First things first, welcome Steph to the blog - nice to have you here.

I've been feeling guilty lately that James has been doing all the heavy lifting on the blog, particularly writing about the Kidderminster meeting and the analysis, so I should probably say a little bit about what I've been up to.

At the last few presentations we've done, James has talked about the analysis essentially being on two levels - the first being quite schematic, number crunching stuff and the second being the clever textual analysis of meaning etc.  So while he's been working his way through the transcripts coding things, I've been painstakingly fiddling with the GIS.

The first thing I've done is to think about the places where people have walked and try to break this down into categories.  Clearly, when you walk in a city, you can't just wander where you want and you tend to follow linear features of one kind or another - particularly roads.  So I produced a list of the different types of features that appear in Eastside:
1) Primary distributor roads (e.g. Digbeth High Street)
2) Secondary distributor roads (e.g. Fazeley Street)
3) Tertiary distributor roads (i.e. any of the back streets)
4) Canal tow path
5) Paths (i.e. pedestrianised and 'other' areas)
I then looked at the areas where our interviewees have walked and redrew the map of the area, categorising all linear features into these five different types (I've posted a working model of this in the Downloads section of the RG website).

One of the problems of the GPS tracks is that they tend to wander a little bit - if you look up close at any of the tracks on the website, you'll see they often pass through buildings etc. because the accuracy is at best around 6m and, particularly around the viaducts, often quite a bit worse than this.  So I've used the tracks to draw rough 'corrected' tracks, which could then be split into pieces depending on what kind of linear feature they were passing through.  This allowed me to calculate approximate distances walked within each feature type and, again working back through the GPS logs, how long was spent on each piece of the walk.

What's the point of all this?  Well, one of the things we were interested to find out in analysing the walked interview method was whether external environmental factors had an impact on the way people walked.  Do people, for example, avoid noisy roads and, where they have to pass along them, do they walk more quickly?  Well, with all of this data about different road types, times/distances we can work this out.  And the answer is... well, sort of.  There does seem to be a bit of a tendency to spend longer walking the same distance on tertiary roads than primary. But the time/distance ratio is pretty similar for primary roads and secondary and people seem to pass most quickly at all along the canal towpath.  This might be because there's less to stop and look at, but we're going to have to look at James' content analysis data to unpick that a bit more clearly.

The other thing I've been doing is taking the hourly recordings from the University of Birmingham's weather station at the Botanic Gardens in Winterborne - just over a mile and a half away from Eastside.  I've plotted the dry bulb temperature, windspeed and level of precipitation against the length of interview, to see if there's any discernable pattern.  There's nothing especially obvious, though it's reassuring to note that the one occasion where I definitely know it was hammering with rain (Jane's interview with Julia from MADE) is the one occasion where we have rainfall recorded at Winterborne - 0.2mm in the course of an hour, which a meteorology colleague assures me is quite a lot.



So, essentially, a lot of what I've been doing has shown somewhat ambiguous/negative results, but it's good to be generating this kind of data.

This said, however, I do have some concerns that we've ended up doing some rather positivistic science i.e. reducing people to a bunch of statistics.  Particularly as those statistics are coming from the rather big brotherish surveillance technologies of GPS and GIS.  I think the tension between this kind of approach (and the inherent power imbalances it contains) as against the rather more fluffy aims about empowerment that we have in mind for the 'community' side of rescue geography are things that we're going to have to unpick at some point.

I thought I really needed to get on here and attempt to blog particularly as the lads have been so well behaved recently...

Finally figured out what my password was and as James and Phil have blogged about all the meetings I thought I would write a bit about the prep work we are doing for the "autumn laboratory" *cringe* this is most definitely a working title and hopefully we will have a better name by the end of Tuesday's meeting!

So I have been cracking the whip and forcing the terrible two to *shock-horror* plan and manage their time... there was some initial resistance as the lab is technically 4 months away, however realising I was leaving in 3weeks (and counting) seemed to convince them it was all for the best.

We managed to have 2 highly productive meetings (albeit one was very impromptu) in the last week and planned out exactly which days we were doing which activities for which groups (Schools, Professionals and Community) inlcuding deciding who else would be giving seminars for the professionals. Possibly completely confused Matt who is from UCL and spending a few weeks at MADE in August on a placement, but he seemed to go away happy in the knowledge he was going to be doing some canal side use surveying, although possibly with a very skewed vision of what working in academia was all about!

I have a list of action points as long as my arm (not that big then...) and they weren't all for me to carry out (yay!)... there are a few nitty gritty contract-styley bits to arrange between the university and MADE and deciding which lucky few get invited to the launch party for the lab/"THE BOOK" as well as constructing invite lists for the different groups who will be attending the lab to ensure we get good numbers.

Otherwise i'm just working on fleshing out the gantt chart and getting highly excited about creating sub tasks and other unrelated things such as urban explorers (www.21dayslater.co.uk); walking algorithms/psychogeography (spending far too much time with geographers it seems!); and use of pervasive media... i'm still buzzing from the pervasive media workshop I went to in Bristol yesterday.

With all this work it must be almost time for me to go to India only 14.75 working days left i calculated, but with the ACE (Arts Council) Bid decision early august, I might be back!!!

**Warning - dull post follows that is purely for my own purposes**

I'm currently playing with the first transcript, trying to come up with a way to record information from it about places that are mentioned and talked about.  The categories are a combination of things that the env psychology literature flagged up as important in terms fo how poeple relate to space and place, stuff that seems obvious to us from a methodological point of view, and some more experimental ways to try and capture local history. At the moment I have the following categories:

Tag	Number of transcript, number of occurrence
Noise level	From transcript
Env descriptor	Type of area
Box number	10 second chunk
Speech object	Thing being spoken of
Type	F (factory), C (consumption building - e.g. shop / pub), P(public building - e.g. church, school), D (domestic), R (road), E (environmental feature), I (infrastructure), O (other)
Toponymy	G (general - no specific names), D (description using names), S (specific name)
Genesis	P (interviewer prompted), U (unprompted)
Presence	Y (still there with same use), D (still there with different use), N (not there)
Spatial descriptor	How its spatial location is described: R (road), B (building), S (sight), N (no spatial ref)
Location	Where the interviewee is in relation to the thing mentioned
Story	P (personal), I (impersonal) / b = built form, c = city, p = people
Topic
Preference	p (positive), n (negative)
Evaluation	p (positive), n (negative)
Place relation	d= elsewhere in digbeth, c= city centre, b= birmingham, o=other city)

Sorry about the formatting - that happens when you import excel stuff into web text editors, but you get the picture.  There's plenty of issues - for example, some places are mentioned more than once in the transcript. It's hard to get the balance between quantifiable typology and recording some qualitative aspects of the data.  I have gone for a half-way house, with between 3 and 6 tags for each variable.   I've also numbered the 10 second boxes in the transcripts so as to get a handle on the patterns in which places are mentioned.  It may also make it easier to categorise the overall transcripts in terms of discourse type.

Phil reckons these variables can be mapped quite easily by importing into a GIS, which should produce some interesting results.  It's literally spatialising discourse!  Cool.

This one almost slipped through the net.  Last week we were invited over to Kidderminster by Ken Harrison, head of their regen team, to discuss the possibility of doing some RG work with them.  Steph came along too, in her role as our official 'handler' and to represent MADE.  Having enjoyed a free lunch in the town hall and been introduced to Matt Barker (his right hand man), Karen Alexander (arts and play officer) and Amanda Hall (conservation), we rather appropriately went out for a walk.

Kiddie seemed to have three main issues.  The closure of many of the large carpet factories located in the town centre seemed to have allowed for relatively low density retail developments to take their place.  As a result, some of the central areas resembled out of town shopping developments, with lots of ground level car parks and no real sense of place.  The second issue appeared to be the inner ring road, which not only acts as a classic concrete collar around the central area, but has broken many of the most attractive historical roads in two.  Perhaps the most distressing example of this is the separation of the beautiful church from the central area.  Finally, Kiddie seems to be a place with something of an identity crisis, with unenviable listings in two recent publications - Chav Towns and Crap Towns - compounding a general sense of malaise. 

Having said that, Ken highlighted a number of opportunities.  The town has a number of rivers running through it that could be opened up.  It also has a very attractive skyline, with the towers associated with the carpet factories slightly reminiscent of Florence and rolling countryside visible all around. Some of the areas in need of regeneration have quite unique histories, and one of these, known as the Horsefair, may be perfect for a rescue geography follow up project.  Traditionally populated by traveller communities, the area is now characterised by high levels of socio-economic deprivation and the familiar set of problems that generally accompany this. 

Plans for the area are only just being considered, and Ken emphasised the need to get the local community involved and enhance the unique heritage of the area... he put it nicely when he said there was a need to reconnect people with the space.  In terms of developing the RG methodology as an applied planning consultation tool, the Horsefair regen could be ideal.  Ken and his team also seemed very keen to collaborate, which means that we could get unprecedented access to actors at all stages of the planning process.  If RG is going to have an impact upon the development process this kind of upstream access is priceless.

We decided in principle that we would use Kiddie as the focus for our son / daughter of RG research proposal to the ESRC.  By that time it was drinks-o-clock, so we went and enjoyed a few bevvies in Ye Olde Seven Stars.

Last Thursday we met to discuss how exactly we were going to analyse the walking interview data that Jane has managed to gather over the last 8 months.  Lots of ideas have been buzzing around, mostly from the odd chat here and there, but nothing concrete had been decided.  So we decided to brainstorm it, thinking of every possible thing we could analyse, and then work through them to try and discover what would actually be possible and / or desirable to do.  Here's what we came up with...

Things we are attempting for the analysis

 

1)      Time spent talking by interviewee and interviewer as against silence in walking vs. seated interviews (word count as proxy measure)

2)      Scatter plot of general weather (Edgbaston weather data) as against length of interview

3)      Map pauses in movement / rate of movement and pauses in speech

4)      Interactions with third persons – how many, who, where, how long

5)      Time and distance of interview against: gender, age, proxy for familiarity with area, lay vs. expert

6)      Time and distance of interview in noisy environments

7)      Sensory typology against which to measure time / distance

a.       Primary distributor road, secondary distributor road, tertiary road

b.      paths

c.       canals

8)      List environmental prompts

9)      Text analysis of how much the environment acts as a prompt to discuss building or how much interviewer prompt or how much general conversation

10)  Map analysis of extent to which we are

a.       at

b.      en route to (close)

c.       en route from (close)

d.      en route to (far)

e.       en route from (far) … the building/phenomenon being discussed

11)  Can we map this against arbitrarily defined vistas/viewpoints

12)  Place discourse – speech acts revealing: preference (vs) evaluation, scale, hierarchies, informal toponymy

13)  Identification of cognitive clusters across transcripts (intertextual analysis)

Looks simple enough, but there is quite a lot of work in some of these tasks.  We split the work between spatial analysis (anything involving the GIS), which Phil is checking out, and the textual, which I'm working on.

When I started going through the first walking interview transcript two main difficulties became apparent. Firstly, in terms of people mentioning places or buildings, there are some issues with what counts.  So for example, people may mention a factory by name, and then say in passing that there were three others on such and such street.  Technically they are making a spatial reference, but in such a general way that there is little practical worth in counting it.  It is a grey area.

The second issue is how best to organise the analysis.  So, for example, we are starting with an excel spreadsheet that lists each 'place' mentioned in the transcript and then recording various characteristics about how, why and where the place is mentioned.  But boiling down these things into analytical categories is difficult, because it is hard to know how much detail to go into.  For example, is it enough to break places referred to down into buildings, environmental features and roads, or are more categories required? 

As you go along grappling with these questions the actual categories also change, as it become apparent that some of the things we thought would be important aren't, or that one category actually subsumes another.  The thing I have to keep reminding myself of is that this exploratory process of trial and error is exactly what a pilot project like RG is all about - it will take a while to figure out the best way to do things!  Anyway, my first job tomorrow it to plough through the first transcript...