Useful links to quantitative and qualitative research studies, statistics, researchers, and news paper articles relevant to gender and education. These links should be of interest to students studying A-level and degree level sociology, as well as anyone with a general interest in the relationship between gender, gender identity, differential educational achievement and differences in subject choice.
Just a few links to kick-start things for now, to be updated gradually over time…
A link to Professor Becky Francis’ research, which focuses mainly on gender differences in educational achievement – at time of writing (November 2017) her main focus seems to be on girls lack of access to science and banding and streaming (the later not necessarily gender focused)
Specific resources for exploring gender and differential educational achievement
Education as a strategy for international development – despite the fact that girls are outperforming boys in the United Kingdom and most other developed countries, globally girls are underachieving compared to boys in most countries. This link takes you to a general post on education and social development, many of the links explore gender inequality in education.
Specific resources for exploring gender and subject choice
Dolls are for Girls, Lego is for Boys – A Guardian article which summarizes a study by Becky Francis’s on Gender, Toys and Learning, Francis asked the parents of more than 60 three- to five-year-olds what they perceived to be their child’s favourite toy and found that while parental choices for boys were characterised by toys that involved action, construction and machinery, there was a tendency to steer girls towards dolls and perceived “feminine” interests, such as hairdressing.
Girls are Logging Off – A BBC article which briefly alerts our attention to the small number of girls opting to do computer science.
This my very simply ‘research’ project task for summer timetable 2018. I’m experimenting with going back to a very open ended project!
The AQA Sociology specification states that you should be able to cite examples of your own research, hence this summer term research project (which is also useful for introducing theories of crime and deviance.
Select one ‘type’ of crime from the list below and produce a 1500 -2000 word report applying perspectives and incorporating some independent research exploring how and why this crime occurs.
Examples of crimes you might look at
Knife crime/ gun crime
Any other type of crime or deviance of your choice
Section 1: Introduction
Outline what crime you’ve chose to focus on, define it, and provide a few basic statistics to outline the extent of it.
Section 2: Theoretical context
Summarise how conflict, consensus and action theories would explain this crime. Use the following links or your main text books as necessary:
Bryman (2016) identifies four criticisms of quantitative research:
Quantitative researchers fail to distinguish people and social institutions from the world of nature
Schutz (1962) is the main critique here.
Schutz and other phenomenologists accuse quantitative social researchers of treating the social world as if it were no different from the natural world. In so doing, quantitative researchers tend to ignore the fact that people interpret the world around them, whereas this capacity for self-reflection cannot be found among the objects of the natural sciences.
The measurement process possesses an artificial and spurious sense of precision and accuracy
Cicourel (1964) is the main critique here.
He argues that the connection between the measures developed by social scientists and the concepts they are supposed to be revealing is assumed rather than real – basically measures and concepts are both effectively ‘made up’ by the researchers, rather than being ‘out there’ in reality.
A further problem is that quantitative researchers assume that everyone who answers a survey interprets the questions in the same way – in reality, this simply may not be the case.
The reliance on instruments and procedures hinders the connection between research and everyday life
This issue relates to the question of ecological validity.
Many methods of quantitative research rely heavily on administering research instruments to participants (such as structured interviews or self-completion questionnaires), or controlling situations to determine effects.
However, these instruments simply do not ‘tap into’ people’s real life experiences – for example, many of the well known lab experiments on the A-level sociology syllabus clearly do not reflect real life, while surveys which ask people about their attitudes towards immigration, or the environment, do not necessarily tell us about how people act towards migrants or the environment on a day to day basis.
The analysis of relationships between variables creates a static view of social life that is independent of people’s lives.
The main critique here is Blumer (1956).
Blumer (1956) argued that studies that seek to bring out the relationships between variables omit ‘the process of interpretation or definition that goes on in human groups’.
This is a combination of criticisms 1 and 3 above, but adds on an additional problem – that in isolating out variables, quantitative research creates an artificial, fixed and frozen social (un)reality – whereas social reality is (really) alive and constantly being created through processes of interaction by its various members.
In other words, the criticism here is that quantitative research is seen as carrying an objective ontology that reifies the social world.
The above criticisms have lead intepretivists to prefer more qualitative research methods. However, these too have their limitations!
Quantitative researchers generally have four main preoccupations: they want their research to be measurable, to focus on causation, to be generalisable, and to be replicable.
These preoccupations reflect epistemological grounded beliefs about what constitutes acceptable knowledge, and can be contrasted with the preoccupations of researchers who prefer a qualitative approach.
It may sound like it’s stating the obvious – but quantitative researchers are primarily interested in collecting numerical data, which means they are essentially concerned with counting social phenomena, which will often require concepts to be operationalised.
In most quantitative research there is a strong concern with explanation: qualitative researchers are more concerned with explaining why things are as they are, rather than merely describing them (which tends to be the focus of more qualitative research).
It follows that it is crucial for quantitative researchers to effectively isolate variables in order to establish causal relationships.
Quantitative researchers tend to want their findings to be representative of wider populations, rather than the just the sample involved in the study, thus there is a concern with making sure appropriate sampling techniques will be used.
If a study is repeatable then it is possible to check that the original researchers’ own personal biases or characteristics have not influenced the findings: in other words, replication is necessary to test the objectivity of an original piece of research.
Quantitative researchers tend to be keen on making sure studies are repeatable, although most studies are never repeated because there is a lack of status attached to doing so.
‘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.
Within sociology, one might even say that there’s a more ‘fundamental’ layer of concepts that lie behind the above – such as ‘society’, ‘culture’ and ‘socialization‘, even ‘sociology’ itself is a concept, as are ‘research’ and ‘knowledge’.
Concepts also include some really ‘obvious’ aspects of social life such as ‘family’, ‘childhood’, ‘religious belief’, ‘educational achievement’ and ‘crime’. Basically, anything that can be said to be ‘socially constructed’ is a concept.
Each concept basically represents a label that researchers give to elements of the social world that strikes them as significant. Bulmer (1984) suggests that concepts are ‘categories for the organisation of ideas and observations’.
Concepts and their measurement in quantitative research
If a concept is to be employed in quantitative research, a measure will have to be developed for it so it can be quantified.
Once they have been converted into measures, concepts can then take the form of independent or dependent variables. In other words, concepts may provide an explanation of a certain aspect of the social world, or they may stand for things we want to explain. A concept such as educational achievement may be used in either capacity – we may explore it as a dependent variable (why some achieve fewer GCSE results than others?) Or: as an independent variable (how do GCSE results affect future earnings?).
Measures also make it easier to compare educational achievement over time and across countries.
As we start to investigate such issues we are likely to formulate theories to help us understand why, for example, educational achievement varies between countries or over time.
This will in turn generate new concepts, as we try to refine our understanding of variations in poverty rates.
Why Measure Concepts?
It allows us to find small differences between individuals – it is usually obvious to spot large differences, for example between the richest 0.1% and the poorest 10%, but smaller once can often only be seen by measuring more precisely – so if we want to see the differences within the poorest 10%, we need precise measurements of income (for example).
Measurement gives us a consistent device, or yardstick for making such distinctions – a measurement device allows us to achieve consistency over time, and thus make historical comparisons, and with other researchers, who can replicate our research using the same measures. This relates to reliability.
Measurement allows for more precise estimates to be made about the correlation between independent and dependent variables.
Indicators in Quantitative Social Research
Because most concepts are not directly observable in quantitative form (i.e. they do not already appear in society in numerical form), sociologists need to devise ‘indicators’ to measure most sociological concepts. An indicator is something that stands for a concept and enables (in quantitative research at least) a sociologist to measure that concept.
We might use ‘Average GCSE score’ as an indicator to measure ‘educational achievement’.
We might use the number of social connections an individual has to society to measure ‘social integration’, much like Hirschi did in his ‘bonds of attachment theory‘.
We might use the number of barriers women face compared to men in politics and education to measure ‘Patriarchy’ in society.
NB – there is often disagreement within sociology as to the correct indicators to use to measure concepts – before doing research you should be clear about which indicators you are using to measure your concepts, why you are choosing these particular indicators , and be prepared for others to criticize your choice of indicators.
Direct and Indirect indicators
Direct indicators are ones which are closely related to the concept being measured. In the example above, it’s probably fair to say that average GCSE score is more directly related to ‘educational achievement’ than ‘bonds of attachment’ are to ‘social integration’, mainly because the later is more abstract.
How sociologists devise indicators:
There are a number of ways indicators can be devised:
through a questionnaire
through recording behaviour
through official statistics
through content analysis of documents.
Using multiple-indicator measures
It is often useful to use multiple indicators to measure concepts. The advantages of doing so are three fold:
there are often many dimensions to a concept – for example to accurately tap ‘religious belief’ questionnaires often include questions on attitudes and beliefs about ‘God’, ‘the afterlife’, ‘the spirit’, ‘as well as practices – such as church attendance. Generally speaking, the more complex the concept, the more indicators are required to measure it accurately.
Some people may not understand some of the questions in a questionnaire, so using multiple questions makes misunderstanding less likely.
It enables us to make more nuanced distinctions between respondents.
Measuring the effectiveness of measures in quantitative social research
It is crucial that indicators provide both a valid and reliable measurement of the concepts under investigation.
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.
Louis Theroux documentaries are a great example of ‘postmodern’ research methods.
I say this for the following reasons:
Firstly, these documentaries select unusual, deviant case studies to focus on, which is especially true of the latest series – ‘Dark States’ which consists of three episodes about heroin users, sex trafficking and murder.
Secondly, they tend to have a narrative style, focusing on people’s stories.
Thirdly, there’s a lack of structure about the documentaries… Theroux makes a connection with people and sees where that leads.
Fourthly – there’s no real attempt to be critical, or provide any analyses of the role of economic and political structures which lie behind these stories. In short, they are not properly sociological!
Finally, these documentaries seem to be produced for entertainment purposes only – they simply invite us to marvel or gawp at the ‘fantastically fucked up’ individuals before us, without offering any real solutions as to how they might sort their lives out, or how society should deal with them.
A brief analysis of two episodes of ‘Dark States’ demonstrates the postmodern nature of these documentaries:
In the first episode in the series, Heroin Town, Theroux looks at how the over-prescription of painkillers has unleashed a heroin epidemic. Theroux says that he largely steered clear of the pharmaceutical companies, regulators and politicians who permitted the disaster…. Instead, he hung out on streets where heroin and opioid addiction is “off the scale, unlike anything I’d ever seen before” and made addicts the stars, giving them space to express themselves and showing how many are beguiled by the romance of being outlaws.
The third episode, on Sex Trafficking in Houston, focuses on the relationships between sex workers and pimps, also shows the ‘postmodern documentary method – in which Theroux deliberately avoided making any value judgments:
Theroux says that he avoided the term “sex slave”: “If you overdo the abusive dimension, you strip the women of agency – it’s oddly disempowering and kind of neo-Victorian. The women are getting a kind of emotional fulfilment in their relationship with the pimps, even though it is poisonous and often damaging.” The pimps tended to be stylish, eloquent and intelligent. “These guys are, in their own way, deeply damaged, often the children of prostitutes, who may have had dads or family friends who were pimps. The closest analogy I have is that they are living in semi-apocalyptic conditions where the police are just not an option.”
Of course there are both strengths and limitations of these postmodern methods… I guess the biggest strength is that they allow the respondents to speak for themselves, and it’s down to the viewer to interpret the information as they will, and analyse deeper if they feel the need!
Websites, social media posts and similar virtual documents are all forms of secondary data, and thus amenable to both quantitative and qualitative content analysis.
There are, however, many difficulties in using web sites as sources of content analysis. Following Scott’s (1990) four criteria of assessing the quality of documents, we need consider why a web site is constructed in the first place, whether it is there for commercial purposes, and whether it has a political motive.
In addition, we also need to consider the following potential problems of researching web sites:
Finding websites will probably require a search engine, and search engines only ever provide a selection of available web sites on a topic, and the sample they provide will be biased according to algorithm the engine uses to find its websites. It follows that use of more than one search engine is advisable.
Related to the above point, a search is only as good as the key words the researcher inputs into the search engines, and it could be time consuming to try out all possible words and combinations.
New web sites are continually appearing while old ones disappear. This means that by the time research is published, they may be based on web sites which no longer exist and not be applicable to the new ones which have emerged.
Similar to the above point, existing web sites are continually being updated.
The analysis of web sites is a new field which is very much in flux. New approaches are being developed at a rapid rate. Some draw on traditional ways of interpreting documents such as discourse analysis and qualitative content analysis, others have been developed specifically in relation to the Web, such as the examination of hyperlinks between websites and their significance.
Most researchers who use documents accept the fact that it can be difficult to determine the population from which they are sampling, and when researching documents online, the speed of development and change of the Web accentuate this problem. The experience of researching documents online can be like trying to hit a moving target that not only moves, but is in a constant state of metamorphosis.
Three examples of content analysis of documents online
Boepple and Thompson (2014) conducted quantitative analysis of 21 ‘healthy living blogs’. Their sampling frame was only blogs which had received an award, and from those, they selected the blogs with the largest number of page views.
They found that content emphasised appearance and disordered messages about food/ nutrition,with five bloggers using very negative language about being fat or overweight and four invoking admiration for being thin. They concluded that these blogs spread messages that are ‘potentially problematic’ for anyone changing their behaviour on the basis of advice contained in them.
Davis et al (2015) conducted an analysis of postings that followed a blog post concerning a cyberbullying suicide y a 15 year old named Amanda Todd. There were 1094 comments of which 482 contained stories about being bullied, 12% about cyberbullying, 75% about traditional bullying, the rest a mixture of both.
The research found that the main reason victims of bullying are targeted is because they do not conform in one way or another to society’s mainstream norms and values, with the most common specific reason for bullying being a victim’s physical appearance.
Humphries et al (2014) conducted content analysis on the kinds of personal information disclosed on Twitter. The authors collected an initial sample of users and they searched friends of this initial sample. In total the collected 101, ,069 tweets and took a random sample of 2100 tweets from this.
One of their findings was that Twitter users not only share information about themselves, they frequently share information about others too.
Researching documents online may be challenging, but it is difficult to see how sociologists can avoid it as more and more of our lives are lived out online, so researching documents such as web sites, and especially blogs and social media postings is, I think, very much set to become a growth area in social research.