What is this research project about?
WiSP in Numbers
Writing in professional social work practice in a changing communicative landscape (WiSP)
- 50 social workers in children’s, adults and mental health services
- In 3 authorities
- To gather writing activity logs covering 1000 social worker days
- Carrying out 50 interviews with social workers
- Carrying out 10 weeks of observation
- Building a 1 million word corpus of written texts
- Tracking 40 histories of texts in detail
To read more on the progress, issues and challenges we’re facing, take a look at the ‘project news and updates’ page.
A day in the life of a social worker.
To get an idea, take a look at A Day in the Life of a Social Worker, by Barry Cooper and Lucy Gray (Rai). Have a look for when and where writing happens (you should notice typing at desktop, note making in a book, completing electronic forms..)
How are we researching?
The overall aim of the Wisp Project is to build a rich picture of what it means to write and record in contemporary social work practice.
To do that we are using a combination of ethnographic and corpus methodologies in approaching data collection and analysis.
The particular ethnographic methodology we are using is what we call a ‘text-oriented ethnographic’ approach. This approach focuses on individual social workers and their text production, whilst taking into account immediate contexts of production as well as institutional practices shaping such contexts.
A key aspect of the project involves building a corpus of 1 million words of professional social work writing. The corpus will include the range of social work texts as well as a substantial subcorpora of a key writing practice in all social work domains, case notes.
Ethnography involves collecting a wide range of data to try and build as rich a picture as possible about a particular phenomenon – in this case ‘writing’ in everyday social work practice.
We use different approaches to collect data about everyday writing practices. The overall ethnographic approach adopted in this project means that we are interested in exploring writing in context – asking questions like:
- when is writing happening?
- where is it happening?
- why is it happening?
- who’s involved?
- what else is happening at the same time?
In the WiSP project we are using interviews, researcher observation, social worker logs as well as collecting a large number of texts (from text messages to diary entries, 20-word emails to 20-page reports) to explore where and how writing fits in the day-to-day practice of social work.
Putting data from all of these together we can build a detailed and contextualised picture of how writing fits within social work in action, and any solutions or challenges they may face, using participants’ own perspectives on their experiences. Building a rich picture is rather like a jigsaw when it’s finished.
The WiSP project is building a corpus of 1 million words of texts written by social workers. A ‘corpus’ is an electronically-stored collection of texts.
One way of analysing this collection of texts is through computer software. Here, we show the kinds of analysis that can be carried out and what this reveals. For this example, we use a relatively small corpus of 18,000 words of case notes around one individual service user. The service user is an elderly woman who is visited daily by carers. All names of individuals have been removed so that the corpus is fully anonymised.
To give an overview of the small corpus of case notes, we first ran it through a wordle programme. Small, function words such as the, a, in on aren’t included in the wordle as otherwise they would dominate.
Unsurprisingly, home, staff and services feature heavily as the context is carer visits. In this set of case notes, the individual concerned had problems with her left foot, so there is high use of words such as wheelchair, leg, left, physio.
Using computer software, we then ran the corpus through a tagging programme called Wmatrix to assign grammatical tags – or labels – for each word. For example, ‘I’ is an example of a pronoun and is tagged ‘PPIS1’. This allowed us to compare the types of words in the corpus to those in a larger corpus. We compared the grammatical words in the example case notes to the 80,000 word written BNC (British National Corpus: http://www.natcorp.ox.ac.uk/).
Here’s what we found:
1) The case notes have many more instances of verbs in the past tense e.g. placed, knocked, spoken, advised, organised. The examples below show some of these words in context.
The use of these words shows how the case notes are written in the past tense and in an abbreviated way. In the top line, we’re not told who spoke with the service user’s daughter – this is assumed to be the report writer and doesn’t need to be stated.
2.There are lots of verbs in the infinitive e.g. ‘to give, to phone’. Again, this is due to the abbreviated report style of the writing. Carers are writing quickly, giving the key information.
3.There are few instances of ‘I’
4.The report contains frequent mentions of times and days of the week e.g.
We also compared the example case notes with the British National Corpus in terms of the words grouped by meaning. This highlighted the extensive communication reported in the case notes. Carers often report on who they emailed or phoned in order to record that they have organised further care and generally kept everyone informed.
How can corpus searches help us understand writing in social work?
The brief examples here are from a fairly small corpus of case notes from just one service user (18,000 words). But already, it tells us something about the patterns of such writing – the abbreviated way in which the notes are written up, the focus on arrangements (times and days in the future) and the extensive reporting of what has been done and on who has been informed.
With a larger set of social work texts – we’re aiming at a corpus of 1 million words – we hope to be able to say a lot more about the different styles of writing and about writing in different text types. Overall, this will help us to document key patterns in the different types of writing and to discuss with social workers their views on the extent to which such writing is appropriate and useful. Findings and insights generated will feed into discussions around who writes what and why, to be used in social work education and training.
The WiSP team are very grateful to Signe Oksefjell Ebeling at Oslo University for expert advice on corpus compilation and anonymisation.