Launch of our new database

We are delighted to announce that we have  launched our new online, interactive  database .

Although the database is accessible online, it can also be downloaded in Excel spread sheet format.

The database allows its users to:

  • Search for individual writers and find out more about their demographic characteristics, such as age/year of birth, gender, occupational category, marital status.
  • Search for writers with specific demographic characteristics, such as gender, or year of birth.
  • Identify writers’ writing behaviours – showing the directives to which individual writers have responded.
  • Search for directives and themes.

We have written some FAQs intended to help new users.  There are also some simple tools (with instructions) to compare the Mass Observation writers with the broader UK population.

We hope that the database is easy to use. But if you identify any problems, please use the contact information at the top of the database website.

Over the next few weeks we are going to be publishing some ‘How to use the database’ videos/vlogs on the Mass Observation Archive’s YouTube channel.

We are also going to publish some videos/vlogs on some of the findings from the analyses that we have been working on. Please watch this space for updates.

 

 

 

The Many Faces of Class

In the previous blog (‘The Persistence of Class’), I outlined how we have found that the idea of class held a really important place in the identities and observations of Mass Observation writers when they responded to the 1990 Social Divisions directive.  However, this is only part of the story.  Of equal significance to our analysis has been our exploration of how class is discussed by the MO writers.

What we have discovered is that MO writers have complex, multi-faceted and ‘vernacular’ understandings of class that do not fit neatly within any systematic sociological models.  Thus, as with the contrasting way in which class continued to be really important to MO writers whilst the significance of class declined within academic scholarship, we see another discrepancy between the views of ordinary people and academic thinking.

The models of class constructed in writers’ responses do not seem to reflect any particular sociological model of class, contemporary or otherwise.  Instead, the models of class are exceptionally complex and use an extremely wide range of indicators.  This is demonstrated in the breadth of class codes in our coding system, which includes Patterns of Consumption, Income, Housing and Region, Exploitation, Accents + Vocabulary, Social Networks, Class Background, Education, Politics, Leisure and Travel, and Work.  The importance of these factors varies from writer to writer but multiple factors feature in almost every script.  This is illustrated in Table 1, which demonstrates how commonly cultural, economic, social and political aspects of class occur across the documents.  Although factors such as ‘Work’ and ‘Education’ – key tenets of most sociological models of class – feature heavily, they are rivalled by more intangible factors such as ‘Accent + Vocabulary’, ‘Politics’ and ‘Housing and Region’.[1]

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This has a number of consequences for our analysis.  One that is immediately apparent is that these ‘vernacular’, or ‘everyday’, understandings of class mean that there are clear distinctions between where individuals place themselves within the British class structure and where social scientific models of class would place them.

Let’s take the example of A22: the Social Census classifications in 1990 – the closest classification model – positioned A22 in group 4 of 9 (1 as highest class, 9 as lowest), ‘Clerical and Secretarial Occupations’.   However, A22 defines herself as working class because ‘with my Lancashire accent I am never going to achieve “middle classness”.’  Similarly, B1106 identifies as working class despite being positioned in occupational group 3, ‘Associate Professional and Technical Occupations’, because he ‘always felt a great affinity with my maternal grandmother and her struggle through life.’  Rather than a straightforward relationship between occupation and class position, the MO writers use complex and varied models of class that make use of cultural, social, geographical, economic, political and background factors to define themselves and others.  Moreover, the MO writers are much more comfortable developing their own models of class to understand society and define their class identities than they are with adhering to existing sociological models.

However, we have noticed that writers do refer to sociological definitions of class, sometimes overtly and openly, sometimes implicitly.  This is reflected in the consistency with which they use certain sociological frames, such as work and education.

Therefore, in the next stage of our analysis we will explore themes and patterns in the ways in which class is constructed across the sample of writers.  We will examine whether social factors such as age, gender or self-defined class identity affect the way in which people think about and construct their own models of class.  This will enable us to explore how class is understood, defined and constructed from the ‘bottom-up’ and how these ‘popular’ systems relate to existing models in social science.  This will provide us with insights into how class was felt and lived in 1990.

[1] For examples of dominant sociological models of class see the Social Census (http://www.ons.gov.uk/ons/guide-method/classifications/current-standard-classifications/soc2010/soc2010-volume-3-ns-sec–rebased-on-soc2010–user-manual/index.html) or the Eriksen-Goldthorpe model in R. Erikson and J. H. Goldthorpe, The Constant Flux: A Study of Class Mobility in Industrial Societies (Oxford, 1992).

Qualitative Analytic Design #1: Factors underlying our approach

In her recent post, Rose commented on the variety in the responses to the 2008 Your Life Line Directive. This variety has shaped the way we are approaching the qualitative analysis of this and the 1990 Social Divisions Directives. So I thought I’d outline our analytic design and share how we are implementing it within MAXQDA (see here for an explanation of our choice of CAQDAS package). I’m doing that in a series of 4 posts, this is the first, check back over the next few weeks and months as our analysis proceeds for the next 3 posts, which detail the way we are going about each analytic phase.

Framed by the projects’ overall objectives, research questions and methodology, our analytic design evolved out of a pilot analysis phase when different approaches were trialled on a sub-sample of narratives from both Directives.

The resulting design involves three phases: i) high-level mapping of semantic content, ii) thematic prioritisation, and iii) in-depth latent thematic analysis. Each phase will be the subject of separate blog posts.

Here, though, I’m briefly discussing four factors that underlie this approach:

1) the nature of the data

2) the need to both keep separate and to integrate the analysis of the two Directives

3) the practicalities of the project

4) the need to develop a transparent and transferable process

 

The nature of writing for the Mass Observation Project (MOP) and the data that is generated

Because the writings of Mass Observation volunteers are only loosely guided by the questions in the Directive, we did not have an overview of the general content of the material at the start. This is symptomatic of this type of secondary qualitative data analysis. The narratives were not generated for the purpose of this study and therefore we have had no influence on the nature or content of the material we are analysing.

This is very different to the type of situation where researchers design and undertake interviews or focus-groups, or observe naturally occurring settings or events. Had we been involved in designing the Directive questions for a specific substantive purpose we might have had some ‘control’ but even then, the very nature of the MOP results in very varied responses to Directives. Some are short, others much longer; some specifically seek to answer Directive questions, others attend only very loosely to the Directive questions; some are written in a quite structured form, for example using bullet points, others are longer more free-flowing, discursive-style narratives; some are written in the first person and reveal detailed insights into personal experiences and opinions, others are more cursory, brief descriptions that upon first reading appear to reveal little about the feelings and opinions of the writers.

This varied nature means we have a very rich set of materials – just what qualitative data analysts love – but when we started out we had no idea of the content of this large body of varied writings. We therefore needed to design an approach that first provides us with an overview, so that we can evaluate the extent to which our research questions are answerable by the data. We could have achieved this by first reading all the Directive responses, but with almost 600 Social Divisions and almost 200 My Life Lines responses, some of which are many pages long, and a short-time frame, we couldn’t do this. We needed to be coding whilst reading. Had the analytic team done the transcribing, we would have had the broad content view we’re looking for from that process, but again, the project resources didn’t allow for that and temporary typists were employed to transcribe the responses. We did informally ‘interview’ the transcribers about their impressions of the MOP writers when they had finished, though, and this informed our thinking. But we could not solely rely on their opinions.

Analysing different sets of responses separately then integrating our analyses

Initially our intention had been to analyse responses to both Directives together, because one of our objectives is to explore the extent to which perceptions and lives have changed between 1990 and 2008 amongst writers who responded to both Directives (that we call ‘serial responders’). However, the pilot demonstrated that despite the need to analyse the ‘serial responders and despite the synergies across the two Directives’, starting out with all the data together would be impractical and would affect our ability to maintain focus whilst coding each Directive.

In addition, it became clear in our pilot coding that we cannot know at the outset which areas of our substantive interest offer potentials for looking across the two Directives. There are many potential synergies, and the longitudinal element of exploring the identities of writers that have responded to both Directives is an important part of our work. However, the Directives are very different and the context of the time in which these were responded to is important.

The practicalities of the project – number of coders and time-frame

Any project needs to attend to ensuring coding is consistent. The involvement of three coders and the short time-scales mean that we needed to design an approach that maximizes consistency from the outset. We could have mapped out the content of the Directive responses by undergoing an “open” coding exercise as a means of initial theme generation; this would have been similar to the usual first stage of Grounded Theory-informed projects. Indeed we did this in our pilot work and this informed the focus of phase one. However, the time available and the uncertainty of content means it is more systematic to focus first on the descriptive content and undertake more interpretive work once we have a clear idea of content.

The need to develop a transparent and transferable process 

One of the objectives of this project is to open up possibilities for using MOP as a source of secondary longitudinal qualitative data. This means that verified and assured processes for analysing MOP data that can be adopted or adapted by other researchers are amongst the projects outputs. The three-phased approach not only serves our analytic purposes but also offers a method that can be easily documented and illustrated.

 

Like qualitative research design in general, ours is iterative and emergent – we expect to need to refine our initial research questions as we progress – in light of our growing understandings. I will outline the three phases of the design (high-level mapping of semantic content, thematic prioritisation, and in-depth latent thematic analysis) and how they are being implemented in the CAQDAS package MAXQDA, in future posts.