You can rank every Division & District for each individual offence. This tells you which Districts and Divisions have the highest crime rates in each offence. Queries on the Index page
relate to 2016 QPS data only.
You can click on the resulting Districts or Divisions which will then chart the crime rate for that District or Division for QPS data from all available years - from January 2001 to June 2017.
The home page also holds a searchable version of the Cashless Debit Card 'approved (online) merchants'. All online merchants (businesses, charities & other organisations) are
banned for use by holders of the Cashless Debit Card provided on behalf of government by Indue. There are over 2 million registered business in Australia alone which puts into context the fact that the approved merchant list holds less than 2,000.
This page has the functionality to chart crime rate data & actual offence number from January 2001 to June 2017 for each offence by District or Divison. Mouse over the chart to see the monthly crime rates and select a view which will change the width of the chart to provide more nuanced
This page has the functionality to chart crime rate data from July 1997 to September 2017 for the state. You get a birds-eye
view of the trend for each offence and offence group for the years available.
Offence groups are groupings of similar offences with sub-totals provided by QPS. These sub-totals are averaged and charted using Google charts API.
Breakdown of victims by gender for relevant offences and offence groups is available for the state.
Queensland Police Service statistical data is provided for different year rages for different datasets:
The SEIFA and population data used in this project is made available under CC by 4.0 by
POLSIS Profiles: Resident Profile for Sunshine Coast Police District, Queensland Government Statisticianâ€™s
Office, Queensland Treasury.
'Socio-Economic Indexes for Areas (SEIFA) is a summary
measure of the social and economic conditions of geographic
areas across Australia. SEIFA, which comprises a number of
indexes, is generated by ABS from the Census of Population
and Housing. In 2011 an Index of Relative Socio-Economic
Disadvantage was produced, ranking geographical areas in
terms of their relative socio-economic disadvantage. The index
focuses on low-income earners, relatively lower education
attainment, high unemployment and dwellings without motor
vehicles. Low index values represent areas of most
disadvantage and high values represent areas of least
disadvantage. This is based on persons by place of usual
residence.' (POLSIS Resident Profiles, 2017)
SEIFA percentages are used as provided with no transformation. They do not always add to 100%.
QLD Police Service commands are broken down into three types of areas:
Regions, Districts and Divisions (largest to smallest).
These do not correspond to ABS boundaries so the population and
socio-economic indicator data is calculated by POLSIS specifically for QPS.
The crime rate figures shown in the home page (available at QPS) relate only to 2016 and have been transformed by me from the raw data by by summing and averaging for each of 73 offence types
to derive a single figure for the 2016 year for each offence by area. ie The rate of each offence per 100,000 is averaged over the year for each District and Division.
Data in other pages is available as far back as either 2001 for the District & Division crime rates & actual offence numbers and right back to 1997 for state-wide crime data.
Users of the project may notice that rates between District and Division vary substantially in that when ranking both Districts and Divsisions from highest to lowest for each
offence, Divisions consistently return higher rates of offending than Districts those Divisions are part of.
This is an effect of the size of the population used for each area. For example, an area which is small in population like Fraser Island (approx 200) returns a high rate of crime per head of population because
when a crime occurs there and it is cacluating that offence as a proportion of a small number of people.
When that area is included in a wider administrative boundary such as District, the rate evens out as the population on which it is based is much larger and includes Divisions with lower rates.
This tendency to exaggerate the crime rates in Divisions with small populations shows how difficult it is to use administative data to draw conclusions when the
areas being compared to more populated areas.
Total of averaged rates for 2016 per 100k head of pop. (also averaged across 73 offences)
Source: QLD Police Reported Crime Trends Data 2016 QLD Police
Data is provided by QPS for each of 73 diferent offences in each Division. Crime rates are calculated & provided by QPS
month by month so each of those 73 offences has 12 data points which I have averaged over a single year to produce one figure for each of the 73 offence types.
Those 73 figures are then averaged to produce a single figure for each Division that can be used to rank Divisions. Estimated Residential Population figures from the 2016 Census are provided in POLSIS Community Profiles and are included to provide context.
When calculated on very small populations, QPS crime rates per 100,000 ERP produce high rates. This needs to be taken into consideration.
This site has been created by Rosie Williams (BA Soc) to assist with research into blanket income management using the 'Cashless Debit Card'. This work relies on a degree in Sociology including units in criminology, juvenile justice & public policy, years of coding using PHP, MySQL etc and experience with long term poverty.
If you would like to support the work that I do please donate.
The expansion of this project to include other states would require that crime rate data is made available by the states in the same granularity for the same time periods.
This project is an example of how quality open data can be used to provide information to the public however as is often the case, availability of data is not consistent across jurisdictions, and as is always the case, there is no one willing to fund these types of projects.
Code and database design by Rosie Williams |
Data provided by government |
Icons made by Freepik
(20,038) hits to index page from (967) Unique IP's