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!)
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.
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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%
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.
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
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!
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).
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.
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.
The Government spent 83.4 billion on education in 2015-16, or 4.4% of GDP, a decrease from 5.3% in 2011-12
The above chart, from the Institute for Fiscal Studies (link below), clearly shows you the extent of the Tory funding cuts to education since 2010.
There are 32, 142 schools in the U.K.
For an overview of the different types of school please see this post: different types of school in England and Wales (forthcoming post).
The majority of schools in England and Wales are state funded, and there are 5 times as many primary schools as secondary schools.
There are 21000 primary schools
There are 4100 secondary schools
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; while 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.
There are 5.5 million pupils in primary schools in the U.K. and 3.8 million secondary school pupils (figures for state maintained schools)
The number of pupils in secondary schools decreased by 2.4% between 2011 and 2015
The number of pupils in primary schools increased by 8.3% between 2011 to 2015.
This probably reflects demographic trends in the United Kingdom (although by all means do verify this); if this is the case, it means we might reasonably expect to see an increase in secondary school numbers over the next few years.
There are 122 000 pupils in special schools, and 15 000 in pupil referral units
The numbers of pupils in both special schools and pupil referral units are increasing: between 2012 and 2016:
the number of students in special schools increased by 17,000, or 21%,
the number of students in pupil referral units increased by 2600, or 16.2%
A total of 14.4% of pupils have Special Education Needs
but only 2.8% of them have an SEN statement with a further 11.6% receiving SEN support, mostly within mainstream maintained schools.
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 previous chart, then it suggests that special educational needs students are becoming increasingly segregated into special schools and/ or pupil referral units, rather than being dealt with in mainstream secondary schools.
Another thing to note about the chart above is that it’s highly unlikely that the number of statemented SEN children are increasing while there’s been a fairly sharp decrease in non-statemented SEN kids, this has got ‘change in labelling’ written all over it as an explanation (no pun intended).
In 2015 the proportion of 16-18 year olds in education and work-based learning was 81.6%
This is he highest level since consistent records began in 1994
At age 16 the participation rate was 94.1%
At age 17 it was 87.8%.
At age 18 it was 63.8% (but of course, most of the ‘missing’ 36.2% will be in paid-work!)
NEETS – The number of 16-24 year-olds Not in Education, Employment or Training (NEET) across the UK has fallen to around 15%
There were 1.3 million students studying towards their first degree in 2015/16, an 8% increase since 2010/11
In 2015 there were 456 900 full time equivalent teachers in England and Wales
The overall number of teachers has increased over the last five years, but this increase is mainly in primary teachers. The number of secondary school teachers has actually decreased.
13% of qualified teachers drop out after just one year of teaching, and 30% drop out after five years of teaching
The current number of qualified teachers aged under 60 (and not in receipt of a pension from the Teachers’ Pension Scheme) that have worked in state funded schools in England and were not employed as at December 2013 is 227 100
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).
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. Published annually every June.
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.
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!
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?
Unlike with social class, the home office does record explicit data based on the ethnic backgrounds of those stopped and searched, arrested and imprisoned. There are a lot of different official statistics on ethnicity and crime, reflecting the different stages of the criminalisation process:
Stop and search stats
Penalty order notices and cautions
Those who are subject to court proceedings
Those convicted in court
Those sent to jail from court
Prison statistics (those in jail) (not shown in the table below)
Of course in order to be properly comparative, we need to look at the numbers from each ethnic group at each stage in proportion to the overall numbers of each ethnic group in the population as a whole, as the table above does.
Official Statistics on Ethnicity and Crime – The Most Obvious Differences between Ethnic Groups…
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
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.”
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.
Sentencing and prison statistics
Jail sentences are more likely to be given to Blacks (68%) compared to Whites (55%) or Asians (59%), whereas Whites and Asians were more likely to receive community services. But this could be due to the seriousness of some ones offence of previous convictions.
Hood (1992) found that even when the seriousness of an offence and previous convictions were taken into account Black men were 5x more likely to be jailed and given a sentence which is 3 months (Asians 9 months) longer than whites.
The current actual prison statistics broken down by ethnicity look something like this:
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.
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%).
This post summaries some of the changing trends (and continuities) in family and household structure in the UK, using data from the Office for National Statistics which collects a range of data annually on families and households in the UK
In 2015 there were 18.7 million families in the UK
The most common family type in 2015 was the married or civil partner couple family with or without dependent children at 12.5 million
The cohabiting couple family continues to be the fastest growing family type in the UK in 2015, reaching 3.2 million cohabiting couple families
In 2015 around 40% of young adults aged 15 to 34 in the UK were living with their parents
There were 27.0 million households in the UK in 2015, 35% of all households were two person households
In 2015 there were 7.7 million people in UK households who were living alone
Changes to families and households 2005 – 2015
Changes to Family Households
There has been a significant increase in the number of cohabiting couples, both with and without children, and a slight increase in lone parent households. The number of married couple households both with and without children has remained stable, which means that the overall picture is one of a slight trend towards increasing family diversity and away from marriage.
2. Marriage and Cohabitation Trends
The chart below clearly shows the slight decline in married households compared to cohabiting and single parent households, but there are still almost three times as many married households compared to cohabiting households!
3. Family Size
Family size appears to have remained pretty stable over the past 15 years
4. Households Size in the UK
We have quite a small average households size in the UK – with two and one person households making up around two thirds of all households.
5.Multi Family Households
Given that they’re starting from a small base, there has been a significant ten year increase in multi family households – households with two or more families in, an increase of one third in twenty years.
6. The increase in People Living Alone
There has been a slow and steady increase in the overall numbers of people living alone, but this varies a lot by age – generally the number of older people living alone has increased, the number of younger people living alone has decreased.
How useful are official statistics for understanding differences in educational achievement by social class, gender and ethnicity?
How do GCSE results vary by social class, gender and ethnicity?
The data below is taken from either the Department for Education’s document – Key Stage 4 performance 2019 (Revised), or Gov.uk ‘ethnicity facts and figures‘. The later shows data from 2017/18 (at time of writing this), but it is much more accessible than the ‘Key Stage 4 document’.
Firstly – GENDER – Girls outperformed boys in all headline measures in 2019.
For example 46.6% of girls achieved both English and Maths at grade 5 or above, compared to only 40.0% of boys, and girls are much more likley to be entered for the Ebacc than boys (45.9% compared to 34.3%
Secondly – ETHNICITY – Chinese pupils are the highest achieving group. 75.3% of Chinese pupils achieved a ‘strong pass’ (grade 5 or above) in English and Maths, with Indian pupils being the second highest achieving group, at 62%
Black Caribbean pupils have the lowest achievement of any ‘large’ ethnic minority group, with only 26.9% achieving a grade 5 or above in English and Maths
Gypsy/ Roma and Irish Traveller pupils have the lowest levels of achievement with only 9.95 and 5.3% respectively achieving a strong pass in English and Maths.
Thirdly – SOCIAL CLASS – Here, instead of social class we need to use the Department for Education’s ‘disadvantaged pupils’ category, which is the closest we’ve got as a proxy for social class, but isn’t quite the same!
The DFE says that “Pupils are defined as disadvantaged if they are known to have been eligible for free school meals in the past six years , if they are recorded as having been looked after for at least one day or if they are recorded as having been adopted from care”.
In 2019, only 24.7% of disadvantages pupils achieved English and Maths GCSE at grade 5 or above, compared to almost 50% of all other pupils, meaning disadvantaged pupils are only half as likely to get both of these two crucial GCSEs.
Some Strengths of Official Statistics on Educational Achievement by Pupil Characteristic
ONE – Good Validity (as far as it goes) – These data aren’t collected by the schools themselves – so they’re not a complete work of fiction, they are based on external examinations or coursework which is independently verified, so we should be getting a reasonably true representation of actual achievement levels. HOWEVER, we need to be cautious about this.
TWO – Excellent representativeness – We are getting information on practically every pupil in the country, even the ones who fail!
THREE – They allow for easy comparisons by social class, gender and ethnicity. These data allow us to see some pretty interesting trends – As in the table below – the difference between poor Chinese girls and poor white boys stands out a mile… (so you learn straight away that it’s not just poverty that’s responsible for educational underachievement)
FOUR – These are freely available to anyone with an internet connection
FIVE – They allow the government to track educational achievement and develop social policies to target the groups who are the most likely to underachieve – These data show us (once you look at it all together) for example, that the biggest problem of underachievement is with white, FSM boys.
Some Disadvantages of the Department for Education’s Stats on Educational Achievement
ONE – If you look again at the DFE’s Key Stage four statistics, you’ll probably notice that it’s quite bewildering – there are so many different measurements that it obscures the headline data of ‘who achieved those two crucial GCSEs’.
When it comes to the ‘Attainment 8’ or ‘Progress 8’ scores, it is especially unclear what this means to anyone other than a professional teacher – all you get is a number, which means nothing to non professionals.
TWO – changes to the way results are reported mean it’s difficult to make comparisons over time. If you go back to 2015 then the standard was to achieve 5 good GCSEs in any subject, now the government is just focusing on English and Maths, Ebacc entry and attainment 8.
THREE – These stats don’t actually tell us about the relationship between social class background and educational attainment. Rather than recording data using a sociological conception of social class, the government uses the limited definition of Free School Meal eligibility – which is just an indicator of material deprivation rather than social class in its fuller sense. Marxist sociologists would argue that this is ideological – the government simply isn’t interested in measuring the effects of social class on achievement – and if you don’t measure it the problem kind of disappears.
FOUR – and this is almost certainly the biggest limitation – these stats don’t actually tell us anything about ‘WHY THESE VARIATIONS EXIST’ – Of course they allow us to formulate hypotheses – but (at least if we’re being objective’) we don’t get to see why FSM children are twice as likely to do badly in school… we need to do further research to figure this out.
No doubt there are further strengths and limitations, but this is something for you to be going on with at least…
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