I caught an episode of Woman’s Hour last week in which the presenter kept mentioning that according to a recent survey 62% of people in the UK had volunteered in the last week, and inviting people to discuss their experiences of voluntary work.
The show was then peppered with references to people’s volunteering efforts, such as working with the homeless at Christmas, staffing food banks, helping out with the Covid-vaccination efforts and so on.
And such examples fit very well with my own imagination of what ‘voluntary work’ involves – to my my mind a volunteer is someone who commits an hour or maybe more a week (I have a low bar in terms of time!) to do something such as the above, probably in conjunction with a formal charity or at least other people as part of a team.
But I just couldn’t believe that 62% of people did that kind of voluntary work last year.
And it turns out that they don’t
The government survey (a form of official statistics) that yielded these results distinguishes between formal and informal volunteering.
The former type: formal volunteering is what I (and probably most people) think of as ‘real volunteering’ – it was these kind of things the Woman’s Hour presenter was interested in hearing about and publicising.
However, only 17% of people did formal volunteering last year…..
Just over 50% of people did ‘informal volunteering’ but this has a VERY LOW BAR for inclusion. Basically, if you babysat your friend’s kids for one day at some point last year, you get to tick the box saying that you did ‘informal volunteering’.
This basically means that ANYONE with a young family has done what this society defines as ‘informal volunteering’ – I mean surely EVERY FAMILY babysits once in a while for their friends – this is just normal parenting – children have friends, parents want a day to themselves every now and then so you ‘babysit swap’ – or sleepovers, technically you could count having your friends’ children over for a sleepover with your own kids as ‘having done voluntary work’ in the last year’.
Add formal and informal volunteering (/ mutal parental favours) together and you get that 62% figure that the Woman’s Hour presenter was talking about.
However to my mind 62% is a completely misleading figure – 17% is how many people ACTUALLY volunteer every year!
It’s a bit annoying TBH – as also in the ‘informal volunteerin’ category are things such as buying shopping for someone who can’t get out of the house and that’s LEGIT, or valid volunteering in my mind, but the category is too inclusive to give us any useful data on this.
Relevance to A-Level Sociology
This is a wonderful example of how a definition which is too broad, in this case what counts as ‘volunteering’ can give a misleading, or invalid impressing of how much actual voluntary work really goes on in the UK.
This survey is a form of official statistics, so you can use this example to be critical of them.
it is possible that the government officials deliberately made the definition so broad so as to give the impression that there is more community spirit, or more of a ‘big society’ around than there actually is – because if there’s lots of community work and voluntary work going on, it’s easier for the government to justify doing less.
However, even with these very broad definitions, the trend in volunteering has still been going down in recent years!
The figures show that women commit less crime than men, and less serious crimes than men.
This is an important update for the gender and crime topic which makes up part of the A-level sociology crime and deviance module.
There are approximately equal numbers of men and women in the population as a whole, but 85% of people arrested are male, around 75% of those prosecuted are male and 95% of people who go to prison are male, meaning women only make up 5% of the total prison population.
Both the male and female crime rates seem to have been declining over the last five years of statistics, with fewer men and women being dealt with by the criminal justice system.
The male crime rate does seem to be declining faster than the female crime rate, with the female crime rate seeming to level off somewhat more recently.
Men Commit more serious crimes than women (I)
‘Indictable offenses’ in the darkest blue below are those more serious offences dealt with by the crown court. Men are twice as likely to be on trial for an indictable offence compared to women.
78% of males are in court for summary (less serious offences) compared to 90% of women, and men are more likely to on trial for motoring offences!
Men commit more serious crimes than women (II)
The chart below shows you that for the more serious, indictable offences such as violence and robbery, men commit around 85-90% of these, but for sexual offenses 98% of offenders are men, only 2% are women.
The most equal in terms of gender are fraud offences and summary non-motoring offences….
Women only make up 5% of the prison population
This is related to their committing less crime and less serious crime than men, although some sociologists (read on!) have argued this is because the courts are more lenient towards women (others argue it’s the opposite, saying the course are harsher towards women.
One of the supposed advantages of official statistics is that they are quick and easy to use to find out basic information.
To test this out, I use the following as a starter for my ‘official statistics’ lesson with my A-level sociology students:
I print the above off as a one paged hand-out and give students 10 minutes to find out the approximate answers to each of the questions.
If some students manage to find all of them in less than 10 minutes, they can reflect on the final question about validity. I wouldn’t expect all students to get to this, but all of them can benefit from it during class discussion after the task.
Official statistics stater: answers
Below are the answers to the questions (put here because of the need to keep updating them!)
How many cases of Domestic Violence were there in England and Wales last year?
In the year ending March 2019, an estimated 2.4 million adults aged 16 to 74 years experienced domestic abuse in the last year (1.6 million women and 786,000 men).
It’s hard to make an arguement that the last two have poor validity – however, you can argue that these are invalid measurements of students’ ability, because of variations in difficulty of the exams and a range of other factors.
With the DV stats, there are several reasons why these cases may go under reported such as fear and shame on the part of the victims.
Marriages, there may be a few unrecorded forced marriages in the UK.
In terms of households, the validity is pretty high, as you just count the number of houses and flats, however, definitions of what counts as a household could lead to varying interepretations of the numbers.
The population stats are an interesting one – we have records of births, deaths and migration, but illegal immigration, well be it’s nature it’s difficult to measure!
The point of this starter and what comes next…
It’s kinaesthetic demonstration of the practical advantages of official statistics, and gives students a chance to think about validity for themselves.
Following the starter, we crack on with official statisics proper – considering in more depth the strengths and limitations of different types of official statistics, drawn from other parts of the A-level sociology specification.
A-level teaching resources
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Unlike Pearsons or Tutor to You (however you spell it), I’m independent, all subscription money comes straight to me, rather than the resource designers getting a pittance and 90% of the money going to the corporates at the top, like with those companies.
Is life in the UK getting better or worse? In this post I evaluate this question by looking at a few official statistics.
Is life in the UK getting better or worse?
This post looks at a few economic and social indicators to see what they suggest about trends in desirable social goods such as economic growth, employment and happiness and less desirable social problems such as crime, mental ill-health and suicide.
The point of this posts is to showcase some of the official statistics we might use to judge the state of the nation. These are the kind of stats we can use to evaluate the Functionalist view that ‘everything in society is generally OK’, compared to other more critical perspectives such as Marxism, Feminism or even Postmodernism.
You should always be critical of the validity of statistics, especially since most of the stats below are official statistics – they are collected by government agencies…
A social or economic indicator might suggest life in the UK is generally getting better or worse, but this might not actually be the case when you scratch beneath the surface.
For example, an increase in recorded crime may not be because of an underlying increase, but rather because people are more aware of certain types of crime and more likely to report those crimes.
Similarly, a decrease in unemployment may just be because more people are fearful of claiming benefits, even though they need them, because of the increased hassle and stigma of claiming them.
Any statistics that use averages may also give us a misleading picture of the ‘health of the nation’. For example, average income can trend upwards, but this doesn’t tell us how that income is distributed – it may mean the top 1/10th getting a lot richer and the bottom 1/10th getting a lot poorer.
Averages can also hide wide variations in how social goods and harms are distributed by gender and ethnicity and age. The male suicide rate is around three times higher than the female suicide rate.
Employment is increasing, unemployment is declining
The employment rate is at a record high of 76.3%, while the unemployment rate has been declining for 6 years, and stands at a very low 3.8%
Fewer households in absolute poverty, the same amount in relative poverty
If we look at households in ‘absolute low income’ (the bottom two graphs below) then we see a decline. Focusing on the ‘after housing costs’ statistics:
In 2002/03 24% of households were in absolute low income, compared to only 19% in 2017/18.
If we look at relative low income, there is no change over time, 22% of households are still classified as low income households.
However, some types of crime have increased recently
Robbery and knife crime have increased recently, although there are very few cases of these types of crime compared to theft and fraud, and while the later has increased, the impact of fraud on victims is probably less harmful than for most other types of crime.
The mean happiness score (/10) for the UK population has increased to all time high of 7.56. ‘Life satisfaction’ and ‘worthwhileness’ scores are also increasing
Anxiety levels are stable
The mean anxiety score (/10) has remained stable at just below 3/10 for half a decade, while the percentage of people reporting high levels of anxiety remains at just under 20%.
In 2018, the UK’s population reached 66.4 million people, with a growth rate of 0.6% and immigration being the main reason for population growth.
The population is increasing at roughly 350 000 people per year, just over 100 000 of these are due to ‘natural change’ (more births than deaths) while just over 200 000 are due to net migration (more people immigrating than emigrating.
Conclusion: Is life in the UK getting better or worse?
On balance I’d say that the official statistics above suggest that, on average, life in the UK is getting better:
Employment and poverty are both down.
Crime is generally down
Happiness is increasing and anxiety is stable
However, there has been a recent spike in the suicide rate and some types of violent crime are up.
It’s very difficult to say whether or not the increasing population is a positive or a negative: clearly the fact that this is driven mainly by immigration concerns a lot of people, but possibly we need migration to offset the increasing dependency ration associated with the aging population, so this might actually be a good sign!
Question: what other stats do you think should be included in the above?
The 2018 report shows that the overall rate of permanent exclusions was 0.1 per cent of pupil enrolments in 2016/17. The number of exclusions was 7,720.
The report also goes into more detail, for example….
The vast majority of exclusions were from secondary schools >85% of exclusions.
The three main reasons for permanent exclusions (not counting ‘other’) were
Persistent disruptive behaviour
Physical assault against a pupil
Physical assault against an adult.
Certain groups of students are far more likely to be permanently excluded:
Free School Meals (FSM) pupils had a permanent exclusion rate four times higher than non-FSM pupils
FSM pupils accounted for 40.0% of all permanent exclusions
The permanent exclusion rate for boys was over three times higher than that for girls
Over half of all permanent exclusions occur in national curriculum year 9 or above. A quarter of all permanent exclusions were for pupils aged 14
Black Caribbean pupils had a permanent exclusion rate nearly three times higher than the school population as a whole.
Pupils with identified special educational needs (SEN) accounted for around half of all permanent exclusions
The ‘reasons why’ and ‘types of pupil’ data probably hold no surprises, but NB there are quite a few limitations with the above data, and so these stats should be treated with caution!
Limitations of data on permanent exclusions
Validity problems…
According to this Guardian article, the figures do not take into account ‘informal exclusions’ or ‘off-rolling’ – where schools convince parents to withdraw their children without making a formal exclusion order – technically it’s then down to the parents to enrol their child at another institution or home-educate them, but in many cases this doesn’t happen.
According to research conducted by FFT Education Datalab up to 7, 700 students go missing from the school role between year 7 and year 11 when they are supposed to sit their GCSEs…. Equivalent to a 1.4% drop out rate across from first enrolment at secondary school to GCSEs.
Datalabs took their figures from the annual school census and the DfE’s national pupil database. The cohort’s numbers were traced from year seven, the first year of secondary school, up until taking their GCSEs in 2017.
The entire cohort enrolled in year 7 in state schools in England in 2013 was 550,000 children
However, by time of sitting GCSEs:
8,700 pupils were in alternative provision or pupil referral units,
nearly 2,500 had moved to special schools
22,000 had left the state sector (an increase from 20,000 in 2014) Of the 22,000,
3,000 had moved to mainstream private schools
Just under 4,000 were enrolled or sat their GCSEs at a variety of other education institutions.
60% of the remaining 15,000 children were likely to have moved away from England, in some case to other parts of the UK such as Wales (used emigration data by age and internal migration data to estimate that around)
Leaves between 6,000 to 7,700 former pupils unaccounted for, who appear not to have sat any GCSE or equivalent qualifications or been counted in school data.
Working out the percentages this means that by GCSEs, the following percentages of the original year 7 cohort had been ‘moved on’ to other schools.
6% or 32, 000 students in all, 10, 00 of which were moved to ‘state funded alternative provision, e.g. Pupil Referral Units.
4%, or 22K left the mainstream state sector altogether (presumably due to exclusion or ‘coerced withdrawal’ (i.e. off rolling), of which
4%, or 7, 700 cannot be found in any educational records!
This Guardian article provides a decent summary of the research.
Further limitations of data on school exclusions
There is very little detail on why pupils were excluded, other than the ‘main reason’ formally recorded by the head teacher in all school. There is no information at all about the specific act or the broader context. Labelling theorists might have something to say about this!
There is a significant time gap between recording and publication of the data. This data was published in summer 2018 and covers exclusions in the academic year 2016-2017. Given that you might be looking at this in 2019 (data is published annually) and that there is probably a ‘long history’ behind many exclusions (i.e. pupils probably get more than one second chance), this data refers to events that happened 2 or more years ago.
Relevance of this to A-level sociology
This is of obvious relevance to the education module… it might be something of a wake up call that 4% of students leave mainstream secondary education before making it to GCSEs, and than 1.4% seem to end up out of education and not sitting GCSEs!
How doe we explain the recent increase in higher education student suicides? Are there any underlying causes, or is this just a ‘moral panic’?
There has been an increase in the suicide rate among Higher Education students, from 3.8 per 100, 000 in 2006/07 to 4.7 suicides per 100, 000 in 2016/17, according to new data released this week by the Office for National Statistics (ONS).
Google headlines for ‘student suicide’ search, June 26th 2018
NB this isn’t only the latest data, it is also ‘new’ in the sense that this is the first time that the ONS has published data specifically focussing on ‘higher education student’ suicides, so in this sense I guess it is inherently news worthy, and the release of the data on the 25/06 certainly caused quite a stir in the mainstream news and talk shows following the release, with the main focus seeming to be on ‘what we should do about the problem of increasing student suicides’, and the fact that this is ‘new data’.
However, to my mind, while I appreciate the fact that there is an underlying increase in students reporting mental health issues that seems to correlate with the increase in suicide, I also believe there’s reason to be sceptical about the usefulness of the above data, especially since the ONS itself refers to these stats as ‘experimental statistics’.
Below, I summarise what the ONS data tells us about HE student suicides, and then contrast two sociological approaches to interpreting this data: the first being a broadly ‘structuralist’ perspective which accepts that the data is basically valid and asks ‘why are there more student suicides?’ (which was pretty much the narrative in the mainstream news); and a second, broadly Interpretivist approach which questions the validity of this data, and asks whether or not all of this might be something of a moral panic?
What does the data tell us?
Firstly, there has been an increase in the suicide rate among higher education students if we compare the data from 2006/07 to 206/17
However, although the data appears to have stabilized in the the last three years, the ONS reminds us that these rates are based on such low numbers (95 suicides in 2016/17) that it’s hard to draw any statistical significance from these figures.
Secondly, male students are approximately twice as likely to commit suicide than female students
Between the years of 2001 and 2017, a total 1,330 students died from suicide, of which 878 (66%) were male and 452 (34%) were female.
Thirdly, older students are more likely to kill themselves than younger students
This actually surprised me a little (note to self about ‘stereotypes’ of suicidal students): higher education students aged 30 or over are twice as likely to commit suicide compared to students aged 20 and under.
Some limitations of the above data
I recommend checking out the publication (link above and below at the end) by the ONS, they mention several limitations with this data: for example, the low overall numbers make it hard to draw any conclusions about the suicide rate with any degree of confidence (statistical significance); and the year on year on year data might not be accurate given delays in recording a death as a suicide, due to inquests taking a long time in some instances (e.g. a suicide which happened in 2016 might appear as a recorded suicide in 2017).
What are the underlying ’causes’ of the ‘increase’ in student suicides?
The mainstream media narrative pretty much took the increase in student suicides at face value, and offered up some of the following possible reasons to explain the increase:
The suicide stats are the ‘extreme ‘tip’ of something of a ‘mental health crisis’ in universities – higher number of students are making use of mental health services, which are under-resourced: universities aren’t giving enough support to vulnerable students who are suicidal.
The increase in mental health problems/ suicide could be due to the fact that university life has become more stressful: there’s more pressure to succeed and get at least a 2.1, and students no longer go to university to have ‘three years off’ (like I did ;)).
Related to the above, mental health problems could be related to the ‘double adjustment’ (my invention that!) students have to go through: they have to adjust not only to the fact that university life isn’t as much fun as its been made out to be (at yer glossy open day), and they have to adjust to the fact that they are just not ‘that clever’ (the later probably applies more to hot-housed privately schooled students, and to those students who are more likely to have had their predicted grades inflated).
A broadly Interpretivist approach to understanding these stats…
Interpretivists would be much more likely to question the validity of these stats, and thus the validity of the view that there is an increase in higher education student suicides, and the opinion that this is something which we should be concerned about.
There are certainly sufficient grounds to be sceptical about these stats:
If you were to compare the three year average for 2002/03 to 2004/05 with the three year average for 2014/15 to 20016/17 the ‘increase’ is much less significant.
The ONS itself says you cannot draw any significant conclusions from the small numbers used to derive these stats. And again, they even explicitly refer to them as ‘experimental stats’!
The overall number of student suicides is half that of the suicide rate in the general population: surely the headlines should be: ‘”great news, going to university helps lower suicide risk”?
There might also be an argument to made that this is something of a moral panic: it seems to me that the media perpetuate the idea that the typical suicidal student is a 19 year old female, when actually this is atypical – a 30+ year old male student is about 4 times more likely to kill himself.
I also think ‘class’ might come into this: Bristol University (A Russel Group, and thus a very middle class university) has been in the news recently due to its high suicide rates:
So, might this uncritical news reporting just really be about stoking a moral panic not so much about the ‘increase’ in higher education student suicides (of which there appears to be no significant evidence), but really about the increase in suicide among our ‘precious’ middle class male students?
Official Statistics are a quick and cheap means of accessing data relevant to an entire population in a country.
They are cheap for researchers to use because they are collected by governments, who often make them available online for free—for example, the UK Census.
Marxists might point out that the fact they are free enables marginalised groups to ‘keep a check on government’.
More generally, they are useful for making quick evaluations of government policy, to see if tax payers’ money is being spent effectively–
Official statistics are a very convenient way of making cross national comparisons without visiting other countries.
Most governments in the developed world today collect official statistics which are made available for free.
More and more governments collect data around the world, so there is more and more data available every year.
The United Nations Development Programme collects the same data in the same way, so it’s easy to assess the relationship between economic and social development in a global age.
Theory and Methods A Level Sociology Revision Bundle
If you like this sort of thing, then you might like my Theory and Methods Revision Bundle – specifically designed to get students through the theory and methods sections of A level sociology papers 1 and 3.
Contents include:
74 pages of revision notes
15 mind maps on various topics within theory and methods
Official Statistics on schools, teachers and educational achievement provided by the United Kingdom government provide an overview of the education system. They are useful for providing an ‘introduction to the state of education in the U.K’, before embarking on the core content of any sociology of education course and providing a basis for comparing the U.K. education system to the education systems of other countries, which would be relevant to the module on global development.
I will also provide a brief discussion of the validity and representativeness of the official statistics below, tying this into research methods.
I only deal with state-schools in this post, I’ll do a separate post in future on private, or independent schools in comparison to state schools.
Also, the post below deals primarily with England and Wales, I will add in details for Wales and Scotland when I can.
For 2020-21 expenditure per education sector broke down as follows:
Primary education expenditure – £27.3 billion
Secondary education expenditure – £40.0 billion
Tertiary education expenditure – £4.9 billion
Spending Per Pupil was £6500 in 2019-2020
The above chart, from the Institute for Fiscal Studies shows us education spending in real terms at 2019-2020 places. We can see that in real terms expenditure per pupil has decreased slightly since 2010, when New Labour left office and the Tories came to power.
This means primary schools are lot smaller in scale in that each of them has, on average, fewer pupils in them, and should be more ‘locally based’ for most parents.
Secondary schools are a lot larger, will have many more pupils in them, have more of an ‘education factory’ feel to them and be more widely dispersed, meaning children will have to travel further to them.
This is despite the fact that there are more secondary school aged pupils compared to primary school aged pupils.
There were 10.5 million school pupils in England and Wales in 2020-2021
This reflects recent demographic trends in the United Kingdom – a baby boom which started in the mid 2000s has seen an increase of 400 000 pupils in the school system as a whole (primary and secondary).
There were 11 600 pupils in Pupil Referral Units in 2021
The number of pupils in PRUs fell from over 15000 in 2015/16 to just just 11 000 by 2020/21
A total of 12.6% of pupils have Special Education Needs in 2021-2022
And four percent of these have a formal statement.
There has been a slight increase in the number of Special Education Needs pupils since 2015/ 16 – a 1% increase in all SEN pupils and a 1.2% increase in SEN pupils with statements.
I’ve left the following historical data in place following a recent update of this post (updated October 2022) as I think it demonstrates how such statistics in particular are socially constructed…
Between 2010 to 2015 the number of pupils with special educational needs fell from 21% to 15%
NB – if you read this in conjunction with the ‘types of school chart’ above, then it suggests that special educational needs (SEN) students are becoming increasingly segregated into special schools and/ or pupil referral units, rather than being dealt with in mainstream secondary schools.
You might also want to think about the extent to which ‘Special Educational Needs’ and ‘Special Educational Needs with statements’ are socially constructed.
Looking back at 2007, 20% of pupils were officially characterised as SEN, but by 2021 this had fallen to 12.6%.
According to labelling theory this is more likely to be because the formal criteria and processes according to which pupils are given the SEN label have changed over the past 15 years, rather than any underlying changes in the actual number of pupils with Special Educational needs.
At the end of 2020 the proportion of 16-18 year olds in education and work-based learning was 81.2%
NEET stands for ‘Not in Education, Employment or Training’ and the government keeps records of the proportion of 16-14 year olds which fit into this category.
The medium term trend in NEETs is that the proportion has fallen from 16% of 16-24 year olds in 2013 down to 11% in 2017.
The NEET figure has been relatively stable for the last five years, holding at around 11% up until today in 2022.
There were 2.4 million students in UK Higher Education Institutions in 2019-2020
The number of full time equivalent students studying their first degrees or post graduate degrees has been increasing steadily over the past few years.
Around 1.9 million students are studying undergraduate degrees or equivalent while 0.5 million are studying towards a Postgraduate degree.
The vast majority of students studying towards their first degree are British, almost 80% in fact, but around 40% of students studying PostGraduate degrees in UK institutions are from abroad, and most of those from outside the UK!
There were 465000 Teachers (FTE) in the UK in 2021/22
There were 465 000 Full Time Equivalent (FTE) teachers employed in England and Wales in 2021/22.
There were 503 000 Full Time Equivalent support staff
The total FTE number of staff employed in schools in 2021/22 was 968 000.
30% of teachers drop out after 5 years of qualifying
12.5% of teachers drop out after just one year of qualifying
Just over 30% drop out within five years.
How useful are these education statistics?
Such statistics are a useful starting point if we wish to make cross-national comparisons between the U.K. education system and the rest of the world, which would be useful for students of global development, given that education plays a key role in development. Indeed if we wish to compare the relationship between education and development in several countries, statistical rather than qualitative comparisons may be the only way of doing so.
From an arrogant, modernisation theory perspective, these statistics provide an indication of the level of investment required in terms of expenditure and teachers, and the types of outcome that less developed countries should be aiming for.
Most of the education statistics above count as ‘hard statistics’, i.e. there’s little room for disagreement over the ‘social facts’ which they show – for example, it’s hard to argue with the stats on ‘number of schools’ and ‘number of qualified teachers’.
However, others are much softer, and have more validity problems, and can be criticised for being social constructions rather than reflecting underlying reality: the statistics on special educational needs clearly come under this category – there is simply no way the underlying numbers of students with ‘SEN’ have decline from 21 to 15% in 5 years while the number of certificated SEN kids have increased – what’s really happened is that the number of kids which schools categorise as having Special Education Needs has decreased in the last 5 years, probably because the Tory’s cut previously existing funding for this category of student in 2010 (ish).
Signposting and Related Posts
As mentioned above this is introductory material for the education topic. For more posts covering theories of education, education policies and educational inequalities by class, gender and ethnicity, please see my sociology of education page.
Links to statistics on education in the United Kingdom:
Most of the statistical sets below are updated yearly, or more frequently.
Education and Training Statistics for the U.K. – published by the department for education. In this source you’ll find data on the number of schools, teachers, and teacher-pupil ratios as well as basic educational achievement data by Free School Meals, gender and ethnicity. Published annually in November.
School Workforce in England – covers teacher numbers and pupil-teacher ratios in primary and secondary schools in England and Wales. The latest figures from November 2021.
Special Education Needs in England – details of children with special education needs, by type of need, and broken down by school type and gender (statistics derived from the ‘schools census’).
Official Statistics are numerical data collected by governments and their agencies. This post examines a ranges of official statistics collected by the United Kingdom government and evaluates their usefulness.
Click the image to search 13, 848 official statistics produced by the U.K. government
The aim of this post is to demonstrate one of the main strengths of official statistics – they give us a ‘snap shot’ of life in the U.K. and they enable us to easily identify trends over time.
Of course the validity and thus the usefulness of official statistics data varies enormously between different types of official statistic, and this post also looks at the relative strengths and limitations of these different types of official statistic: some of these statistics are ‘hard statistics’, they are objective, and there is little disagreement over how to measure what is being measured (the number of schools in the U.K. for example), whereas others are ‘softer statistics’ because there is more disagreement over the definitions of the concepts which are being measured (the number of pupils with Special Educational Needs, for example).
If you’re a student working through this, there are two aims accompanied with this post:
After you’ve read through this material, do the ‘U.K. official statistics validity ranking exercise’.
Please click on the images below to explore the data further using the relevant ONS data sets and analysis pages.
Ethnic Identity in the United Kingdom According the U.K. 2011 Census
U.K. Census 2011 data showed us that 86% of people in the United Kingdom identified themselves as ‘white’ in 2011.
How valid are these statistics?
To an extent, ethnic identity is an objective matter – for example, I was kind of ‘born white’ in that both my parents are/ were white, all of my grandparents were white, and all of my great-grandparents were white, so I can’t really claim I belong to any other ethnic group. However, although I ticked ‘white’ box when I did the U.K. Census, this personally means very little to me, whereas to others (probably the kind of people I wouldn’t get along with very well) their ‘whiteness’ is a very important part of their identity, so there’s a whole range of different subjective meanings that go along with whatever ethnic identity box people ticked. Census data tells us nothing about this.
Religion according to the U.K. 2011 Census
In the 2011 Census, 59% of people identified as ‘Christian’ in 2011, the second largest ‘religious group’ was ‘no religion’, which 25% of the U.K. population identified with.
Statistics on religious affiliation may also lack validity – are 59% of people really Christian? And if they really are, then what does this actually mean? Church attendance is significantly lower than 59% of the population, so the ‘Christian’ box covers everything from devout fundamentalists to people that are just covering their bases (‘I’d better tick yes, just in case there is a God, or gods?’)
The British Humanist Society present a nice summary of why statistics on religious belief may lack validity…basically based on the ‘harder’ statistics such as church attendance which show a much lower rate of committed religious practice.
The United Kingdom Employment Rate
The employment rate is the proportion of people aged from 16 to 64 in work.
The lowest employment rate for people was 65.6% in 1983, during the economic downturn of the early 1980s. The employment rates for people, men and women have been generally increasing since early 2012.As of December 2016, the employment rate for all people was 74.6%, the highest since records began in 1971
Household Income Distribution in the United Kingdom
Household income statistics are broken down into the following three broad categories:
original income is income before government intervention (benefits)
gross income is income after benefits but before tax
disposable income is income after benefits and tax (income tax, National Insurance and council tax).
In the year ending 2016, after cash benefits were taken into account, the richest fifth had an average income that was roughly 6 times the poorest fifth (gross incomes of £87,600 per year compared with £14,800, respectively)
Reasons why household income data may lack validity
While measuring income does appear to be purely objective (you just add and minus the pounds), the income data above may lack validity because some people might not declare some of the income they are earning. Cash in hand work, for example, would not be included in the above statistics, and some money earned via the ‘gig economy’ might not be declared either – how many people actually pay tax on their YouTube revenue for example, or from the goods they sell on Ebay?
The United Kingdom Crime Rate
Below I discuss data from the Crime Survey of England and Wales (CSEW), which is a victim-survey conducted by structured interview with 35 000 households. It seems pointless discussing the crime rate according to police recorded crime because it’s such an obviously invalid measurement of crime (and the police know it), simply because so many crimes go unreported and hence unrecorded by the police.
Latest figures from the Crime Survey for England and Wales (CSEW) show there were an estimated 6.1 million incidents of crime experienced by adults aged 16 and over based on interviews in the survey year ending December 2016.
The green dot shows the figure if we include computer based crimes and online fraud, a new type of crime only recently introduced to the survey (so it wouldn’t be fair to make comparisons over time!) – if we include these the number of incidents of crime experienced jumps up to 11.5 million.
Reasons why even the CSEW might lack validity
Even though its almost certainly more valid than police recorded crime – there are still reasons why the CSEW may not report all crimes – domestic crimes may go under-reported because the perpetrator might be in close proximity to the victim during the survey (it’s a household survey), or people might mis-remember crimes, and there are certain crimes that the CSEW does not ask about – such as whether you’ve been a victim of Corporate Crime.
The U.K. Prison Population
The average prison population has increased from just over 17,400 in 1900 to just over 85,300 in 2016 (a five-fold increase). Since 2010, the average prison population has again remained relatively stable.
Prison Population Statistics – Probably have Good Validity?
I’ve included this as it’s hard to argue with the validity of prison population stats. Someone is either held in custody or they or not at the time of the population survey (which are done weekly!) – A good example of a truly ‘hard’ statistic! This does of course assume we have open and due process where the law and courts are concerned.
Of course you could argue for the sake of it that they lack validity – what about hidden prisoners, or people under false imprisonment? I’m sure in other countries (North Korea?) – their prison stats are totally invalid, if they keep any!
United Kingdom Population and Migration Data
Net migration to the U.K. stood at 248 000 in 2016, lower than the previous year, but still historically high compared to the 1980s-1990s.
There are a number of reasons why UK immigration statistics may lack validity
According to this migration statistics methodology document only about 1/30 people are screened (asked detailed questions about whether they are long term migrants or not), on entering the United Kingdom, and only a very small sample of people (around 4000) are subjected to the more detailed International Passenger Survey.
Then of course there is the issue of people who enter Britain legally but lie about their intentions to remain permanently, as well as people who are smuggled in. In short the above statistics are just based on the people the authorities know about, so while I’m one to go all ‘moral panic’ on the issue of immigration, there is sufficient reason to be sceptical about the validity of the official figures!
Ranking Exercise:
You might like to rank the following ‘official statistics’ in terms of validity – which of these statistics is closest to actual reality?
Immigration statistics – Net migration in 2016 was 248 000
Prison statistics – There are just over 85 000 people in prison
Crime statistics – There were around 6 million incidents of crime in 2016
The richest 20% of households had an average income of around £85 000 in 2016
Please click the pictures above to follow links to sources…
The United Kingdom Census is a survey of every person in the United Kingdom, carried out every 10 years, the last one being in March 2011. It asks a series of ‘basic’ questions about sex, ethnicity, religion and occupation. It is the only survey which is based on a ‘total sample’ of all U.K. households. You might also like this summary – What is a Census?
A summary of how ethnic minorities are over-represented at different stages of the criminal ‘justice’ process in England and Wales
Official government statistics suggest that both black and asian people are more likely to be stopped by the police and go to jail than white people in England today.
The Home Office records statistics on the ethnic backgrounds of people as they ‘progress’ through the criminal justice system, such as:
The latest report notes that ethnic minorities, especially black people are over-represented at many stages of the criminal justice process – but especially in the stop and search practice.
The figures below show the percentages of different ethnic groups represented through stop and search to the prison population:
NB the percentages above do not show us the percentages proportionate to the numbers of White, Black and Asian in the population so on their own they are misleading. 22% of the population isn’t Black, for example, so black people are hugely over-represented in the stop and search statistics (something the England and Wales Police Force is well aware of as something of a ‘problem’!)
Official Statistics on Ethnicity and Crime: The Main Differences…
Proportionate to the overall numbers in the adult population as a whole…
Black people are approximately SIX times more likely to be stopped and searched and SIX times more likely to be sent to jail;
Asian people are THREE times more likely to be stopped and searched than White people, but have a similar chance of being sent to jail.
The rest of this post provides a little more detail on how the stats vary at different stages of the criminalisation process.
Stop and Search Statistics by Ethnicity
Stop and search has long been an issue of concern by Human Rights campaigners in England and Wales
According to this BBC summary (2013) The Equality and Human Rights Commission (EHRC) said in some areas black people were 29 times more likely to be stopped and searched. The commission said the disproportion between different ethnic groups remained “stubbornly high”.
The highest “disproportionality” ratios were found in the following places:
In Dorset black people were 11.7 times more likely than white people to be stopped
In West Mercia, Asian people were 3.4 times more likely than white people to be stopped
In Warwickshire, people of mixed race were 4.4 times more likely than white people to be stopped and searched.
The report also looked at the use of Section 60 of the Criminal Justice and Public Order Act under which police can stop and search someone for weapons, without suspicion that the individual is involved in wrongdoing, providing that a senior officer has a reasonable belief that violence had or is about to occur.
Under section 60, In the West Midlands, black people were 29 times more likely than white people to be targeted and Asian people were six times more likely than white people to be targeted, which is what the above spoof advert mush be drawing on.
EHRC chief executive Mark Hammond said “the overall disproportionality in the use of the powers against black, Asian and mixed race people remains stubbornly high.”
And the latest figures figures (from the 2018 report above) note that things have got worse:
“The proportion of stop and searches conducted on White suspects decreased from 75% in 2014/15 to 59% in 2018/19 and increased for all minority ethnic groups.
The largest increases were from 13% to 22% for Black suspects and from 8% to 13% for Asian suspects.”
As the table below shows the overall number of people being stopped and searched by the police has declined in the last five years, but the proportions of Black and Asian people stopped and searched compared to whites has increased.
It seems that when the police are asked to use Stop and Search more selectively, they select to stop and search less white people and more ethnic minorities.
Arrest Rates following Stop and Search
The rates are converging, which I guess suggests the police are ‘getting it right’ in equal amounts across ethnic groups:
Arrest Statistics by Ethnicity
The total number of arrests have gone down over the last five years, in line with the declining crime rates. The arrest statistics have remained stable over time, with 77% of arrests being made of white people, 10% black and 7% Asian in 2018.
One stand-out trend for reasons for arrest is that Black people are less likely to be arrested for ‘violence against the person’ and more likely to be arrested for drugs than other ethnic groups – drugs is also the main reason for stop and search, so the two could be correlated.
Penalty Notices and Ethnicity
The main reason white people get given a penalty notice is for being ‘drunk and disorderly’, while for Black and Asian people the main reason is ‘cannabis possession’.
It’s interesting to note here that white people are getting notices for actually being offensive, while for black and asian people it’s merely possessing a drug the system has chosen to make illegal. There’s a significant link to interactionism here!
Prosecution and trial statistics
The Crown Prosecution service (CPS) is responsible for deciding whether a crime or arrest should be prosecuted in court. They base it on whether there is any real chance of the prosecution succeeding and whether it is better for the public that they are prosecuted.
Ethnic minority cases are more likely to be dropped than whites, and blacks and Asians are less likely to be found guilty than whites. Bowling and Phillips (2002) argue that this is because there is never enough evidence to prosecute as it is mainly based on racist stereotyping. In 2006/7 60% of whites were found guilty, against only 52% of blacks, and 44% of Asians.
When cases go ahead members of ethnic minorities are more likely to elect for Crown Court trail rather than magistrates (even through Crown Courts can hand out more severe punishments), potentially because of a mistrust of magistrates.
Convictions
The conviction ratios are very similar for all ethnic groups, suggesting little racial bias at this stage of the criminal justice system:
Black people receive by far the longest sentences, but this seems related to much higher rates of repeat offending, while a much higher proportion of white people being prosecuted are first time offenders….
The 2018 report produced the impressive flow chart below, make of it what you will!
Personally my takeaway is that there seems to be broad equality in the way different ethnicities are treated, and a lot more repeat offending by Black offenders, hence their longer prison sentences.
Prosecutions and Convictions by Type of Offence and Ethnicity
To summarise to the extreme, White people mainly get convicted for theft, Black and Asian people for Drugs.
It’s also worth noting that Black people have significantly lower rates for violent crime than White or Asian people.
Prison Population by Ethnicity
The younger the age group, the fewer white people there are in jail:
And for the under 25s, the number of ethnic minorities in jail has increased proportionate to White people over the last five years:
More than half of children in jail are ethnic minorities
The latest report also has stats on children moving through the criminal justice system.
The figures are even more skewed against ethnic minorities compared to the adult statistics.
It’s more than a little disturbing to note that 51% of children in prison are from ethnic minority backgrounds.
Victim surveys
The British Crime Survey indicated that 44 per cent of victims were able to say something about the offender who was involved in offences against them. Among these, 85 per cent of offenders were said by victims to be ‘white’, 5 per cent ‘black’, 3 per cent ‘Asian’ and 4 per cent ‘mixed’. However, these stats are only for the minority of ‘contact’ offences and very few people have any idea who was involved in the most common offences such as vehicle crime and burglary. Therefore, in the vast majority of offences no reliable information is available from victims about the ethnicity of the criminal.
Self-report studies
Though not ‘official statistics’ because they’re not done by the government routinely, it’s interesting to contrast the above stats to this alternative way of measuring crime. Self-report studies ask people to disclose details of crimes they committed but not necessarily been caught doing or convicted of. Graham and Bowling (1995) Found that blacks (43%) and whites (44%) had similar and almost identical rates of crime, but Asians actually had lower rates (Indians- 30%, Pakistanis-28% and Bangladeshi-13%).
Sharp and Budd (2005) noted that the 2003 offending, crime and justice survey of 12,000 people found that whites and mixed ethnicity were more likely to say they had committed a crime, followed by blacks (28%) and Asians (21%).
Related Posts
You might also like these two further posts on official statistics, ethnicity and crime….
