Tag Archive | research methods

3 words: I love you. [part 1]

Wendy Hollway’s piece Gender Difference and the production of subjectivity (1984) seemed to be somewhat dated when I started reading it. She aims to theorise gender subjectivity (i.e. gender identity from a psychologist’s perspective) by looking at practices and meaning making within heterosexual relationships.
Reference: Hollway, W. (1982) Identity and Gender Difference in Adult Social Relations, unpublished PhD thesis, University of London

Hollway takes an approach based on critical discursive psychology; she distinguishes this from a Foucauldian genealogical approach that would look at the operation of power as a more neutral force that may be creative and productive. Its main limitation, she argues, is the lack of acknowledgement of potentially contradictory discourses. From her point of view, the focus on a single patriarchal ideology is a weakness.

I perceive this assessment as flawed, mainly because ideologies are not single coherent units but mosaics that include dominant views and knowledge constructed by those who hold authority and power to shape them as well as the many opposing and undermining views and perspectives which all evolve in relation to more dominant discourses within a broader ideology. However, it is important to acknowledge that this early work of Hollway was based on Foucault’s earlier studies which were criticised for their lack of recognition of agency in the context of operation of power. Hollway did not manage to ‘repair’ this very aspect in her theory as she argues that alternative discourses are often not accessible to women, which implies indeed their lack of agency and a co-dependency (or even co-ownership) in what she perceived as dominant male power. I will discuss her approach from a methodological perspective and I will question her assumptions from a view informed by contemporary use of old and new media.

For an interesting reading (different methodology, different discipline) of my critique in a contemporary context, I suggest the research findings by Angel Brantley, David Knox and Marty E. Zusman . They conducted a study, published in 2002, which investigated how 147 undergraduate students in the US handle the first stages expressing feelings in a love relationship. The survey looked at how students use and establish meaning when telling their new partner ‘I love you’. The authors suggest a socio-biological explanation for finding that

  • males were more likely to say ‘I love you’ first
  • males were more likely to say ‘I love you’ when they thought this could increase their chance to have sex with their partner.

Brantley et al. reference earlier studies by Sharp & Ganong (2000) which “found that men fall in love more quickly and have higher levels of romantic beliefs than women.” And they took into account the research undertaken by Knox, Sturdivant and Zusman (2001) which found that “men are more likely to seek sex early in the relationship (indeed, within hours) than women”.

They also found, not very romantic, though, that students might be actually aware of these patterns and that they had a good sense of what ‘I love you’ may mean in certain contexts. The study is not representative due its small sample. Moreover, the number of female participants was more than twice as large as the male students.

Whether qualitative or quantitative research, it often strikes me how little exchange there seems between or among disciplines. Discourse analysis, the way Hollway conducted it, seemed to overly support Feminist claims valid at that time. Her research then made neither use of a triangulation (for instance by adding survey research and looking at broader patterns) nor did she provide a reflexive account that would have helped readers to understand a possible bias towards certain socio-political beliefs informing her project.

Exactly 20 years later, Brantley et al. equally provide a highly biased and limited account by relying on a group of students who are by definition widely homogenous in terms of social markers such as age and social class (as well as cultural capital). As interesting as the research findings may sound, they lack depth and the richness that comes with qualitative research based on in-depth interviewing.

I will discuss love and sex further in a post that focuses on interview excerpts used in Hollway’s research and my own observations: in Part 2

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Research Design: methodology in question

One of the blogs I follow on a regular basis is Jeffrey Keefer’s Silence and Voice which is currently concerned with some issues related to research design and formulating of research questions in the wider context of auto-ethnography as methodology and identity construction as the subject of interest. Recent posts I found very interesting and commented on are the one on broader research design questions and the one on auto-ethnography and reflexivity which are worthwhile having a think over – they provide very good ground for some reflection on dilemmas and politics entailed in the underlying epistemological questions of research-related decision-making.

I am fascinated by the way crowd-sourcing can work in academic blogging, it’s a great way of engaging broader audiences and gaining some insights from outside immediate areas. I like and do value the fact that academic bloggers, busy with studies and work, research and other things, take the time and effort to reflect publicly online, open up to questions and critiques – and respond to comments and ideas. Personally, I enjoy the challenge to think about issues and see whether I can contribute some ideas and to what extent I need to improve on gaps and communication of insights.

Jeffrey’s research made me recall some podcasts featuring Stuart Hall et al. debating questions related to identity construction. They form part of the Open University’s post-graduate course D853 Identity in Question which I studied in 2008 – the interviews cover Lacanian Theory, Language Approach, subjectivity and legal definitions of personhood as well as some comments on Michel Foucault’s genealogical perspective. They last 2 to 9 minutes and deliver some great food for thought. I also came across James Schirmer’s paper on Scribd which I recommend as thought-provoking read in this context The Personal as Public: Identity Construction/Fragmentation Online

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Ethical issues in Social Research Projects

This short paper discusses ethical issues as embedded in a TV reality show format that provides the [ill-designed] imagined setting for a social psychology-informed research project looking at group dynamics and performance under stress. The core principles of informed consent, briefing and debriefing, backup, coercion and incentives are applied to the experiment.
You find the PDF below and for download on Slideshare where you can also get a presentation transcript. Creative Commons Licence applies, attribute please. And if you like it: quote, embed – and question it 🙂

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IR10: Multidisciplinary Internet Research

This year’s annual conference of the Association of Internet Researchers (AoIR) Internet Research 10.0– Internet: Critical will be held 7-10 October 2009 in Milwaukee, WI, USA. I will be attending the preconference workshop on Multidisciplinary Internet Research which participants were asked to prepare for. The preparation covered a list of [early-stage] research questions, theoretical and methodological frameworks and key literature drawn upon in the reflection on interdisciplinary and multidisciplinary research design.

The workshop organisers have set up an already quite comprehensive wiki which is available on sociotech.net and contains my summary that is also available on Slideshare where you will be able to find a transcript of the 2-pages PDF. The wiki will be updated in due course, so keep watching if that field interests you.

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exam revision: deductive versus inductive research strategies

This belongs to the revision of social research strategies, I am going to summarise the key differences between inductive and deductive research approaches – but first what they’ve got in common. Both strategies are rooted in a positivist assumption in terms of epistemology and ontology. The underlying empiricism, i.e. the notion that only knowledge gained through experiences and senses is acceptable, is implemented by rigorous testing. Enlarging the number of instances observed (samples) increases plausibility and the number of regularities being identified. The accumulated ‘facts’ provide basis for general laws of cause and effects. Those are depicted in models as dependent (predictor) and independent (outcome) variables.

Inductive theory is being derived from the observations made. This approach cannot test hypotheses but generates them. In contrast, deduction is theory-driven, it’s based on preconceptions and aims to overcome the limitations of induction. It puts theories to the test, that means hypotheses can be falsified and disproved. The aim is to move closer to the truth, hence the gradual elimination of false theories implies that theories tested and not disproved can only be considered provisional.

Ideally, a deductive approach starts with a theoretical framework (for instance based on Erving Goffman’s ‘stigma’ or Pierre Bourdieu’s ‘social capital’) and the formulation of hypotheses. Usually, this includes an alternative hypothesis (also called experimental H., which states the effect assumed) and the null hypothesis (which states the effect is absent). What follows is the data collection which delivers findings that either result in confirmation or rejection of the null hypothesis and a subsequent revision of the theory.

In practice, though, deduction often entails an element of induction and vice versa. This is rooted in theoretical reflection once the data has been collected or the desire to establish conditions which allow the theory to hold (or not). This continuous weaving back and forth between data and theory and is called an iterative strategy, particularly evident in qualitative research which takes a grounded theory approach and a way to add to the validity of research. In quantitative research, it is advisable to carefully distinguish between the more complex development of theory and the generalisation of empirical findings.

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exam revision: epistemology and ontology

Some brief summaries for the DT840 exam in research methods and skills. I am revising the secondary literature and OU course material as discussed on 4th and 8th August.

Ontological and epistemological positions provide fundamental aspects of research as they concern the philosophical questions what counts as reality and how beings come into being as well as what constitutes knowledge and how knowledge comes to be established. Two core positions can be distinguished in either area: positivist and constructionist.

  • positivist ontology: the world is ‘out there’, it operates in a systematic and lawful manner, discrete and observable events, reality is separate from human meaning-making;
  • constructionist ontology: assumes the world we can study is a semiotic world of meanings, represented in signs and symbols, language is central to this position;
  • positivist epistemology: knowledge can only be gained by gathering facts in a systematic and objective manner, predominantly by the experimental method and by testing of hypotheses in order to gradually build laws. The aim is to refine them and achieve applicability on a universal level;
  • constructionist epistemology: knowledge is constructed rather than discovered, it is a representation of the ‘real world’ and interpreted by the researcher. Knowledge is subject to time-space configurations and a means of power (e.g. doctors as ‘architects of medical knowledge’). Scientists and their institutions shape the production of knowledge by their choices and values.

These positions significantly shape research designs and methodologies.

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Research Methods – the useful material

Following on from my previous two posts, here is a list of very useful material I recommend for studying Social Research Methods including

  • research strategies and design,
  • literature review,
  • ethics and politics of research
  • sampling,
  • qualitative and quantitative methods,
  • as well as data analysis,
  • writing up social research and presentation of findings.

References:
BRYMAN, A. (3rd ed.) (2008) Social Research Methods. Oxford: Oxford University Press.
Resource centre including Flashcards, Multiple Choice Questions etc. as well as some hands-on Excel data analysis/tutorials. More useful links in relation to each chapter to external sites: weblinks by chapter. The book is also listed on Amazon, where you can search inside: Bryman’s Social Research Methods on Amazon.

DE VAUS, D. (5th ed.) (2002) Surveys in Social Research. Abingdon: Routledge.
de Vaus’s Surveys in Social Research on Amazon. This edition comes with a massive number of weblinks which de Vaus has listed on his site. Further de Vaus links, site set up by an OU student: who publishes under Ariadne and also some handy notes related to the OU’s DT840 study guide .

LEE, Carl et al. , Central Michigan University.
Tutorials and Movie Clips (based on SPSS 9.0 and 10.0) with transcripts

LEVESQUE, Raynald in Montreal, Canada SPSS tools

OPEN UNIVERSITY (OU)
OpenLearn SPSS is a step-by-step online tutorial which covers adding variables, obtaining descriptive statistics, correlation, independent t-tests, and paired samples t-tests.

ROWNTREE, D (1981) Statistics without Tears: An Introduction for Non-Mathematicians. London: Penguin Books.
a classic on Amazon, search inside.

SEALE, C. (ed.) (2004) Social Research Methods – A Reader. London: Routledge.

SOPER, Daniel offers a free calculator for multiple regression as well as a great overview of numerous concepts on his Free Statistics Calculators site which is an excellent online support source for last minute revision, pop-up windows will save you time.

TROCHIM, William M.K. Social Research Methods is another incredibly helpful site. Well structured and illustrated.

UNIVERSITY OF CALIFORNIA, Los Angeles (UCLA)
SPSS Version 15.0 Learning Module includes T-tests, Chi-square tests, correlation, ANOVA (Analysis of Variance) as well as a detailed, well-structured discussion and explanation of Regression among their SPSS Webbooks.

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Research Methods – DT840 and beyond, review of course books

As announced in my earlier post on Research Methods and Skills
I am providing here a brief review of the books which present the set books in my current post-graduate course on research skills and statistics, i.e. the Open University post-graduate course DT840 (DTZY840). The assessment (5 assignments and an exam) is based on the following materials:

LE VOI, M., Sapsford, R., Potter, S., Green, A., Redman, P. and Yates S. (2008) DT840 Course and Study Guide. Milton Keynes: The Open University

POTTER, S (2nd ed.) (2006) Doing Postgraduate Research. London: Sage.
This set book by Stephen Potter – OU Professor, specialist in transport strategies, and course team members – is available on Amazon. There is also a companion which contains related links and chapter excerpts: Potter companion on Sage which, unfortunately, appears to be neglected: 3 listed links out of 4, supposed to connect to ethical frameworks, turn out to be broken. Some of the course assessment is based on the online sources which you will need to find elsewhere. I have listed ethical guidelines in a separate box on the right hand within this blog.

SAPSFORD, R. (2nd ed.) (2007) Survey Research. London: Sage.
Also this one is available on Amazon, interested readers can: search inside. The reviews on Amazon are throughout very negative and the reviewers have gone into great detail with their substantiated critique. It’s helpful to read them and keep in mind the following problems with the material:

  • Lack of a glossary
  • Minimalist link list and Index
  • Key concepts such as triangulation not mentioned
  • Discusses online research settings only very briefly, insufficient
  • References to chapters/figures/boxes/tables rather than to pages
  • 1st edition had attracted equally negative reviews
  • 16 pages contain substantial errors: in formulae, explanations of concepts, tables are wrongly labelled etc. Luckily the OU provides a list of corrections, but it’s not comprehensive and you will need to constantly check and correct.
  • Carelessly compiled bibliography: referencing appears to follow random systems and lacks consistency (the OU prefers Harvard referencing style also in this course).
  • Unclear structure with a wordy approach

[N.B. To make matters worse: NO previous exams available – as common for the majority of courses on OUSA site, yet 1 exam specimen paper is delivered by OU.]
Here is a site which lists Sapsford’s content without providing any evaluation: Sapsford content, overview by OU student.

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Andy Field’s Discovering Statistics using SPSS – a student review

As mentioned before in my post on Research Methods and Skills here is a review of the book by Andy Field that has proved to be most helpful in my current post-graduate statistics course:

FIELD, A (3rd ed.) (2009) Discovering Statistics using SPSS. London: Sage.

For this 820 pages oeuvre there is a companion available with a number of student resources such as multiple choice questions and a flash card gloassary. Field’s companion on Sage
I got the edition which includes a 13 months student licence for SPSS Version 17.0.

Here are a number of reviews on Amazon . It is the most user-friendly, smart-structured, and accessible as well as entertaining Statistics book I have come across. If you are a busy student with more than a commitment to studies, try this. Field is doing a fantastic job in providing an all-you-need volume which does not step into the trap so many other authors seem to be unable to avoid. All those who believe they can fragment statistics and provide either the maths only, or the SPSS only or some statistics chunk food that leaves you unsatisfied as you still don’t understand how to apply findings to a case other than the model discussed.

Field’s book provides a 16-pages glossary, 7-pages references, index plus an appendix which contains the following:

  1. Table of the standard normal distribution
  2. Critical values of the t-distribution
  3. Critical values of the F-distribution
  4. Critical values of the chi-square distribution

There is a separate chapter about SPSS, the environment, the viewer, the SmartViewer, the syntax and more. A list of mathematical operators, Greek symbols and English symbols comes in very handy, so does the brief maths revision
EasyMaths .

Each chapter highlights at the end the important terms which is very useful for revision. There are self-tests, references for further reading and interesting real research as well as areas which explain either ‘strange dialogue boxes’ (in SPSS and how to make sense of them) or concepts (such as degree of freedom).

The chapters are structured in a clear manner, the language is clear and terms are explained throughout so that you won’t have to flip nervously through several books at the same time and do the work a smart author and editing team would have done for you. Formulae and tables produced in SPSS are displayed in a logical manner, for instance the dialog box to be selected in SPSS is followed by a scatterplot which in turn is illustrated by SPSS outputs. The latter are also explained in detail so you know what they actually mean, how to write them up in a conventional way, how to analyse them and how to interpret the outcome. Key terms have been printed in red and the SPSS dialogue boxes also come in colour.

Recoding, for instance, is explained for those using the recode function in SPSS but also for those who do a lot of recoding, there is the syntax and a related file on the CD. There is a number of data sets available to play with, Field has chosen to provide areas such as the impact of Viagra on a person’s libido (getting those on board who are tired of jobs in postoffice.sav or the little inspiring government statistics on traffic) in order to explain ANOVA (analysis of variance).

Field’s Statistics Hell is also very useful and offers:

  • Lectures on frequency distributions
  • Handouts: SPSS: t-test, frequency distributions and correlation

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