Based on in-depth interviews with twenty-three Israeli mothers, this article seeks to contribute to an ongoing inquiry into women’s subjective experiences of mothering by addressing an understudied maternal emotive and cognitive stance: regretting motherhood. The literature teaches us that within a pronatal monopoly, threatening women that they will inevitably regret not having children acts as powerful reproducer of the ideology of motherhood. Simultaneously, motherhood is constructed as a mythical nexus that lies outside and beyond the human terrain of regret, and therefore a desire to undo the maternal experience is conceived as an object of disbelief. By incorporating regret into maternal experiences, the purpose of the article is twofold: The first is to distinguish regret over motherhood from other conflictual and ambivalent maternal emotions. Whereas participants’ expressions of regretting motherhood were not bereft of ambivalence, and thus were not necessarily exceptional or anomalous, they foreground a different emotive and cognitive stance toward motherhood. The second purpose is to situate regret over motherhood in the sociopolitical arena. It has been suggested that the “power of backward thinking” might be used to reflect on the systems of power governing maternal feelings in two ways: first, through a categorical distinction in the target of regret between object (the children) and experience (maternity), which utilizes the cultural structure of mother love; second, by opposing the very essentialist presumption of a fixed female identity that naturally befits mothering or progressively adapts to it and evaluates it as a worthwhile experience.
Donath, O. (2015). Regretting motherhood: A Sociopolitical analysis. Signs,40(2), 343-367.
Category Archives: qualitative and quantitative research debate
Why “there is no such thing as economic science”?
I have recently referred to an interview made to Piketty where he states “there is no such thing as economic science. There are social sciences”. He argues that “economic processes involve social control” and that “we should teach economics much more in conjunction with economic history, social history, political history, political science”
That said, the truth is that Piketty’s argument is deductible from the classic economic sociology concept embeddedness. It refers to the degree to which economic activity is constrained by non-economic institutions. The term was created by economic historian Karl Polanyi as part of his Substantivist approach. Polanyi argued that in non-market societies there are no pure economic institutions to which formal economic models can be applied. In these cases economic activities such as “provisioning” are “embedded” in non-economic kinship, religious and political institutions. In market societies, in contrast, economic activities have been rationalized, and economic action is “disembedded” from society and able to follow its own distinctive logic, captured in economic modeling. Polanyi’s ideas were widely adopted and discussed in anthropology in what has been called the “Formalist vs Substantivist” debate. Subsequently, the term “embeddedness” was further developed by economic sociologist Mark Granovetter, who argued that even in market societies, economic activity is not as disembedded from society as economic models would suggest.
“Spurious correlations” is the name of a website I came across recently. There you can see plenty of cases where correlation may not imply causation. What does it mean in terms of research methods in the social sciences? It means that whenever our research approach is uniquely quantitative, we take the risk of come up with wrong or non-consistent findings. In other words, a certain doses of qualitative interpretation is always required in order to avoid wrong and sometimes ridiculous depictions of the social reality, like in the bellow example. It is true that advance and multivariable analysis allow having a more accurate understanding of certain social phenomena nowadays. However such analysis should always be preceded by a good interpretation of such phenomenon. What does “good” mean? Well, first of all take into consideration whether two or more variable are susceptible to be part of the same social reality. It doesn’t seem that “US spending on science, space, and technology” and “Suicides by hanging, strangulation and suffocation” has anything to do one each other. Secondly, even when two variables may potentially explain certain realities we should try to include more than one explicative variable. For instance, when studying the reality of Polish labor market, we may find correlation between education and employment. However, an accurate analysis should also include such other variables as age, income or social class. Such analysis are possible via the so called multivariate statistical analysis to be hopefully covered in future posts. The key of this sort of analysis is considering the right variables. To do so, we can use previous theories, where certain authors (based on previous empirical studies) suggest a number of a priori relevant and explicative variables.
“Quantitative and qualitative social science” by Daniel Little
I would like to share here a outstanding post on the quantitative/qualitative debate by Daniel Little in his blog Understanding Society. Debate addressed in previous posts here and that is gaining more and more importance within social science.
THE social world is one reality, but the methodologies associated with quantitative and qualitative research are quite different. Quantitative research allows the researcher to discover patterns, associations, correlations, and other features of a population based on analysis of large numbers of measurements of individuals. Qualitative research usually involves studies of single individuals, based on interviews and observations, with the goal of identifying their internal psychological and behavioral characteristics. Quantitative research is directed at identifying population characteristics, patterns, and associations. Qualitative research is directed at teasing out the mental frameworks and experiences of individuals within specific social and cultural settings. Qualitative researchers are generally not interested in discovering generalizations or regularities, and are more interested in identifying particular features of consciousness, culture, and behavior.
What kinds of interface or bridging are possible between these two levels of social research?
Take the example of race studies. Both qualitative and quantitative research studies have been conducted in this field, with the goal of shedding light on the phenomenon of race in American society. Quantitative research has often been concerned to identify the features of inequality which are associated with race within American populations, including income, wealth, education, health, employment, and other important features. For example, the National Survey of Black Americans provides voluminous data on a range of characteristics of African American individuals, with surveys extending from 1979 to 1992 (link). Here is a list of the variables included in these studies (link). Several hundred research studies and reports have been completed making use of these data sets; here is a representative study by James Jackson making use of data sets like these to probe health disparities by race (link). These quantitative studies permit the researcher to use advanced statistical tools to measure and evaluation the strength of associations among characteristics and to evaluate causal hypotheses about the linkages that exist among characteristics.
Qualitative research on race takes several forms. There are ethnographic studies, through which the researcher attempts to identify the phenomenology and lived experience of race. Here I would include several research efforts that have been discussed here previously — Al Young’s study of young inner city Chicago men (The Minds of Marginalized Black Men: Making Sense of Mobility, Opportunity, and Future Life Chances) and Loïc Wacquant’s ethnographic study of a boxing club on Chicago’s south side (Body and Soul: Notebooks of an Apprentice Boxer). There are theoretical studies, which explore possible structures or mechanisms which produces racial and racialized behavior and disparities. Here is a good example from Elizabeth Cole on the construct of intersectionality as a way of theorizing about racial and gender identities (link). And there are studies of social psychology designed to identify the ways in which racial attitudes, presuppositions, and ideas contribute to behavior in American society. Here is a nice example of such an analysis by Lawrence Bobo and Cybelle Fox (link).
It is clear that studies based on all of these methodologies are insightful and valuable. We will arrive at a better understanding of the meaning and causal importance of “race” through all these approaches. The question raised above remains an important one, however: how should we think about the relations among these bodies of inquiry and knowledge?
One way is to think in terms of levels of analysis (link): we might say that quantitative studies examine facts about race at a more macro level (large populations), whereas qualitative studies are more meso- or micro-level studies. This isn’t a very satisfactory view, however, because each of these approaches is concerned about individual-level facts; what differs is the level of aggregation of those facts that is chosen.
Another approach seems more promising: to consider the suite of qualitative studies of race as being a tool box for identifying the social mechanisms through which the patterns and associations that are discovered at the large population level come about. Qualitative studies (studies aimed at discovering or theorizing the mentalities and behaviors through which race is constructed and carried out) permit us to understand racialized behavior in groups that in turn allow us to understand the population outcomes that quantitative studies identify.
A third possibility is that these different methodological approaches do not admit of “bridging” at all. Here the idea would be that these are fundamentally different forms of knowledge, and they belong in different parts of the toolbox. Sometimes this approach is taken by advocates of one methodology or the other in dismissing the scientific credentials of the other approach — quantitative researchers who dismiss qualitative research as anecdotal and qualitative researchers who dismiss quantitative research as positivist. This approach seems fundamentally wrong. We should look at the various ways of studying important aspects of social life as being complementary and fundamentally consistent.
My own predilection is to think of the qualitative approaches as providing insight into how various social processes work; how it is that socially constructed actors bring about the patterns of behavior and outcome we observe at various levels of aggregation. A quantitative study of racial attitudes might suggest that cities with effective public transportation have higher (or lower) levels of racial mistrust across groups. We would want to be able to form some hypotheses about what the underlying behaviors and attitudes are that bring about this effect. What are the mechanisms through which access to public transportation influences racial trust? And for this kind of inquiry to be possible, we need to have some good empirical theories about racial identities and mental frameworks.
So it does in fact seem both possible and desirable to try to integrate the findings of both quantitative and qualitative studies of racial attitudes; and this finding seems equally valid in almost all areas of the social sciences.
(Thanks to Mosi Ifatunji for his stimulating seminar at the University of Michigan on new approaches to the study of black ethnic disparities, which caused me to think about this topic a little further. Here is Mosi’s webpage with some links to his work; link.)
Source: Little, Daniel (2014) Understanding Society Blog. Retrieved from here
Why the qualitative approach is essential for every research project?
“Recently, it was conducted a global survey which sought to answer the following question: Please answer honestly. How in your opinion could be solved the problem of lack of food in many countries in the world?”
The survey was a failure because in Africa nobody knew what food means. In France nobody knew what honesty means. Nobody knew in Western Europe what having lack of something means. In China no one knew what is having your own opinion. In Arabs countries none knew what is solving a problem. In South America, nobody knew what the word “please” means. In North America, no one knew that other countries exist.”
The above parody is just that, a parody. However, it illustrates very well how the ambiguity of such terms as happiness, leadership or being modern are constantly challenging social researchers. “The more ambiguous and elastic our concepts, the less possible is to quantify our data in a meaningful way” (Dey, 1993) Can we measure happiness all over the world if the meaning of it may strongly vary from one country to another? It may be not possible assuming right away a quantitative approach. And it is precisely here where the qualitative one finds its place. Qualitative techniques may bring the not measurable concepts into the “realm” of the measurable. Indeed it is “an opportunity to explore a subject in as real manner as is possible” (Robson, 2002).
For instance, what is a great place to work? We can quantify work by the unemployment rate in every country, as well as places where people work just collecting information on the number of companies. But great place to work? We could actually build another funny story as above, or just try to understand what people think what a “great place to work” is. And this is precisely what Great Place to Work did to measure a prior ambiguous concept.
This company on a year basis publishes a best workplace ranking both nationwide and worldwide. To do so they built up a model formed by categories of analysis like trust, enjoy or pride, among others. In turn each of them is divided into indicators. These indicators give way to a questionnaire that is used in a survey among a set of companies in every country. As they report in their website, “this model has been confirmed through over 25 years´ worth of analysis of employees´ own opinions“.
Therefore, the quantification of a priori ambiguous concepts is preceded (or even accompanied) by a qualitative analysis. This analysis consists of doing a categorization of what people think it is a great place to work. If the result of a quantitative study is usually a graphic or a statistic table, the result of a qualitative study is based on categorizations.
Finally, although the categorization process is frequently used as way to identify measurable units referred to ambiguous concepts, as in the above example, it may be used independently, i.e. doing a categorization of happiness, for instance, may have as the only aim to obtain an accurate understanding of this concept, regardless it is going to be or not measured later.
- The meaning of qualitative methods (researchmethodsgdansk.wordpress.com)
- Why qualitative research? (Case study and solution) (researchmethodsgdansk.wordpress.com)
- Qualitative vs. quantitative debate or why facebook is not driving the debt crisis (researchmethodsgdansk.wordpress.com)
Imagine a conversation between the qualitative and quantitative approach!
(Needless to say that if case Qualitative would be feminine and quantitative masculine)
– Mr. Quantitative: we need to find out social causal relationships
-Mrs. Qualitative: why?
-Mr. Quantitative: obviously, to be able to do law-like generalizations like natural scientist do!
-Mrs. Qualitative: It is not possible because relationships of human beings might be spurious.
– Mr. Quantitative: I don´t understand.
– Mrs. Qualitative: we don´t need to be like natural sciences and do law-like generalizations, we just need to get a more accurate understanding of the phenomenon under study, as well as reflect on and interpret it.
The limits of quantitative research in social sciences
“If there is no net force on an object, then its velocity is constant. The object is either at rest (if its velocity is equal to zero), or it moves with constant speed in a single direction“. First Newton law
The mastering of the so called “law-like generalizations” (Saunders et at, 2009) produced within natural science as the above example, as well as the supremacy of the way of thinking using reason that give the name to the so called Age of Enlightenment (or simply the Enlightenment or Age of Reason) would eventually influence the development of social science in the 19th century.
Such authors as Auguste Comte would claim that only phenomena that you can observe will lead to the production of credible data. Like natural science does. Emile Durkheim´s theory on suicide exemplifies very well this idea. Durkheim explores the differing suicide rates among Protestants and Catholics, arguing that stronger social control among Catholics results in lower suicide rates. In other words, suicide may be explained by a number of social laws.
What do Durkheim and Newton´s laws have in common? Both establish causal relationships between variables and both try to explain the reality (society and nature respectively): net force/velocity relationship on the one hand and the religion culture/suicide rate one on the other.
Many law-like generalizations have their precedent in suicide Durkheim theory. We all listen to statements based on this principal in media every day, e.g. “the more an employee earns the more satisfied is at work”, “the more economically advanced is a country the low is the birth rate in the world” This philosophy, so called positivism, is actually the essence of the quantitative approach in research. Furthermore, many of today´s decision making are based on this philosophy. Human resources management is often based on such relationships. “High productivity rates mean that one employee is working hard. For this reason, the manager decides to increase his salary“. It is simple common sense, isn´t it?
But, does relationship implies causality? Something like that must have wordered Max Weber at the turn of 20th century, who is considered one of the founders of antipositivism philosophy and, therefore of the qualitative approach. As Business Week’s Vali Chandrasekaran writes, “Correlation may not imply causation”. Although pretentious, the bellow graphic illustrates very well this argument. “Is facebook driving the Greek debt crisis?” Hopefully you already know better which way the wind is blowing regarding the limits of quantitative research.
Moreover, Max Weber argued that the relationships of human “social action” might be spurious. As an antipositivist, making generalizations are not the essence of social research. It does not mean that one should not seek relationships between variables, but there is no reason to do law-like generalization. The emphasis is place, on the contrary, on obtaining a more accurate understanding of the phenomena under study. As well as positivist philosophy is the essence of the quantitative approach, the antipositivist one is the essence of qualitative.
Craig J. Calhoun, Donald Light, Suzanne Infeld Keller. Sociology. McGraw-Hill, 2000.
Chandrasekaran , Vali (2011, December 1). Correlation or Causation?. Retrieved from http://www.businessweek.com/magazine/correlation-or-causation-12012011-gfx.html
Lewis, P., Saunders, M. N. K., & Thornhill, A. (2009). Research methods for business students Pearson.