7.5.3 Alternative theoretical conceptualisations
Much more important than the selective reporting of politicians is the differing interpretations that can be placed on the same data depending on the epistemological underpinnings and sociological theorising of the researcher. This goes beyond Widdecombe’s simplistic slight of hand.
For example, Tables 7.1 to 7.3, show the educational qualifications attempted, qualifications gained, and post-school destinations of school leavers (for 1986–7). Two alternative conceptualisations (both broadly positivistic) result in quite different conclusions: first, a view based on sociobiology and, second, a functionalist view.
Table 7.1 Percentage of leavers who attempted GCE/CSE in the following subjects, 1970–1 and 1986–7
Source: Department of Eduation
Table 7.2 Highest qualification achieved on leaving school, 1986–7
2 A levels/3 S Highers
1 A level/1 or 2 S Highers
5 or more O levels*
1-4 O levels*
Other CSE passes
No GCSEs or CSEs**
*or equivalent CSE grades **Grade D or less and/or equivalent CSE grades
Source: Department of Eduation
Table 7.3 Destination of school leavers 1986–7 (percentages)
Source: Department of Eduation
A possible sociobiology interpretation
Sociobiology (Wilson, 1975) argues that the genetic make-up of humans is an important, if not indispensable, element in many aspects of social life. Genetic factors explain, for example, why men tend to be dominant and women passive. Such views are controversial and resurrect the nature–nurture debate in sociology. The moderate sociobiological view of the importance of biological factors suggests that while our behaviour is genetically influenced it only affects the limits of what we might do rather than determining specific actions.
The following interpretation of the tables makes use of the sociobiological view.
Table 7.1 shows that over 80% of both boys and girls attempt mathematics and English GCSE/CSE. This reflects the priority placed on these subjects at school. While as many boys as girls attempt science, it is noticeable that boys are almost three times as likely as girls to attempt technology. On the other hand, girls are much more likely to attempt foreign languages and creative arts.
These differences reflect the differing aptitudes of boys and girls.
If we consider Table 7.2, then, we can see that there are more girls (18.9%) with A-levels than boys (16.1%). Overall, 59.9% of girls get O or A level qualifications compared to 53.5% of boys. This indicates that girls tend to develop earlier than boys. However, although girls develop faster they reach a peak and tend not to go on to develop academic careers to the same extent as do the later-developing boys.
Table 7.3 shows that more boys than girls go into employment and this probably reflects their bent towards technology and the availability of jobs in such areas. Although 33.2% of girls go into further and higher education compared to only 25.4% of boys, a larger percentage of boys (8.3%) than girls (6.6%) take degrees. Furthermore, if we only consider those who go into further and higher education this difference is accentuated. Only 19.9% of girls who stay in education (6.6% of 33.2%) go on to degree courses while 32.7% of the boys who stay in education (8.3% of 25.4%) take degree courses. This shows that girls are probably less academically inclined than boys and that they are naturally more drawn to practical, caring and nurturing occupations, which tend to be taught on further education courses, rather than to academic degrees.
A possible functionalist interpretation
Functionalist approaches to education would see it as providing pupils with the training, knowledge and skills necessary for their effective participation in the labour force. A functionalist analysis might therefore argue that the overall increase in the number of pupils taking examinations, and the dramatic increase for girls, is simply a response to the changing demands of the labour market (Table 7.3).
If modern industrial economies need an increasingly skilled work force then it is the role of education to meet this need. Other developments in education such as the introduction of a National Curriculum and the growth of vocationalism provide further evidence of the functional relationship between the education system and the labour force.
The functionalist perspective also sees the education system as being important in reproducing the ‘social consensus’ by transmitting society’s norms and values. They may suggest that part of this consensus relates to the different roles men and women perform in society. Parsons (1951), for example, argued that a gender-based division of labour was the most efficient way of organising society. Within the modern nuclear family the male performs an instrumental role as the main family ‘breadwinner’ and this is complemented by the supportive or ‘expressive’ role performed by his partner.
This view might suggest that, although more girls than boys are taking examinations and achieve higher grades, they are less likely to have a serious commitment to a career and thus to higher education, because this would conflict with their future primary function within the domestic sphere. This would account for the fact that although more girls get A levels (18.9%) than boys (16.1%), fewer girls go on to degree level (6.6%) than boys (8.3%).
Reinterpret the tables from a feminist perspective. Bear in mind thi is historical data and recent data that you might uncover may give further weight to the reinterpretation. Time: 30 minutes plus additional time seeking more recent data.
7.5.4 Informed scepticism not prejudice
It is important for the social researcher to adopt a sceptical attitude towards published statistics and they way they are reported. However, this scepticism needs to be informed and based on a critique of the methdology used in compiling the statistical data and on the presentation of the summaries. Governments and other organisations are not averse to manipulating statistical data to suit their own ends; adjusting the way that data are collected to produce a positive impression of their own policies and actions (Section 7.5).
The number of people out of work is a very different statistic to the number of people out of work and claiming benefits, although both are referred to as the number of unemployed. And the number out of work and claiming benefits can change simply by changing the rules on how long one has to be out of work before a claim can be made.
So being aware of how statistics are compiled and how the methodology changes is important and this information is available in the vast majority of cases, both for official and non-official published statistics, although it sometimes requires investigation to uncover the detail. Identifying how statistics are produced from so-called 'big data' (see Section 7.4.3) is rather more difficult as these data are controlled by large corporations and used for their own benefit. What little is published tends to have sparse detail on the method of compilation. Some forms of big data, such as that generated through social media, has the added disadvantage of being of suspect veracity. Concerns over fake news, combined with false blogs and simply self-deluded postings means that the researcher needs to be careful how social media data is used.
During the Arab Spring of 2011, a Scotland-based heterosexual male regularly made web posts between February and June in the persona of a lesbian woman in Syria. The blog, 'A Gay Girl in Damascus', gathered a growing following until the hoax was revealed, intensifying concerns about unverified user-generated information. The blogger claimed he used the hypothetical persona to try to illuminate the events in the Middle East for a western audience. However, any reader would have been ultimately relying on fabricated information (Addley, 2011).
People posting under their real name are not guaranteed to provide a 'truthful' account: if based on perception, then the information could be mistaken or biased, as perceptions are not always an accurate portrayal of what occurred. When reporting about their own experiences, most people present themselves in a positive light.
There is a long tradition of scepticism of large scale statistical data: the adage 'lies, damn lies and statistics' sums up this scepticism. However, such concerns reflect the need to investigate the basis of statistical claims. Rather more worrying in the mid-2010s is the ignorant disavowal of statistics, particularly by populist politicians, simply on the basis that statistical data contradicts their deep-seated prejudices. This is evident in areas such as immigration, where statistical data showing the economic benefits are rubbished as fabricated simply because the evidence is contrary to anti-immigration prejudices. Such an approach, while possibly garnering votes, is a disaster for rational analysis and for democracy. It leads to misinformation, which, through the uncritical medium of social media, can spread rapidly and become established as 'truth' in what has been described as the 'post-truth' society.
Healthy scepticism based on critique and analysis, not prejudice and populist misinformation, is an important part of the social researcher's toolkit.