fieldwork title
to what extent does quality of life vary within king’s cross
risks and ways to avoid
kidnapping - staying in large groups, in designated area
getting run over - only cross at crossings, look both ways
getting lost - school phone number, large groups, meeting points
mugging - large groups, valuabales (e.g, phones) are kept out of sight
why is king’s cross suitable for the enquiry
Has both recently developed, regenerated wealthy areas (Coals Drop Yard - CDY) and more deprived areas (Bemerton estate and Caledonian road - BE and CR). Accessible due to tube links
hypothesis for investigation
Overall QOL will be higher in the southern parts of King’s Cross (CDY), than north. Around BE, roads will be less maintained, buildings will be older.
how was secondary data used to support this investigation
Using maps, photos and articles, we could pick two areas with very different levels of development, so there’s a clear comparison, and the sites are more representative. Could further edit/ personalise questionnaire questions.
advantage and disadvantage of random sampling
+ avoid basis, allows for larger sample area
-could lead to selected areas being v close to each other, poor representation
advantage and disadvantage of systematic sampling
+ reduces human basis, good coverage of study area, simple
-not time effective, can lead to over/under representation
advantages and disadvantages of stratified sampling
+ can be used along other methods, time-efficient, can be more representative
- hard to stratify questionnaire data collection, needs to be used alongside secondary data to be accurate representation of population
what data collection methods did we use at each site
- retail diversity survey
- environmental quality survey
- photographs
- questionnaire (only at CR)
method and results of retail diversity surveys
- walk around area and tally the types of shop or service there (according to RICEPOTS categories)
- mark on map (for later land use maps)
- use formula to calculate score of retail diversity index
CDY: 0.79 CR: 0.85
RICEPOTS categories
Residential (house, flats)
Industrial (chemical, lights)
Commercial (food, shops)
Entertainment (cinema, gym)
Public building (library, hospital)
Open space (park, cemetery)
Transport (bus stop, car park)
Services (financial, medical)
what is retail diversity index
Scores an area on how diverse the shops and services available are. Number 0-0.99, closer to 1, more diverse.
evaluation of retail diversity index
WWW: RICEPOTS categorise make it easy and clear to categorise, RDI is objective and numerical so easy to compare
Limits: some shops fit into multiple categories, didn’t include the general price range in these shops
Next time: more specific categories, pick areas of similar size, include some kind of pricing score
EQS and photos method
- divided each site (CYD) and (BE) into 3 areas
- in each site, gave score from 1-5 on quality of area, buildings, services and traffic infrastructure
CYD: 60-71
BE+CR: 45-49 - took photos at each site
Questionnaire method
- opportunistic sampling strategy (who agreed)
- asked 7 closed questions and 1 open question
WWW and limitations of retail diversity index
+ provided a figure for clear numerical comparison
+ reduced bias with clear categories
- some shops didn’t fit into 1 category
- areas were different size (CR much larger)
WWW and limitations of EQS
+ considered a lot of factors relating to QOL
+ numerical scores allowed for easy comparison
- subjective scoring
- hard to tell where grid squares began and ended
- bias in large squares so could pick area within that
WWW and limitations of photos
+ geolocated & provided context for EQS
+ captures lots of data easily
- bias for angle photo taken at (360 vid would be better)
- need annotations for context
WWW and limitations of questionnaires
+ questions easy to answer (numerical score), making easy to compare with other data points
+ good mix of open and closed Qs
- couldn’t tell who were residents
- bias as residents won’t talk badly about their homes
- time of day limits demographic
what were the data presentation methods we used
- land use maps
- GIS located proportional symbols
- annotated photos
- 100% stacked bar chart
description of land use maps
letter codes on a goad (street) map with key to identify where different services were located
description of GIS located proportional circles
- to present EQS scores
- map with circles shaded according to EQS score (darker = higher score)
description of annotated photos
- geolocated photos placed around the EQS map to contextualise the data
description of 100% stacked bar chart
One bar for each question and divided into segments proportional to the frequency of each response
