Longitudinal Studies are studies in which data is collected at specific intervals over a long period of time in order to measure changes over time. This post provides one example of a longitudinal study and explores some the strengths and limitations of this research method.
With a longitudinal study you might start with an original sample of respondents in one particular year (say the year 2000) and then go back to them every year, every five years, or every ten years, aiming to collect data from the same people. One of the biggest problems with Longitudinal Studies is the attrition rate, or the subject dropout rate over time.
The Millennium Cohort Study
One recent example of a Longitudinal study is the Millennium Cohort Study, which stretched from 2000 to 2011, with an initial sample of 19 000 children.
The study tracked children until the age of 11 and has provide an insight into how differences in early socialisation affect child development in terms of health and educational outcomes.
The study also allowed researchers to make comparisons in rates of development between children of different sexes and from different economic backgrounds.
Led by the Centre for Longitudinal Studies at the Institute of Education, it was funded by the Economic and Social Research Council and government departments. The results below come from between 2006 and 2007, when the children were aged five.
The survey found that children whose parents read to them every day at the age of three were more likely to flourish in their first year in primary school, getting more than two months ahead not just in language and literacy but also in maths
Children who were read to on a daily basis were 2.4 months ahead of those whose parents never read to them in maths, and 2.8 months ahead in communication, language and literacy.
Girls were consistently outperforming boys at the age of five, when they were nine months ahead in creative development – activities like drama, singing and dancing, and 4.2 months ahead in literacy.
Children from lower-income families with parents who were less highly educated were less advanced in their development at age five. Living in social housing put them 3.2 months behind in maths and 3.5 months behind in literacy.
The strengths of longitudinal studies
They allow researchers to trace developments over time, rather than just taking a one-off ‘snapshot’ of one moment.
By making comparisons over time, they can identify causes. The Millennium Cohort study, for example suggests a clear correlation between poverty and its early impact on low educational achievement
The limitations of longitudinal studies
Sample attrition – people dropping out of the study, and the people who remain in the study may not end up being representative of the starting sample.
People may start to act differently because they know they are part of the study
Because they take a long time, they are costly and time consuming.
Continuity over many years may be a problem – if a lead researcher retires, for example, her replacement might not have the same rapport with respondents.
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?
Positivists prefer to the limit themselves the study of objective ‘social facts’ and use statistical data and the comparative method to find correlations, and multivariate analysis to uncover statistically significant ‘causal’ relationships between variables and thus derive the laws of human behaviour.
This post explores the Positivist approach to social research, defining and explaining all of the above key terms and using some examples from sociology to illustrate them.
The first rule of Positivist methodology is to consider social facts as things which means that the belief systems and customs of the social world should be considered as things in the same way as the objects and events of the natural world.
According to Durkheim, some of the key features of social facts are:
they exist over and above individual consciousness
they are not chosen by individuals and cannot be changed by will
each person is limited (constrained) by social facts
According to Durkheim what effects do social facts make people act in certain ways, in the same way as door limits the means whereby you can enter a room or gravity limits how far you can jump.
Positivists believed that we should only study what can be observed and measured(objective facts), not subjective thoughts and feelings. The role of human consciousness is irrelevant to explaining human behaviour according to Positivists because humans have little or no choice over how they behave.
Positivists believed it was possible to classify the social world in an objective way. Using these classifications it was then possible to count sets of observable facts and so produce statistics.
The point of identifying social facts was to look for correlations – a correlation is a tendency for two or more things to be found together, and it may refer to the strength of the relationship between them.
If there is a strong correlation between two ore more types of social phenomena then a positivist sociologist might suspect that one of these phenomena is causing the other to take place. However, this is not necessarily the case and it is important to analyse the data before any conclusion is reach.
Spurious correlations pose a problem for Positivist research. A spurious correlation is when two or more phenomena are found together but have no direct connection to each other: one does not therefor cause the other. For example although more working class people commit crime, this may be because more men are found in the working classes – so the significant relationship might be between gender and crime, not between class and crime.
Positivists engage in multivariate analysis to overcome the problem of spurious correlations.
Multivariate Analysis involves isolating the effect of a particular independent variable upon a particular dependent variable. This can be done by holding one independent variable constant and changing the other. In the example above this might mean comparing the crime rates of men and women in the working class.
Positivists believe multivariate analysis can establish causal connections between two or more variables and once analysis is checked establish the laws of human behaviour.
Positivism – Establishing the Laws of Human Behaviour
A scientific law is a statement about the relationship between two or more phenomena which is true in all circumstances.
According to Positivists, the laws of human behaviour can be discovered by the collection of objective facts about the world in statistical form and uncovering correlations between them, checked for their significance by multivariate analysis.
Positivism and The Comparative Method
The comparative method involves the use of comparisons between different societies, or different points in time
The purpose of using the comparative method is to establish correlations, and ultimately causal connections, seek laws and test hypotheses.
The comparative method overcomes the following disadvantages of experiments:
Moral problems are not as acute
The research is less likely to affect the behaviour or those being studied because we are looking at natural settings
The comparative method is superior to the experimental method because allows the sociologist to explore large scale social changes and changes over time
However, a fundamental problem with the comparative method is that the data you want may not be available, and you are limited to that data which already exists or which can be collected on a large scale via social surveys.
Social Surveys are one of the most common methods for routinely collecting data in sociology and the social sciences more generally. There are lots of examples of where we use social surveys throughout the families and households module in the A level sociology syllabus – so what do they tell us about family life in modern Britain, and what are their strengths and limitations….?
This information should be useful for both families and households and for exploring the strengths and limitations of social surveys for research methods…
Attitudes to marriage surveys
Headline Fact – in 2016, only 37% of the UK population believe people should be married before they have children.
For the first time since NatCen started asking whether people who want to have children ought to be married, the proportion who disagree (35%) is almost the same as those who agree (37%).
Back in 1989, seven people in ten (70%) felt that people should be married if they want to have children, compared with less two in ten (17%) who disagreed.
It’s actually worth noting how quickly attitudes have changed since the previous survey in 2012, as demonstrated in the info graphic below – in 2016 it’s now down to 37%
What are the strengths of this survey (focussing on this one question)?
I’m tempted to say the validity is probably quite good, as this isn’t a particularly sensitive topic, and the focus of the question is the ‘generalised other’, so there should be no social desirability.
It’s very useful for making comparisons over time – given that the same question has been asked in pretty much the same way for quite a few years now…
Representativeness seems to be OK – NatCen sampled a range of ages, and people with different political views, so we can compare all that too – no surprises here btw – the old and the conservatives are more likely to be in favour of marriage.
What are the limitations of this survey?
As with all surveys, there’s no indication of why belief in marriage is in decline, no depth or insight.
The question above is so generalised, it might give us a false impression of how liberal people are. I wonder how much the results would change if you made the questions more personal – would you rather your own son/ daughter should be married before they had children? Or just different – ‘all other things being equal, it’s better for children to be brought up by married parents, rather than by non-married-parents’ – and then likehert scale it. Of course that question itself is maybe just a little leading….
Headline ‘fact’ – women still do 60% more housework than men (based on ONS data from 2014-15)
Women put in more than double the proportion of unpaid work when it comes to cooking, childcare and housework and on average men do 16 hours a week of such unpaid work compared to the 26 hours of unpaid work done by women a week.
The only area where men put in more unpaid work hours than women is in the provision of transport – this includes driving themselves and others around, as well as commuting to work.
This data is derived from the The UK Time Diary Study (2014-15) – which used a combination of time-use surveys and interviews to collect data from around 9000 people in 4000 households.
It’s worth noting that even though the respondents were merely filling in a few pages worth of diary, this document contains over 200 pages of technical details, mainly advice on how researchers are supposed to code responses.
What are the strengths of this survey?
The usual ease of comparison. You can clearly see the differences in hours between men and women – NB the survey also shows differences by age and social class, but I haven’t included that here (to keep things brief).
It’s a relatively simply topic, so there’s unlikely to be any validity errors due to interpretation on the part of people completing the surveys: it’s obvious what ‘washing clothes’ means for example.
This seems to suggest the continued relevance of Feminism to helping us understand and combat gender inequality in the private sphere.
What are the limitations of this data?
click on the above link and you’ll find that there is only a 50% response rate…. which makes the representativeness of this data questionable. If we take into account social desirability, then surely those couples with more equal housework patterns will more likely to return then, and also the busier the couple, the less likely they are to do the surveys. NO, really not convinced about the representativeness here!
this research tells us nothing about why these inequalities exist – to what extent is this situation freely chosen, and to what extent is it down to an ‘oppressive socialisation into traditional gender norms’ or just straightforward coercion?
given all of the coding involved, I’m not even convinced that this is really that practically advantageous…. overall this research seems to have taken quite a long time, which is a problem given the first criticism above!
Surveys on Children’s Media Usage
Headline Fact: 5 – 15 year olds spend an average of 38 hours a week either watching TV, online or gaming.
It’s also worth noting that for the first time, in 2016, children aged 5-15 say they spend more time online than they do watching television on a TV set.
It makes comparisons over time easy, as the same questions are asked over a number of different years.
Other than that, I think there are more problems!
Limitations of this Survey
There are no details of how the sample was achieved in the methodology – so I can’t comment on the representativeness.
These are just estimations from the children and parents – this data may have been misrepresented. Children especially might exaggerate their media usage when alone, but downplay it if a parent is present.
I’m especially suspicious of the data for the 3-7 year olds, given that this comes from the parent, not the child… there’s a strong likelihood of social desirability leading to under-reporting… good parents don’t let their kids spend too much time online after all!
Further examples of surveys on the family
If you like this sort of thing, you might also want to explore these surveys…
The two main sources of official statistics on Crime in the UK (or rather England and Wales!) are:
Police Recorded Crime – which is all crimes recorded by the 43 police forces in England and Wales (as well as the British Transport Police)
The Crime Survey for England and Wales which is a face to face victim survey in which people are asked about their experiences of crime in the previous 12 months.
NB – There are other sources of official statistics on crime, which I’ll come back to later, but these are the two main ones.
Below are three very good web sites which you can use to explore crime stats from the above two sources. The point of this post is really just to direct students to good sources which they can use to explore these statistics (strengths and limitations of crime statistics posts will be forthcoming shortly!)
Published by the Office for National Statistics, Crime in England and Wales provides the most comprehensive coverage of national crime trends. I’d actually recommend starting with the methodology section of this document, which states
This is a good starting point for exploring crime statistics. You can click on an interactive map which will show you how much crime there is in your area. NB this map shows you only police recorded crime, and there are many, many crimes which are not recorded, for various reasons.
This site describes itself as ‘the leading crime and property data’ website – scroll down for a nice colour coded analysis of crime trends for a number of different crime categories. Reported month by month (2 month data lag). I think the table below is CSEW data
What I particularly like about this web site is that it provides data tables by police force – Here’s a link to data for the Surrey Police (Local link, I teach in Surrey, where my measly teacher salary makes me feel poor because of the sickening and unjustified wealth in the local area.) The data below is Police Recorded Crime data.
When looking at statistics on crime, make sure you know whether the stats come from Police Recorded Crime or the Crime Survey of England and Wales (a victim survey) – the two figures will be different, and the difference between them will be different depending on the type of crime – for example the stats for vehicle theft are quite similar (because of insurance claims requiring a police report) but domestic violence figures are very different from these two sources because most offences do not get reported to the police, but many more (but not all) get reported to the CSEW researchers.
Firstly – GENDER – Girls outperform boys by about 10 percentage points. 61.7% of girls achieved at least 5 A*- C GCSEs (or equivalent) grades including English and mathematics compared to 51.6% of boys; this is a gap of 10.1 percentage points.
Secondly – ETHNICITY – Chinese pupils are the highest achieving group. 74.4% of Chinese pupils achieved at least 5 A*- C GCSEs (or equivalent) grades including English and mathematics. This is 17.9 percentage points above the national average (56.6%). Almost half of Chinese Pupils are achieving the English Baccalaureate (49.5%); 25.4 percentage points above the national average (24.2%).
Children from a black background are the lowest achieving group. 53.1% of pupils from a black background achieved at least 5 A*- C GCSEs (or equivalent) grades including English and mathematics; this is 3.4 percentage points below the national average (56.6%). However, things are also improving: 75.5% of black pupils are making the expected progress in English and 68.4% in mathematics; both above the national average of 71.6% for English and 65.5% for mathematics.
Thirdly – SOCIAL CLASS – Here, instead of social class we need to use Pupils eligible for Free School Meals (FSM) (meaning they come from a household with an income of less than £16000) – FSM pupils are nearly 30% points behind non FSM pupils. 33.5% of pupils eligible for FSM achieved at least 5 A*- C GCSEs (or equivalent) grades including English and mathematics compared to 60.5% of all other pupils. This is a gap of 27.0 percentage points. 36.5% of disadvantaged pupils achieved at least 5 A*- C GCSEs (or equivalent) grades including English and mathematics compared to 64.0% of all other pupils, a gap of 27.4 percentage points.
The government stats also include achievement data by ‘disadvantage’:
Disadvantaged pupils are defined as pupils known to be eligible for free school meals in the previous six years as indicated in any termly or annual school census, pupil referral unit (PRU) or alternative provision (AP) census or are children looked after by the local authority for more than 6 months.
Other statistical data included in the pupil characteristics report
The Department for Education also collects data and reports on educational achievement by English as a second language, and special educational needs. Look it up if you’re interested, I’m limiting myself here to educational attainment by ‘social class’, gender and ethnicity.
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 – We need to be a little cautious about the validity of some of these results, especially when making comparisons over time. This is because until last year schools could count any one of 3000 ‘soft’ subjects as equivalent to a GCSE, which could make the results look better than they actually are. Also, with coursework subjects there is a potential problem with ‘grade inflation’ within schools, and not to mention the fact that with coursework we are least partially measuring the degree to which parents have helped their children, rather than their children’s actual personal achievement.
TWO – comparisons over time might be difficult because of recent changes to the qualifications that are allowed to be counted towards attainment measurements. In 2014 the following changes were made:
1. The number of qualifications which counted towards ‘GCSE or equivalent’ results were drastically reduced – around 3,000 unique qualifications from the performance measures between 2012/13 and 2013/14.
2. The associated point scores for non-GCSEs was adjusted so that no qualification will count as larger than one GCSE in size. For example, where a BTEC may have previously counted as four GCSEs it will now be reduced to the equivalence of a single GCSE in its contribution to performance measures.
3. The number of non-GCSE qualifications that count in performance measures was restricted to two per pupil.
All of this has had the effect of making the results look worse than they actually are:
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…
This post provides a brief overview of Positivist Research Methods, which consist of a scientific approach to social research using quantitative data to ensure objectivity and reliability. (In contrast to the Interpretivist approach to research which favors qualitative data.)
The historical context of Positivism is that it emerged out of The Enlightenment and The Industrial Revolution….
The Enlightenment refers to a period of European history spanning from 1650 to 1800. During this time, the authority of the church was challenged as people started to believe that knowledge should be derived from science rather than from God. The Enlightenment witnessed the birth of modern science which lead to massive social changes. The following three core beliefs (there were others too!) emerged out of The Enlightenment:
Underlying laws explained how the universe and society work (wasn’t just God’s will)
Scientific study could reveal these laws.
All men could understand these laws (unlike religious belief – God’s will is unknowable)
Laws could be applied to society to improve it (the belief in progress and the pursuit of happiness).
The Enlightenment, Industrialisation’, ‘Progress’ and the Birth of Sociology
The 18th and 19th centuries saw a number of new scientific discoveries in the fields of physics, chemistry and biology. Most notably for students of Sociology, scientific discoveries lead to new technologies which in turn lead to industrialisation, or the growth of factory based production and the building of such things as railways.
This in turn lead to much social transformation – such as Urbanisation and the growth of what Marxists called the Proletariat. Many commentators from the early 19th century onwards were disturbed by the contradiction between the huge advances, or progress being made in science and industry and the apparent worsening of the lives of the majority. As hundreds of thousands of people flooded into expanding industrial city centres such as Manchester and elsewhere in Britain and Europe, these new urban centres were plagued with new social problems – most notably poverty, unemployment, and social unrest.
It was in this context that August Comte founded Sociology – Comte basically believed that if we can use scientific findings to bring about improvements in production through industrialisation then we can study the social world and figure out how to construct a better society that can combat social problems such as poverty, lack of education and crime.
Auguste Comte (1798-1857): The Founder of Scientific Sociology (aka Positivism)
Comte introduced the word “Sociology” in 1839. The term “Sociology” is derived from the Latin word Socius, meaning companion or associate, and the Greek word logos, meaning study or science. Thus, meaning of sociology is the science of society.
Comte concentrated his efforts to determine the nature of human society and the laws and principles underlying its growth and development. He also laboured to establish the methods to be employed in studying social phenomena.
Comte argued that social phenomena can be like physical phenomena copying the methods of natural sciences. He thought that it was time for inquiries into social problems and social phenomena to enter into this last stage. So, he recommended that the study of society be called the science of society, i. e. ‘sociology’.
The General Ideas of Positivism – or The Scientific Method Applied to the Study of Sociology
1. Positivists believe that sociology can and should use the same methods and approaches to study the social world that “natural” sciences such as biology and physics use to investigate the physical world.
2. By adopting “scientific” techniques sociologists should be able, eventually, to uncover the laws that govern societies and social behaviour just as scientists have discovered the laws that govern the physical world.
3. Positivists believe that good, scientific research should reveal objective truths about the causes of social action – science tells us that water boils at 100 degrees and this is true irrespective of what the researcher thinks – good social research should tell us similar things about social action
4. Because positivists want to uncover the general laws that shape human behaviour, they are interested in looking at society as a whole. They are interested in explaining patterns of human behaviour or general social trends. In other words, they are interested in getting to the ‘bigger picture’.
5. To do this, positivists use quantitative methods such as official statistics, structured questionnaires and social surveys. Statistical, numerical data is crucial to Positivist research. Positivists need to collect statistical information in order to make comparisons. And in order to uncover general social trends. It is much more difficult to make comparisons and uncover social trends with qualitative data.
6. These methods also allow the researcher to remain relatively detached from the research process – this way, the values of the researcher should not interfere with the results of the research and knowledge should be objective
Emile Durkheim (1858-1917) – Positivism and Quantitative Sociology
The modern academic discipline of sociology began with the work of Émile Durkheim (1858–1917). While Durkheim rejected much of the details of Comte’s philosophy “positivism”, he retained and refined its method. Durkheim believed that sociology should be able to predict accurately the effect of particular changes in social organisation such as an increase in unemployment or a change in the education system.
Durkheim believed the primary means of researching society should be the Comparative Method which involves comparing groups and looking for correlations or relationships between 2 or more variables. This method essentially seeks to establish the cause and effect relationships in society by comparing variables.
Durkheim’s Study of Suicide (1897)
Durkheim chose to study suicide because he thought that if he could prove that suicide, a very personal act, could be explained through social factors, then surely any action could be examined in such a way. Durkheim’s method consisted of comparing the incidence of various social factors with number of cases of suicide. Durkheim did this work so well, that seventy years later his study was still being cited in textbooks as an excellent example of research methodology
The starting-point for Durkheim was a close analysis of the available official statistics, which showed that rates of suicide varied:
• From one country to another – countries experiencing rapid social change had higher suicide rates.
• Between different social groups – The divorced had higher suicide rates than the married.
• Between different religious groups – Protestants had higher suicide rates than Catholics
Durkheim noted that these rates were relatively stable over time for each group. The rates may have gone up or down, but the rates remained stable relative to each other. Durkheim theorised that if suicide was an entirely individual matter, untouched by the influence of social factors, it would be an astonishing coincidence if these statistical patterns remained so constant over a long period of time. Entirely individual decisions should lead to a random pattern.
Durkheim used his data to derive his now famous theory – that suicide rates increase when there is too little or too much social regulation or integration. Social Regulation is the extent to which there are clear norms and values in a society, while social integration is the extent to which people belong to society.
Even though this study is now almost 120 years old it remains the case that suicide rates still vary according to the levels of social integration and regulation.
Positivism and Social Facts Durkheim argued that social trends are ‘social facts’ – they are real phenomena which exist independently of the individuals who make them up. He claimed that by if sociology limited itself to the study of social facts it could be more objective. He argued that these facts constrain individuals and help us to make predictions about the way societies change and evolve.
Some Criticisms of the Positivist Approach to Social Research
Treats individuals as if they passive and unthinking – Human beings are less predictable than Positivists suggest
Interpretivists argue that people’s subjective realities are complex and this demands in-depth qualitative methods.
The statistics Positivists use to find their ‘laws of society’ might themselves be invalid, because of bias in the way they are collected.
By remaining detached we actually get a very shallow understanding of human behaviour.
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Positivists believe society shapes the individual and use quantitative methods, intepretivists believe individuals shape society and use qualitative methods.
Positivism and Interpretivism are the two basic approaches to research methods in Sociology. Positivist prefer scientific quantitative methods, while Interpretivists prefer humanistic qualitative methods. This post provides a very brief overview of the two.
Positivistsprefer quantitative methods such as social surveys, structured questionnaires and official statistics because these have good reliability and representativeness.
Positivists see society as shaping the individual and believe that ‘social facts’ shape individual action.
The positivist tradition stresses the importance of doing quantitative research such as large scale surveys in order to get an overview of society as a whole and to uncover social trends, such as the relationship between educational achievement and social class. This type of sociology is more interested in trends and patterns rather than individuals.
Positivists also believe that sociology can and should use the same methods and approaches to study the social world that “natural” sciences such as biology and physics use to investigate the physical world. By adopting “scientific” techniques sociologists should be able, eventually, to uncover the laws that govern societies just as scientists have discovered the laws that govern the physical world.
In positivist research, sociologists tend to look for relationships, or ‘correlations’ between two or more variables. This is known as the comparative method.
An Interpretivist approach to social research would be much more qualitative, using methods such as unstructured interviews or participant observation
Interpretivists, or anti-positivists argue that individuals are not just puppets who react to external social forces as Positivists believe.
According to Interpretivists individuals are intricate and complex and different people experience and understand the same ‘objective reality’ in very different ways and have their own, often very different, reasons for acting in the world, thus scientific methods are not appropriate.
Intereptivists actually criticise ‘scientific sociology’ (Positivism) because many of the statistics it relies on are themselves socially constructed.
Interpretivists argue that in order to understand human action we need to achieve ‘Verstehen‘, or empathetic understanding – we need to see the world through the eyes of the actors doing the acting.
Positivism and Interpretivism Summary Grid
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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
Five theory and methods essays
‘How to write methods in context essays’.
Links to more detailed posts on Positivism and Social Action Theory are embedded in the text above. Other posts you might like include: