This is a ‘new thread’ idea… posting up examples of naff research. I figure there are two advantages to this…
It’s useful for students to have good examples of naff research, to show them the meaning of ‘invalid data’ or ‘unrepresentative samples’, or in this case, just plain unreferenced material which may as well be ‘Fake News’.
At least I get some kind of pay back (in the form of the odd daily post) for having wasted my time wading through this drivel.
My first example is from The Independent, the ex-newspaper turned click-bait website.
12% of children under 6 spend more than 24 hours a week on their mobile
80% parents admit to not limiting the amount of time their children spend on games
Eventually it references a company called MusicMagpie (which is an online store) but fails to provide a link to the research, and provides no information at all about the sampling methods used or other details of the survey (i.e. the actual questions, or how it’s administered.). I dug around for a few minutes, but couldn’t find the original survey either.
The above figures just didn’t sound believable to me, and they don’t tie in with OFCOM’s 2017 findings which say that only 5% of 5-7 year olds and 1% of 3-4 year olds have their own mobiles.
As it stands, because of the simple fact that I can’t find details of the survey, these research findings from musicMagpie are totally invalid.
I’m actually quite suspicious that the two companies have colluded to generate some misleading click-bait statistics to drive people to their websites to increase advertising and sales revenue.
If you cannot validate your sources, then do not use the data!
The relationship between social class and religion is not straightforward: the middle classes are, in general, more likely to attend church, but they are also less likely to believe in God and more likely to be atheists and join both world affirming and world rejecting NRMs.
The working classes are less likely to attend church, yet more likely to believe in God than the middle classes. There are also certain denominations and even sects which might appeal specifically to the working classes: such as Methodism, for example.
Church attendance and social class
The ‘middle classes’ have higher rates of church attendance than the ‘working classes’
A 2015 YouGov survey of 7000 adults found that 62% of regular church goers were middle class and 38% working class.
The same 2015 survey found that twice as many married working class men had never attended church compared to middle class men (17% compared to 9%).
Voas and Watt (2014) conducted research on behalf of the Church of England and made three observations not directly about social class, but relevant to it. Firstly, church attendance is higher in rural areas compared to urban areas. Secondly, church attendance is higher in the South of England compared to the North. Thirdly, they noted growth in church attendance in areas which had high performing church primary and secondary schools. All of these indicators suggest higher church attendance in middle class compared to working class areas.
Ashworth and Farthing (2007) found that, for both sexes, those in middle class jobs had above average levels of church attendance. Conversely, those in skilled, semi-skilled and unskilled working class jobs had below average church attendance. Welfare recipients had the lowest levels of church attendance.
Religious belief and social class
A 2016 YouGov Survey revealed that 48% of those in social grades ABC1 described themselves as ‘Atheist’ compared to 42% of those in social grades C2ED.
A 2013 review of >60 research studies on the relationship between IQ and religiosity found that people with higher IQs are more likely to be atheists. (High IQs are correlated with higher levels of education and higher social class).
Lawes (2009) found that ‘lifelong theists’ disproportionately come from unskilled and semi-skilled manual backgrounds, and were less likely to have academic qualifications. Conversely, lifelong atheists disproportionately come from higher professional and managerial backgrounds, and are more likely to have experienced higher education.
NB – It’s worth noting how this contradicts what’s above in terms of church attendance
Social class, religion and deprivation
There is some evidence that those suffering deprivation (the lower social classes) are more likely to turn to religion…..
Churches in deprived inner city areas tend to have higher rates of attendance.
Methodist, Pentacostal and Baptist denominations tend to be more working class.
Catholic Churches are more likely to attract Irish, Polish and African immigrants who have typically experienced higher levels of deprivation.
New Religious Movements and social class
As a general rule, the middle classes are more attracted to both World Affirming NRMs (and the New Age Movement), and World Rejecting NRMs, at least according to Eileen Barker’s classic study of ‘The Moonies’.
Problems with identifying the relationship between religion and social class
Andrew Mckinnon notes that there has been a ‘dearth’ of research on the relationship between religion and social class, meaning there is something of a data gap.
Because of the above, we are often stuck with relying on indicators which might not actually measure social class.
Even if the data suggests that church attendance and belief are higher among the middle classes, this doesn’t necessarily mean the middle classes are actually more religious. They may just be attending church to keep up appearances or to get their children into the local church school (which tend to have high academic performance); or they may feel under more social pressure to state they are religious than the working classes
Chapman et al, as well as the good ole’ t’internet.
The concepts of ‘normal’, and ‘normality’, and the question of what counts as ‘normal behaviour’ has long been of interest to sociologists. Sociologists from different perspectives have very different approaches to answering the basic, but fundamental question, ‘what is normal’?
For the early positivists such as August Comte and Emile Durkheim, uncovering the existence of social norms (or typical patterns of behaviour) was central to their early positivist sociology. However, contemporary sociologists are more likely to question whether or not there is such a thing as ‘normal’ in our postmodern society.
Interest in the word ‘normal’ started to grow in line with early Positivist sociology, peaked during the ‘heyday’ of structuralist sociology in the 1940s-70s and has been in decline since the (contested) shift to postmodern society from the 1980s…
What is Normal?
‘Normal’can be defined as any behavior or condition which is usual, expected, typical, or conforms to a pre-existing standard.
‘Normal behaviour’ may be defined as any behaviour which conforms to social norms, which are the expected or typical patterns of human behaviour in any given society.
It follows that in order to establish what ‘normal’ behaviour is, sociologists firstly need to establish what social norms are present in any given society.
This is actually more difficult than it may sound, because social norms exist at ‘different levels’ of society (at least for those sociologists who actually believe social norms actually exist!)
Some social norms exist at the level of society as a whole, known as ‘societal level norms’, which tend to be very general norms, such as ‘obeying the law most of the time’ or ‘children being expected to not talk to strangers’.
Other norms are context-dependent, and are specific to certain institutions – for example the specific norms associated with sitting a formal examination within an educational setting, or those associated with a funeral. (In some respects the two examples are quite similar!)
Social norms can also vary from place to place, time of day, and different norms may be expected of people depending on their social characteristics: their age, or gender for example.
Given all of the above problems with establishing the existence of social norms, postmodern sociologists have suggested that we need to abandon the concept of normality all together, and just accept the fact that we live in a society of individuals, each of whom is unique.
However, many contemporary sociologists disagree with this postmodern view, given then fact that there do appear to be certain patterns of behaviour which the vast majority of people in society conform to.
The remainder of this post will consider a range of examples of behaviours which might reasonably be regarded as ‘normal’ in the context of contemporary British society….
How might sociologists ‘determine’ what is ‘normal’?
As far as I see it, there are a number of places sociologists can look, for example:
They can simply start out by making observations (possibly backed up by ‘mass observation’ data) of daily life, which will reveal certain General norms of behavior.
They can use statistical data to uncover ‘life events’ or actions that most people will engage in at some point during their ‘life-course’.
They can look at statistical averages.
They can look at attitude surveys and field experiments to find out about typical attitudes towards certain objects of attention and typical behaviours in specific contexts.
They can simply look at the most popular tastes and actions which the majority (or ‘largest minority’ of people engage in.
Below I discuss the first three of these…
Normal behaviour in daily life….?
Simple observations of daily life (backed up with a few basic surveys) reveal there are several social norms that the vast majority of the public conform to. For example:
Wearing clothes most of the time
Despite the fact that according to one survey as many as 1.2 million people in the UK define themselves as naturists (which is about as many as there are members of the Church of England), only 2% of people report that they would ‘get their kit off too’ if they came across a group of naked people playing cricket on a beach while on a coastal ramble’.
You probably don’t think about it very much, but nearly all of us do it – ignoring other people on public transport. So much so that if you type in ‘avoiding people on public transport’ to Google, then the first search return is actually a link to ‘how to do it‘… from ‘sitting by yourself and putting a bag on the seat next to you’ to (most obviously) using your mobile phone or eating something. There’s even advice on how to ‘disengage’ from conversation, just in case some deviant is socially unaware enough to talk to you.
The limitations of establishing ‘normality’ from such ordinary, everyday behaviours…
While most of us engage in such behaviours, is this actually significant? Do these ‘manifestations of similarity’ actually mean anything? Most of us brush our teeth, most of us ignore each other on public transport, most of us wear clothes, but so what?
All of these manifestations of ‘normality’ are quite passive, they don’t really involve much of a ‘buy in’, and there’s still scope for a whole lot of differences of greater significance to occur even with all of us doing all of these ‘basic’ activities in unison…
Life Course Norms…?
It’s probably not as simply as ‘normal life in the U.K.’ as equating to having a 9-5 job, a mortgage, a fuck off big television, walking the dog, paying taxes and having a pension….
But it possible to identify some ‘life-events’ that the vast majority of people in the United Kingdom (or at least England in some of the examples below) will experience at some points in their life. All of the examples below are take from across the A-level sociology syllabus…
Most children in the United Kingdom will go to school….
According to World Bank data, 98.9% of children in the United Kingdom are enrolled in school, so it’s reasonably fair to say that ‘it is normal for children in the UK to go to secondary school’.
NB – it’s probably worth pointing out that ‘secondary school enrollment is much more common in the UK compared to the United States, and especially Uruguay, and various other less economically developed countries.
Of course the fact that nearly 99% of children are enrolled in secondary school in the UK tells us nothing about their experience of education, or how long they actually spend in school, but nonetheless, being enrolled and being subjected to the expectation to attend secondary school in the UK is one of the most universal experiences through the life-course.
Most people in the U.k. will engage in paid work or live with someone who has engaged in paid work at some point in their lives
Only 0.8% of 16-64 year olds live in households where all members have never worked. These figures don’t actually tell us how many people have never worked, but we can say that 99.2% of the adult population has either worked, or is currently living with someone who has, at some point in their lives, worked.
Limitations of establishing ‘normal’ behaviour from these trends
The limitations of deriving an idea of ‘normality’ from life-course data is that you are much less likely to find norms across the generations rather than in one specific age-cohort. More-over, one of main reasons postmodernists argue that it is no longer appropriate to talk about social norms today is that there is a trend away from shared norms in many areas of social life and a movement towards greater diversity.
Social Norms based on statistical averages
A third method of determining what is ‘normal’ is to look at the ‘median’ value of a distribution, that is the value which lies at the midpoint.
In social statistics, it is very like that the median will provide a more representative average figure than the mean because a higher percentage of people will cluster around the median compared to the mean.
Median disposable household income in the UK in 2017 was £27,300
Limitations of establishing ‘normal behaviour’ from medians or means
Is the median the ‘best’ way of establishing ‘what is normal’? Even though it’s the figure around which most people cluster, there can still be enormous differences in those at both ends of the distribution.
As to the mean, as with the household average above…. this might be useful for establishing trends over time, but surely when we look at ‘today’, this is meaningless… there are no households with 2.4 people in!
So… is there such a thing as normal?
While it is possible to identify ‘norms’ using various methods, hopefully the above examples at least demonstrate why postmodernists are so sceptical about the concept of normality today!
I actually did two surveys this week with the students this week, both on Socrative.
For the first survey, I simply asked students via Socrative, who did most of the domestic work when they were a child (mostly mother or mostly father – full range of possible responses are in the results below), with ‘domestic work’ broken down into tasks such as cleaning, laundry, DIY etc…
For the second Survey, I got students to write down possible survey questions on post it notes, then I selected 7 of them to make a brief questionnaire which they then used as a basis for interviewing three couples about who did the housework.
Selected results from the initial student survey on parents’ housework
These results were based on students’ memory!
Selected results from the second survey
based on student interviews with couples
Discussion of the validity of the results…..
These two surveys on the domestic division of labour (and other things) provided a useful way into a discussion of the strengths and limitations of social surveys more generally….we touched on the following, among other things:
memory may limit validity in survey one
lack of possible options limits validity in survey two, also serves as an illustration of the imposition problem.
asking couples should act as a check on validity, because men can’t exaggerate if they are with their partner.
there are a few ethical problems with the ‘him’ and ‘her’ categories, which could be improved upon.
Postcript – on using student surveys to teach A-level sociology
All in all this is a great activity to do with students. It brings the research up to date, it gets them thinking about questionnaire design and, if you time it right, it even gets them out of the class room for half an hour, so you can just put yer feet up and chillax!
If you want to use the same surveys the links, which will allow you to modify as you see fit, are here:
Quiz one – https://b.socrative.com/teacher/#import-quiz/16728393
Quiz two – https://b.socrative.com/teacher/#import-quiz/33508597
‘Evaluate the Strengths of Using Social Surveys in Social Research’ (20)
This is an essay plan for a possible essay for the AQA’s A Level Sociology paper 3: Crime and Deviance with Theory and Methods. This essay plan uses the TPEN structure which covers the theoretical, practical, ethical and ‘nature of topic’ factors relevant to this research method.
Theoretical Factors: Positivists/ Interpretivists – Positivists generally like social surveys because the data from Structured Social Surveys is easy to put into graphs and charts – it is easy to make comparisons, find trends and uncover the ‘laws’ of human action
Theoretical: Representativeness/ Sampling – It is generally easy to obtain large samples
Theoretical: Reliability – Surveys generally have good reliability because….
Theoretical: Validity – Validity should be good for simple topics and it is less likely that the researcher’s opinions will affect the research process as with more qualitative methods
Practical Factors: Social surveys are one of the cheapest methods for collecting data from a wide, geographically dispersed sample of the target population; they are generally one of the quickest ways of collecting data
Ethical Factors: There are few ethical issues with this method compared to more qualitative methods.
Nature of Topic: Social surveys are best used for simple, straightforward topics.
Conclusion: Social Surveys are good for gaining an ‘overview’ of social trends
A Likert* scale is a multiple-indicator or multiple-item measure of a set of attitudes relating to a particular area. The goal of a Likert scale is to measure intensity of feelings about the area in question.
A Likert scale about Likert scales!
In its most common format, the Likert scale consists of a statement (e.g. ‘I love Likert scales’) and then a range of ‘strength of feeling’ options which respondents choose from – in the above example, there are five such options ranging from strongly agree to strongly disagree.
Each respondents reply on each item is scored, typically with a high score (5 in the above example) being given for positive feelings and a low score (1 in the above example) for negative feelings.
Once all respondents have completed the questionnaire, the scores from all responses are aggregated to give an overall score, or ‘strength of feeling’ about the issue being measured.
Some examples of sociological research using Likert scales:
The World Values Survey is my favourite example – they use a simple four point scale to measure happiness. The poll below gives you the exact wording used in the survey…
The results on the web site (and below) show you the percentages who answer in each category, but I believe that the researchers also give scores to each response (4 to 1) and then do the same for similar questions, combine the scores and eventually come up with a happiness rating for a country out of 10. I think the USA scores around 7.2 or something like that, it might be more! Look it up if you’re interested….
Important points to remember about Likert scales
The items must be statements, not questions.
The items must all relate to the same object being measured (e.g. happiness, strength of religious belief)
The items that make up the scale should be interrelated so as to ensure internal reliability is strong.
*The Likert Scale is named after Rensis Likert, who developed the method.
Here’s a general plan of how I tend to revise each research method with my students, for A level sociology, focussing on social surveys revision.
The link above is to the section of the revision hand-out I use (working through it should take about an hour).
I use very similar looking material, and pretty much the same structure (with slight modifications) for all the other research methods.
As far as I’m concerned the important tasks are in bold, the rest is just fluff to get students’ attention/ deal with those who have short attention spans.
Q/A starter 1 – provide an example of the results of a social survey – what does it tell us and what are the limitations….? I quite like to introduce something new here.
PPT starter 2 – Recap the key terms and examples of social surveys – I quickly PPT over the basics of social surveys – just the definition and examples (the ones the students haven’t managed to remember themselves!)
Individual task – Basic true/ false grid (statements to do with social surveys). Sometimes I’ll make this into a Kahoot or a Socrative task
Student task – Strengths and limitations evaluation grids – students can basically use the answers from the true false grids – getting them to evaluate the strengths and limitations pushes them a bit further. For some topics, I’ll make this a cut and paste sentence sort.
Teacher feedback – I give selected examples of how, for example, random sampling might undermine the representativeness (usually a strength) of a survey.
Q/A – Applying social surveys to researching topics in education – students select on of 8-10 key research methods topics we look at and plan and develop their thoughts on how they might use surveys to research that topic
Student task – exam SAQ or essay practice – it is what it is, exam practice, which I may or may not mark! For some topics this will be a marking exercise.
It’s pretty dry, but then again it’s revision – enough fun and games already, let the exam fear commence…
Quantitative research is a strategy which involves the collection of numerical data, a deductive view of the relationship between theory and research, a preference for a natural science approach (and for positivism in particular), and an objectivist conception of social reality.
It is important to note that quantitative research thus means more than the quantification of aspects of social life, it also has a distinctive epistemological and ontological position which distinguishes it from more qualitative research.
An ideal-typical outline of the stages of quantitative research:
The fact that quantitative research starts off with theory signifies the broadly deductive approach to the relationship between theory and research in this tradition. The sociological theory most closely associated with this approach is Functionalism, which is a development of the positivist origins of sociology.
It is common outlines of the main steps of quantitative research to suggest that a hypothesis is deduced from the theory and is tested.
However, a great deal of quantitative research does not entail the specification of a hypothesis, and instead theory acts loosely as a set of concerns in relation to which social researcher collects data. The specification of hypotheses to be tested is particularly likely to be found in experimental research but is often found as well in survey research, which is usually based on cross-sectional design.
3. Research design
The next step entails the selection of a research design which has implications for a variety of issues, such as the external validity of findings and researchers’ ability to impute causality to their findings.
4. Operationalising concepts
Operationalising concepts is a process where the researcher devises measure of the concepts which she wishes to investigate. This typically involves breaking down abstract sociological concepts into more specific measures which can be easily understood by respondents. For example, ‘social class’ can be operationalied into ‘occupation’ and ‘strength of religious believe’ can be measured by using a range of questions about ‘ideas about God’ and ‘attendance at religious services’.
5. selection of a research site or sites
With laboratory experiments, the site will already be established, in field experiments, this will involve the selection of a field-site or sites, such as a school or factory, while with survey research, site-selection may be more varied. Practical and ethical factors will be a limiting factor in choice of research sites.
6. Selection of respondents
Step six involves ‘choosing a sample of participants’ to take part in the study – which can involve any number of sampling techniques, depending on the hypothesis, and practical and ethical factors. If the hypothesis requires comparison between two different groups (men and women for example), then the sample should reflect this.
Step six may well precede step five – if you just wish to research ‘the extent of teacher labelling in schools in London’, then you’re pretty much limited to finding schools in London as your research site(s).
7. Data collection
Step seven, is what most people probably think of as ‘doing research’. In experimental research this is likely to involve pre-testing respondents, manipulating the independent variable for the experimental group and then post-testing respondents. In cross-sectional research using surveys, this will involve interviewing the sample members by structured-interview or using a pre-coded questionnaire. For observational research this will involve watching the setting and behaviour of people and then assigning categories to each element of behaviour.
8. Processing data
This means transforming information which has been collected into ‘data’. With some information this is a straightforward process – for example, variables such as ‘age’, or ‘income’ are already numeric.
Other information might need to be ‘coded’ – or transformed into numbers so that it can be analysed. Codes act as tags that are placed on data about people which allow the information to be processed by a computer.
9. Data analysis
In step nine, analysing data, the researcher uses a number of statistical techniques to look for significant correlations between variables, to see if one variable has a significant effect on another variable.
The simplest type of technique is to organise the relationship between variables into graphs, pie charts and bar charts, which give an immediate ‘intuitive’ visual impression of whether there is a significant relationship, and such tools are also vital for presenting the results of one’s quantitative data analysis to others.
In order for quantitative research to be taken seriously, analysis needs to use a number of accepted statistical techniques, such as the Chi-squared test, to test whether there is a relationship between variables. This is precisely the bit that many sociology students will hate, but has become much more common place in the age of big data!
10. Findings and conclusions
On the basis of the analysis of the data, the researcher must interpret the results of the analysis. It is at this stage that the findings will emerge: if there is a hypothesis, is it supported? What are the implications of the findings for the theoretical ideas that formed the background of the research?
11. Writing up Findings
Finally, in stage 11, the research must be written up. The research will be writing for either an academic audience, or a client, but either way, a write-up must convince the audience that the research process has been robust, that data is as valid, reliable and representative as it needs to be for the research purposes, and that the findings are important in the context of already existing research.
Once the findings have been published, they become part of the stock of knowledge (or ‘theory’ in the loose sense of the word) in their domain. Thus, there is a feedback loop from step eleven back up to step one.
The presence of an element of both deductivism (step two) and inductivism is indicative of the positivist foundations of quantitative research.
A recent report by the Resolution Foundation based on a survey of 2000 people aged 16-75 found that the vast majority of people are pessimistic about the prospects for young people.
In total, 21% of respondents believed Millennials (those born between 1981 and 2000) could expect to enjoy a better standard of living than their parents.
However young people are less pessimistic than older people: around 33% of young people think they will have a better life than their parents, while only 15% of older people said they’d rather be a young person growing up today.
The main points of the report include:
There is widespread pessimism about young people’s lives compared to those of their parents
Graduates, unemployed people and Labour voters are among the most pessimistic
Housing, jobs and retirement living standards are the areas of greatest concern
People believe that housing and jobs market failures are the key causes of this situation, with relatively little blame placed on the actions of generations themselves
People believe that government actions can make a difference, with addressing broad economic challenges and improving public services the top priorities
It’s important to remember that these are just the opinions of people – this data actually tells us nothing about the ACTUAL life chances of Millennials compared to their parents. However, what the last two findings suggest is that there is not such support for small state neoliberal policies – people seem to want government assistance to maintain living standards.
But then again the population go and vote the Tories in – which suggests either that the public is very confused about politics or that these opinion polls aren’t especially valid!
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…