, machine learning, and constructions of evidence of culture. I think I scared people.
Below is a video of the extended talk. It goes for just over 10 mins. At the end, I talk about my Mediated recordkeeping model and how it might be useful in exploring these expanding contexts and complexities of culture.
I am keen to explore the role of machine learning in cultural heritage spaces. Who wants to help?
Hello, I am Dr. Leisa Gibbons from Curtin University. I teach archives and preservation to undergrad and post grad students. In my research, I explore sociotechnical issues, impacts and implications of acquisition and preservation of online content and the role that archivists can, do and might play in the formation of digital cultural heritage.
In this presentation I am going to share with you some intriguing information about algorithms and machine learning I have been collecting over the last year or so, so that I might talk about the nature and purpose of web archiving and how it is possible to understand evidence of culture as it is being valued and formed over spacetime.
Originally, this presentation was designed in PechaKucha style where 20 slides are shown for 20 seconds each. This presentation has 13 slides with the last one being quite a lot longer than 20 seconds.
This year Professor Geoff Goodhill, from the University of Queensland wrote about AlphaGo, an AI program designed to learn to play Go. AlphaGo learns via use of neural networks and extraction of key ideas.
You’ve probably heard about the algorithm created by Standford researchers that predicts sexual orientation from photographs of a person’s face? This is also generated with learning neural network technology.
Yet, as Professor Geoff Goodhill mentioned, there is no known way to interrogate the network to directly read out what these key ideas are that help the algorithm make decisions. Instead they can only study its outputs and hope to learn from these.
A couple of years ago, Vladan Joler and colleagues in Belgrade began investigating the inner workings of Facebook. This image is a flow chart that they created on how our interactions with Facebook create data – which show how we, as Facebook users, are in fact doing unpaid work for Facebook – so they can sell us stuff.
We all know this of course, but perhaps we think less about what this might mean in 20 or 150 years time related to data privacy and surveillance when you think about the data we give Facebook is used to calculate our ethnic affinity (Facebook’s term), sexual orientation, political affiliation, social class, travel schedule and much more.
In 2013, a community of scholars and activists gathered in the US to examine and discuss the social justice impact of algorithmic accountability or #algacc. Tthey raised more questions than answers about the impact of data surveillance and our right to know what and how data collected about us is being used.
UCLA Assistant Professor Safiya Noble writes about algorithms of oppression and how the data they use to learn reinforces existing structures of racism and sexism. Safiya talks about how a Google search she undertook on the search term “black girls” often suggested porn sites and un-moderated discussions about “why black women are so sassy” or “why black women are so angry” – presenting a disturbing portrait of black womanhood in modern society.
In Australia, there are at least 20 separate parts of law that allow the government to give computers the power to make decisions. Decisions that used to be made by a human and can have important consequences.
These laws allow for computers to make decisions about social security, taxation, parental leave, superannuation, migration, biosecurity and child support. In every case, some kind of algorithm may be used to make decisions, yet we have no knowledge of how these work.
These are powerful and disturbing stories about the creation and use of data, the role the internet plays and the shaping role that mathematics and computers are playing in our society. This brings me to web archiving.
One of the most basic tenants of all data science is that data doesn’t exist in a vacuum, it is the result of a massive pipeline of explicit and implicit decisions…
…yet so much of the output of the data science world proceeds as if data can be cleanly separated from the contexts in which it is created.
Nowhere is this more apparent than the world of web archiving.
Researcher Kalev Leetaru, wrote an article for Forbes recently that starts with this paragraph. This was not his first dig at how poorly web archiving is conceptualised and constructed. He started in 2012 talking about the lack of documentation regarding even the most critical decisions like inclusion criteria, seed lists and third-party crawl donors means that we have precious little insight into how these archives were constructed and what biases may be manifest through those myriad decisions.
This is not a new conversation for me either. But algorthms and the rate of change in our virtual spaces and technologies are raising the stakes.
When it comes to using data to understand the world around us, the most important question revolves around how well that data reflects the phenomena we are attempting to study.
Kalev rightly asks questions about the nature of web archiving. When it comes to using data to understand the world around us, the most important question revolves around how well that data reflects the phenomena we are attempting to study. Do Twitter-based studies of human society truly reflect the dreams and fears of global society or are they systematically biasedgeographically and demographically? Do the breaking news events surfaced by the Facebook Trending Topics module exclude much of the continent of Africa and is Africa as a whole largely absent from the datasets we use to understand the world? Does the relative dearth of analytic algorithms for languages other than English mean we miss critical trends.
All this exploration of algorithms and the internet comes back to a question I have been raising for a decade now – what is evidence of culture? And in this question, what is the role of the archivist and the archives in the construction and dissemination of cultural heritage?
If web archives are online cultural heritage, how is their construction being understood and documented? As Kalev points out – does the medium examined define the results?
This raises the question of what web archives actually evidence of? But how do we interrogate the notion of evidence of culture?
I want to share with you a model I created from research on how to understand the complexity of evidence of culture in online spaces. This model is an attempt to make sense of how and why people interact with recorded information – the purposes, the values, and the nature of memory as it is created, shared, accessed and managed over time in various and complex ways, including in response to technologies, other people and entities, and various mechanisms, systems and tools that help to enable and empower, as well as disempower and make hidden.
I want to share with you the three important areas it represents:
Firstly, memory and evidence as processes are separate but intrinsically linked. The processes of memory-making has a relationship to multiple systems, mechanisms and perspectives involved in establishing evidence.
Secondly, how people create is linked to how they see and identify themselves, what they are interested in, how they identify with various communities, as well as what values they perceive according to various community cultures. Narrative is vital to understanding this as it is a tool that can construct and communicate multiple and simultaneous realities, identify and make sense of the self within groups, community and society, and is imbued with power; of dominant, counter and competing narratives and as a mechanism for memory-making and knowledge preservation.
Thirdly, interaction occurs in conjunction with an understanding of action at various levels, as well as in relation to how people use, value and experience technologies including what technologies afford or do not allow to help people achieve their goals in creating and sharing something of who they are.
This model shows all these points of view to exist simultaneously and in multiples. How an individual understands their identity and work is not necessarily how it is seen by someone else. So when the archivist creates, in the creator dimension by documenting the world, they should be taking into account the varied, diverse and potentially incommensurable complexities that make up this map of how we understand cultural heritage as evidence of culture.
If we see algorithms as part of a continuum of mediated memories where and how do they fit in? Whose narratives are being told and what do we need to know about mandates to understand their contexts as memory? I don’t have any answers today but this is something I am about to examine.
But what my research into algorithms is beginning to reveal is the deep complex relationship and nature we have with data and machines. Recordkeeping is a memory-making process that contributes to evolving values, purposes and interactions over spacetime including memory (as making and remembering), narrative (as personal, sharing and evolving), evidence (as constructions of value and meaning) and technologies (as mediators and facilitators).
Archivists, and I count myself as one, need to consider what this means as to how we understand culture as evidence and heritage as it is being formed. Archivists also needs to understand and challenge their role in the system so that they may empower, discover and transform to meet multiple needs over time. Flexibility, adaptability and a need to understand what is being valued and who by as it is being created is essential to any transformation. That includes transformation within ourselves as professionals as well as the transformation of what role archives as constructions of evidence play in society.
I had to shorten it for the conference, but have now recorded it in full. I also adapted it to fit with an online presentation. It is a PREZI so please click using the forward arrow to listen to me explain each screen.
The key ideas in my research is how personal memory systems (such as those that exist in how we manage stuff on computers, tablets, mobile phones and in online spaces such as social media) help to form collective memory (this term can include various conceptualisations of ‘collective’ but in this research it is primarily focused on what we might call traditional memory institutions).
In looking to explore the formation of memory systems from personal to collective I examine how value is constructed and contextualised by individuals who create and share digital content. By understanding value at the creator level it can provide deeper and richer insight into whose memory is being captured and preserved.
As a final note on terminology, I do not use the terms personal digital archiving, nor personal information management. I prefer to use the term recordkeeping and memory-making. These latter two terms encompass various aspects of what it means to create and manage information for various purposes, including to remember. I see information management is a form of memory management and control. Recordkeeping provides a way to construct the systems to manage and control. And recordkeeping is not necessarily about producing or managing authentic, reliable records or evidence in the sense of what is usually done by governments and organisations. We all do recordkeeping in some form or another using various tools and processes to do so, some more effective than others. Archiving activities or processes are just another kind of recordkeeping process, regardless of who does them. Recordkeeping is a process where recorded information is managed according to its value. The value could mean retention for an instant or forever (although the latter is highly unlikely in practice, but rather is an intention). Value is assigned or identified at various times. This is what this research was looking to find out more about.
Recently, I submitted a paper to the Computational Archival Science (CAS) workshop about my research exploring ways to develop tools and methods to support and undertake automated appraisal for cultural heritage. The project is at the conception stage and I am exploring the existing methods and tools that identify data from documents and map them as networked contexts. I am starting with a pilot project focusing on the Zoetic Walls street art project in Cleveland.
The project is heavily conceptual and explores what it means to document and manage cultural heritage that exists physically and virtually, and has significant ephemerality issues. The goal is to explore how it is possible to do this work in a way that engages with multiple stakeholders and various contexts that contribute to a social phenomenon that has been given some meaning and value. The ultimate goal is to design appraisal tools that might be able to be used in a much more participatory way. It is heavily conceptual right now and right at the beginning. A great place for some feedback from people who are interested in archival science and data. Or so I thought.
My short paper for the workshop was rejected, although the reviewers said it was well written. From the comments and then a closer reading of the workshop history and goals, I realise that I was trying to pitch a research project about archives to mostly digital humanities scholars who have their own particular view about what CAS is as well as what archival science is more broadly. I wrote an email responding to the reviewer comments, but it bounced back as it one of those email boxes that are not read. I could not find an email address for them either, so I have copied the email I wrote below.
The main issues that the reviewers seemed to have was that my work was too conceptual and that the conceptual aspects I was talking about are not “computational archival science.” Not just not suited or not part of the conversation, but actually not CAS. The email I wrote addresses comments from the second reviewer mostly and while I have not copied the second reviewer’s comments here, I think you get the gist from my email.
I feel like I must have missed a conversation somewhere about the relationship between computational archival science has with the actual discipline of archival science (or archival studies as it is also called here in the US). Are there any archival scholars out there who have been involved in this CAS that can enlighten me? I have read the definition listed on the website and wonder primarily about how the term, “archival thinking” has been used and its relationship use of “archival science.” I checked and I believe my work fit into the notion of Computational Thinking (CT) as being “the thought processes involved in formulating a problem and expressing its solution(s) in such a way that a computer—human or machine—can effectively carry out”. Of course I am happy to receive feedback and improve on my work and I can see where I could improve on the paper to expressly address CT, especially at this pilot stage. However, my concern remains this issue with what “archival thinking” means and how this is carried out in CT contexts as CAS.
To the workshop organizers;
Thank you for the feedback. From the reviewer feedback it is clearer to me that this workshop focus is on data science and machine learning from digital humanities perspectives.
It is unfortunate to hear that while engagement with archival science theories and principles is being asked for, engagement with archives and archival work is not suitable for the workshop. I am of course engaged with exploring what it means to document cultural heritage from an archives-as-institution point of view as this one of the ways that big data and linked data gets created. However, my research also attempts to grapple with alternative conceptual, practical and technological approaches to appraisal via crafting and testing methods to identify data as context (and then what that data tells us about the social phenomenon). I do see that I did not explore the notion of automation enough from an archival processing point of view and the potential role it can play for digital humanities research.
Regards literature on conceptual modelling, I am not addressing or using conceptual modelling, rather context entity mapping and network analysis using existing archival science standards and methodologies. It is possible to explore links between conceptual modelling from a computer science and information systems point of view, but it is really the topic for another paper. In archival science there is not much literature on conceptual modelling other than possibly the OAIS model (which is a functional model, albeit from a computer science idea of conceptual modelling) or the models developed from InterPARES (mostly business process models), or the records continuum model (conceptual and activity model) and other entity models developed by the Records Continuum Research Group (context entity models), so I am not sure what was expected in relation to this.
Regards the comment about being heavily influenced by critical theory, I do not refer to or engage in any critical theory literature or frameworks in this paper. As was mentioned clearly in the paper, my paradigmatic approach is social constructivism. The comment about being heavily influenced by critical theory in archives indicates a lack of understanding about engagement by archival science scholars with critical theory.
Finally, it is regrettable that a workshop on archival science does not want to engage with the “four walls” of the archives and provide a space to engage with challenges that can be made from within and outside of this context. I do not work within those four walls, but I study them and what they mean in various conceptual, technological and practical ways, and any engagement with archival science, computational or not, requires exploration of their impact and meaning.
Had a little play with Ngrams again today for a paper I am writing. I have several issues with the limitations of Ngrams (books from western traditions, written in English, only those scanned, only those scanned full text are useful, context and association issues with language). But it is fun.
I was looking to see when lifecycle (or life cycle) appears first in relation to information, records and archives. Interestingly enough, archive[s] lifecycle does not appear in the literature. This made me realise something that I had been pondering in my head quite a bit over the years. The lifecycle model is actually not about archives at all. This is therefore both freeing (archives as new things aka. Schellenberg), and a bit odd at the same time. Aren’t records in archives about contexts and relationships? The relationships and contexts are not just about the records themselves either, but about their various roles during which time they were in the life cycle before getting to the archive. They do not get a new life, but provide evidence of the sum of their old one, as well as have new parts to play. I do wonder to what extent this thinking about archives as being something ‘other’ plays a role in how they are conceived of in the US tradition. And by conceived I mean created, studied, used and so on. More pondering needed.
As Schellenberg, often associated with the life cycle model, did not actually use that term (he used life span) I wondered if this turned up anything interesting in Ngrams using the same prefixes above. Answer = no.
However, record life span did achieve a result.
Upon reviewing the books for this result however it shows up the use of the term record (as in achievement) life span, mostly related to biology and population studies (where the use of the term life cycle is also derived).
One last fun Ngram on records management, information management and information governance. Revealing yes?
I also note that in my research into this there has been a LOT of plagiarising from the 1998 Philip C. Bantin paper (quoted in the SAA Glossary). So many others have copied word for word what is written about life cycle without attribution. But also, Bantin says: “Schellenberg and others…” without any reference. Who are the others?????
Last year I published a model called the Mediated Recordkeeping Model, a systems and activity-based theoretical model that explores and attempts to explain the formation of cultural heritage via narrative, identity, memory, technological and evidential systems. I created this ‘thing’ and for a while I have not really know what to do with it. I know how it came to be, but what now?
The first thing I did to explore what this model can do was to re-engage with a YouTube video I often use in presentations. This video, the first featured below, can be found in the Australian National Film and Sound Archive (NFSA). I wrote about it in a 2009 paper and often start presentations off with showing what the NFSA catalogue description of this video documents (and what it does not). I mention this description in that 2009 paper and there is an image of the entry, but also search for it yourself in the NFSA collection catalogue. The purpose of highlighting the NFSA catalogue entry is to show how metadata does not explain much, if anything, and can actually be quite judgemental and incorrect.
My first test of the Mediated Recordkeeping Model was to go back to this video and to identify what description might look like if I was to use the model labels. So, I put the model labels into a table format and added metadata to each. What I realised when I was doing this process is that I was crafting a story. Then I realised I was creating more than one story.
The sum of the analysis/description is my interpretation of the video and its role as cultural heritage.
As I built up the metadata and for each element described a different story was being told with multiple potential endings/contexts that were not described.
The relationships between each element as they were documented and mapped was not just linear or entries on a table, but were part of a movement or mapping that could be done on the model. The process of this mapping is as important as the mapping itself.
I was creating the potential of multiple stories. By documenting my own story or interpretation of the model I was also providing a process for others to create their stories. These stories might be built the same way, or in different ways. Stories could be critical, ancestral, visionary, contemporary, individual, collective, antagonistic, conflicting, incommensurable as well as many other kinds of stories.
That in seeing one story, there can exist a way to see many more, as well as what is absent.
This led me to consider some things:
Is it possible to see absence only when something else is present?
How can multiple stories be told? And are there different ways to interact with stories? Can the process of the storytelling be represented in different ways?
How can people, including archivists, use this model to help tell these multiple stories?
I have been dabbling with visual presentations of theoretical models for a while now which led me to do some Google Sketchup work a few years ago, see video below, as well as influenced my redesign of the classic continuum model shape as shown in the Mediated Recordkeeping Model (and contrasted with the image shown on the Wikipedia page of the Records Continuum Model). I was also given the opportunity to develop and exhibit a visualisation of data and this led me to think more about how the Mediated Recordkeeping Model might look like visualised.
The result is the sun ray or flower representation of the video description I laid out in the table. For the exhibition I recorded myself talking about the model, what it shows and how I created it. I have now uploaded this to YouTube. I showed some people at the recent AERI held at Kent State and their feedback got me intrigued about how to use this model and visualisation such as this in a practical or operational way.
What does this way of modelling (the sun ray) bring to archival description?
Does the sun ray and the Mediated Recordkeeping Model include or address what is important about archival description?
Can the sun ray move in 3 dimensions? How would it move?
And what would it look like if I was able to add additional stories?
I am preparing to write a paper on conceptual model making and the use of theoretical models for critical archiving.
I delivered a paper recently on What it means to teach ethics to students: exploring the complexity of representation and equity in records, recordkeeping and archives. I also referred to the Mediated Recordkeeping Model in this presentationand plan to include something of the lessons I outlined into the paper.
Lessons from the presentation:
How we, as educators, can help to teach our new archivists what the power of technology means and what it means to act?
How technology affords reaction rather than action and how individuals can be made aware of the difference?
How ethical standards and statements of principles sit with an increasing awareness of activism not just in our profession, but globally, and the continued tension with the position of an impartial view?
Is it ethical to document or manage any records without consent or allowing them to have an active, collaborative role in the processes including decisions about access, rights and description over time?
So, finally, in thinking about modelling, theoretical and conceptual frameworks and operationalising them in various contexts, its seems there are many things to consider. Some of these issues are already being explored in the archival discipline including what is being represented and how, what is missing or in conflict, and how the processing of recordkeeping (including use of the model) influence and impact on representation. Another issue I think equally important is how it is possible to evaluate and build on the theoretical models. It is great to operationalise them or show how they can impact on practice, but what does this also mean for the theory?
It has been a while between posts. And what a while it has been. I have been undertaking major research commitments and curriculum work during this semester all while trying to teach two new courses and help plan this year’s AERI. I feel like I am in a whirlwind of excitement stabbed with anxiety. I have, in the past, been the master of organization, but this is stretching my skills. BUT the sun is shining today in Ohio and spring feels beautiful. My window is open in my study at home and I am writing a blog post for the first time in a while. I updated my research page and I am thinking again about the cultural continuum. Things are OK.
I wanted to share a video I found where Geneva Gay is talking about “Variables on the Cultural Continuum.” There are some wonderful parallels with my work and in particular the Mediated Recordkeeping Model that encourages me to explore it in more depth. There are several points that Professor Gay makes that are key to understanding how the information continuum works (as it exists in the records continuum models and other continuum models).
Essentializing and identity. Geneva talks about how “everything has some essential dimensions to it” and talks about what is held as being core. I take this to mean essential elements of how we define ourselves via our identities. What we think is important to us – our essential being. This makes me think of the sociological concept of habitus and the writings of Pierre Bourdieu. Bourdieu refers to habitus as a “system of dispositions” that contributes to the creation of individuality and in turn helps to form the conditions that will impact on further iterative development of identity (1984, p. 2). These are productions of knowing, power and identity, yet they can be unconsciously enacted. My identification as a continuum theorist in the research and in the subsequent thesis served to highlight this as my cultural area and the primary source of production and authorisation. That continuum theory has been developed and applied to archival science also plays a significant role and ultimately influences and contributes to the construction of how I understand and apply knowledge in research.
These kinds of understandings are also apparent in the Research Design Model, another continuum model that came out of the PhD research. I have written a book chapter on this model (this is a thesis chapter) but have not published on it very much, instead focussing on the Mediated Recordkeeping Model. I have two papers in draft related to the Research Design Model as a reflexive model and their use in informatics. But these are on the back burner.
Multiplicity in the continuum. Geneva refers to “varying degrees of elaboration” related to our identification of components of our essential selves. She explains that there are various components or elements (or the kinds of data captured in demographic research) such as race, socio-economic background, age, gender and so on that “have an impact on how the core features of a given culture are manifested in expressed behaviour.” As an example, each member of her “nuclear” family unit expresses “different layers” along a continuum of African-American culture “because of the fact of who we are.” She refers to her brother expressing African-American culture differently and proposes that there is likely a gender factor, but also refers to the age difference between family members as being relevant to a different expression. Yet, all these expressions exist along a continuum of African-American identity.
Geneva’s examples are very micro – her family, but this is the point of multiplicity and continuum thinking – that very small parts contribute to a whole (continuum). What is also relevant here is the points of intersection are not just singular, but are multiple. Her brother is both a male and a different age. The continuum models express these intersections and multiplicities in various ways in relation to recorded information. On the Records Continuum Model identity is only represented by grouping from individual to institution, but is intersected by ideas about memory and evidence, as well as activities and parts that contribute to how records are formed. So, by taking Geneva’s example of her brother, his contributions to memory via recorded information will be informed by his identity as he perceives it, including what roles he might play within groups and organizations (included or excluded) as well as in relation to the activities he performs related to how he captures and manages memory.
My work says that OK, this happens, but there are also more factors and complexity than that. Identity must be understood within the context of how and what we communicate as part of our identity and the impact of power on this, as well as how we interact with our social and technological environments. Plus, memory and evidence are linked but not so linked that that are the same and that memory-making or the need to remember is a vital aspect of cultural identity and transmission (heritage) over time. This is what the Mediated Recordkeeping Model proposes. What my research suggested was that there are multiple factors and ways that people decide on what is of value and how they then encode that value into what they create and communicate. These factors and ways or interactions are quite complex and have multiple intersections between various identities over time, including how community norms and values impact on decisions.
I want to do some more research into the cultural continuum and memory-making but looking at how technology engages and mediates these transactions. My immediate goal is to explore distributed identity on social media and in particular decision-making related to significance and value across social media platforms related to memory-making. I am interested in what people decide to create so that they can remember or create memory and who that memory is for and if use of different social media sites is at all relevant.
I also recently proposed a research project related to how people experience the internet and what it means to capture memory of this and whether or not this would be relevant to manage as archives and, if it is, how it is useful and who would care about it.
Sometimes, when I stop and reflect on what I am doing I wonder why exactly I care about how people make decisions and construct ways to remember. In a way I think it is me trying to make sense of the immenseness of the world and how individuals carve out our place in it.
Bourdieu, P. (1984). Distinction: a social critique of the judgement of taste. London, UK: Routledge & Kegan Paul.
I am currently reviewing with colleagues the archives program and curriculum and I am reminded of how archives support researchers. Archives are often considered to be filled with historical documents and records and they are, but they those documents and records are more than their place in spacetime as history. Researchers do not always want to use archives for ‘history.’ There is also the idea that there is informational value in archival materials that provides inherent value etc. The informational value also comes from the recordkeeping systems themselves in the multiple contexts the records were created and managed, including the archive itself. I wonder these these possibilities are catered for?
Related to the multiple uses of archives, including their systems, I wonder then what we need to teach our graduate students. I have been to a few Digital Humanities events and can see that people want to use digital information now and be able to access it, link to it, scrape it, combine it, mash it, map it, make music from it and so on. Stepping back from the idea of whether or not archival systems support these multiple uses, what knowledge does a graduate student need to acquire to be able to think about and respond to the different ways that archives can be used? What does it mean to ‘add value’ to an archive?
Archivists might not participate in hack-a-thons, but they need to know what they are and how people use information and data in these contexts. They might need to know how systems support or do not support the use of data in this way. So what literacy do we need to be teaching? Related to my own work, is it OK just to teach the workflow of digital preservation or should we be challenging the nature of preservation? How does this get balanced in a field of practice that needs to engage with theory (but is known for rejecting theory as being non-relevant or too complicated). How can we achieve innovation as a practice if the theory is not being explored in practice? Another thing that I think about in relation to teaching or providing a way to explore innovation is how they we can support students who go out into the workplace and have to do the basics? But then in 5, 10, 15 years time their theoretical experiences in grad school help them think about and develop innovation?
I have heard stories about how students in our field and more broadly in LIS do not realize what kind of skills they have learned until well into their career and well after grad school. How can we make the grad school experience balance the need to explore theory and innovation, as well as meet expectations for practice (from the student and the employer). The situation in the US is different than in Australia as well, but has many similarities.