8
Selecting a Case
I concluded the previous chapter with my favourite research maxim: 'make a lot out of a little', tf you take me seriously, you will have every chance of producing a thorough, analytically interesting research study. However, a nagging doubt may well remain.
This doubt surfaces in a regular refrain I hear from student researchers. 1 have so few data, only just one case,' they say, 'how can 1 possibly generalize about it?'
Genera I i/ability is a standard aim in quantitative research and is normally achieved by statistical sampling procedura. Such sampling has two functions. First, it allows you to feel confident about the representativeness of your sample: 'if the population characteristics are known, the degree of representativeness of a sample can be checked' (Arber, 1993: 70). Second, such representativeness allows you to make broader inferences:
The purpose of sampling is usually to study a representative Subsection of a precisely defined population in order to make inferences about the whole population. (1993: 38)
Such sampling procedures are, however, usually unavailable in qualitative research. In such studies, our data are often derived from one or more cases and it is unlikely that these cases will have been selected on a random basis-Very often a case will be chosen simply because it allows access. Moreover, even if you were able to construct a representative sample of cases, the sample size would be likely to be so large as to preclude the kind of intensive analysis usually preferred in qualitative research (Mason, 1996:91). This gives rise to a problem, familiar to users of quantitative methods:
How do we know ... how representative case study findings are of all members or the population from which the case was selected? (Bryman, 1988:88)
GENERALIZABILITY IN QUALITATIVE RESEARCH
For a few writers who see qualitative research as purely descriptive, gener-alizability is not an issue. For example, Stake refers to the 'intrinsic cast study' where 'this case is of interest ... in all its particularity and ordinariness'
(1994:236). In the intrinsic case study, according to Stake, no attempt is made K, generalize beyond the single case or even to build theories.
This is resisted by many qualitative researchers. As Jennifer Mason puts it:
I do not think qualitative researchers should be satisfied with producing explanations which are idiosyncratic or particular to the limited empirical parameters of Iheir study... Qualitative research should [thereforej produce explanations which are generalizabie in some way, or which have a wider resonance. (1996: 6)
So, unlike Stake, the problem of 'representativeness' is a perennial worry of many qualitative or case study researchers. How do they attempt to address it? Can we generalize from cases to populations without following a purely statistical logic?
In the rest of this chapter, I will discuss four different but positive answers to this question of how we can obtain general inability:
•    combining qualitative research with quantitative measures of populations
•    purposive sampling guided by time and resources
•    theoretical sampling
•    using an analytic model which assumes that generalizability is present in the existence of i«y case.
COMBINING QUALITATIVE RESEARCH WITH QUANTITATIVE MEASURES OF POPULATIONS
Quantitative measures may sometimes be used to infer from one case to a larger population. Hammersley (1992) suggests three methods through which we can attempt to generalize from the analysis of a single case:
•    obtaining information about relevant aspects of the population of cases and comparing our case with them
•    using survey research on a random sample of cases
•    co-ordinating several ethnographic studies.
Hammersley argues that such comparisons with a larger sample may allow us to establish some sense of the representativeness of our single case.
However, two of Hammersley's methods are very ambitious for the student researcher. For instance, you are unlikely to have the funds for even a small piece of survey research, while the co-ordination of several ethnographic studies requires substantial resources of time and personnel as well as good contacts with other researchers. Such contacts allowed Miller and Silverman (1995) to apply the comparative approach in describing talk about troubles in two counselling settings: a British haemophilia centre counselling patients who are HIV-positive, and a family therapy centre in the US. In this study, we focused on similarities in three types of discursive practices in
103
these settings: those concerned with trouble definitions, trouble remedies i   and the social contexts of the clients' troubles (see also Gubrium, 1992).
Without such contacts and resources, the student researcher is left with Hammersley's first method: obtaining information about relevant aspects of the population of cases and comparing our case with them. This is more useful because, at its simplest, this method only involves reading about other cognate studies and comparing our case with them- For instance, in my study of HIV counselling (Silverman, 1997b), I compared my counsellor-client interviews with Heritage and Sefi's (1992) data on interviews between health visitors and first-time mothers. Although this had little to do with establishing the representativeness of my sample, it gave a firmer basis to my generalizations about advice sequences in my data (1997b: 124-8).
The comparative method used here allows you to make larger claims about your analysis without leaving your library. Ás Perákyla puts it;
The comparative approach directly tackles the question of generali zabili ty by demonstrating the similarities and differences across a number of settings. (1997* 214)
In this sense, your literature review (see Chapter IS) has as much to do with the issue of generalizabilily as with displaying your academic credentials.
PURPOSIVE SAMPLING
Before we can contemplate comparing our case with others, we need to have selected our case. Are there any grounds other than convenience or accessibility to guide us in this selection?
Purposive sampling allows us to choose a case because it illustrates some feature or process in which we are interested. However, this does not provide a simple approval to any case we happen to choose. Rather purposive sampling demands that we think critically about the parameters of the population we are interested in and choose our sample case carefully on this basis. As Denzin and Lincoln put it:
Many qualitative researchers employ ... purposive, and not random, sampling methods. They seek out groups, settings and individuals where ... the processes being studied are most likely to occur. (1994: 202)
Stake (1994: 243) gives the example of a study of interactive displays in children's museums. He assumes that you only have resources to study four such museums. How should you proceed?
He suggests setting up a typology which would establish a matrix of museum types as in Table 8.1. The typology yields six cases which could be increased further by, say, distinguishing between museums located in small and big cities - bringing up the cases to twelve, Which cases should you select?
104
SELECTING   A   CASE
TABLE 8.1     A typology of children's museums
Type o( muicum
programme type                                  Art              Science            History
Exhibitor/                                                 I                  2                      3
PcnScipolive_________________________4__________5____________6________^__^
Source: adopted Iron» Stale, 1994: 2/3
You will be constrained by two main factors. First, there may not be examples to fit every cell. Second, your resources will not allow you to research every existing unit. So you have to make a practical decision. For instance, if you can cover only two cases, do you choose two participatory museums in different locations or in different subjects? Or do you compare such a museum with a more conventional exhibit-based museum?
Provided you have thought through the options, it is unlikely that your selection will be criticized. Moreover, as we see below, how you set up your typology and make your choice should be grounded in the theoretical apparatus you are using. Sampling in qualitative research is neither statistical nor purely personal: it is, or should be, theoretically grounded. To improve your understanding of this point, you could now attempt Exercise 8.1.
THEORETICAL SAMPLING
Theoretical and purposive sampling are often treated as synonyms. Indeed, the only difference between the two procedures applies when the 'purpose' behind 'purposive' sampling is not theoretically defined.
Bryman argues that qualitative research follows a theoretical, rather than a statistical, logic: 'the issue should be couched in terms of the generalizabilily of cases to theoretical propositions rather than to populations or universes' (1988: 90, my emphasis).1
The nature of this link between sampling and theory is set out by Jennifer Mason:
theoretical sampling means selecting groups or categories to study on the Oasis of their relevance "> your research questions, your theoretical position ... and most importantly the explanation or account which you are developing. Theoretical sampling is concerned with constructing a sample... which is meaningful theoretically because it builds in certain characteristics or criteria which help to develop and test your theory and explanation. (1996: 93-4)
Theoretical sampling has three features which 1 discuss below:
•    choosing cases in terms of your theory
•    choosing 'deviant' cases
•    changing the size of your sample during the research.
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PANT   TWO         STARTINO    OUT
Choosing eases in terms of your theory
Mason wnli". about 'the wulei nnivrisi-ofsoci.il explanations in relation to which you hflvc constructed your research questions' (1996: 85). This theo] eticiilly defined universe 'will make some sampling choices more sensible .in.l meaningful than others'. Mason describes choosing a kind of sample whit h cm represent a wulei populalioii   1 lere we sele« I a vainplc ot paitu (:
'■"   j'i"i <•'• ■•• ■■ i\ 'pe.s, catei;oru".....x.imples which  ire iclevanl lo or appc,n
wilhin M»- wiilcr universe' (I'Wlt'';'.). Mason suggests lhal examples of these would include single units such a» 'an organization, a location, a document ... [or| a conversation'.
Mason gives the example of a PA study of gender relation as discourses which construct subjects of gender n-lalioas. In this approach, as she puts it: 'you are . .. unlikely to perceive the social world in terms of a large set of gender relations from which you can simply draw a representative sample of people by gender; (1996; 85).
So in qualitative research I he relevant or 'sampleahle' units are often seen as tin.ueliially defined. This means that it is inappropriate lo sample popu la t ions In such attributes as gender', 'ethnicity' or even age because how such attrihuti-s .we routinely defined is itself the topic of your research.
As an example of theoretically defined sampling. Bryinan uses Glaser and :*•■• er.   -. 11 ľ.i h '■:.■:: >,i '.i-.v.n.'i ■ "■    ■ <n(e\ts' in relation lo dyin^ in hospital
The 1M.UC at whether the particular hospital studied t> 'typical' is not the critical issue; what is important is whether the experiences of dying patients are typical ol the broad dm» of phenomena ... to which the theory refer*. Subsequent research would then focus on the validity ol the proposition in other milieux (e.g. doctors' sunjertm) (1988:91)
\\r .m understand better the theoielical logk behind i hoice ol a sample in a further example of a study of police work. Say you are inlerested in llie arrest and booking of suspects (see Miles and Hubernian, 19H: 37-8). You are now confronted with a series of choices which relate lo:
•     Ihe particular selling to he studied
•     Ihe eh tnem i "i proa sse .on " hich you will focus
•     how you might generalize further.
Lcl us look at each of these in turn.
SETJ1NGS
In independent, unfunded research, you are likely to choose any setting
which, while demonstrating the phenomenon in which \.....aie interested, is
acce able ami will provide appropriate data reasonably readily and quickly. In the pol in-study, this might well lead you lo study the police station rather than a squad car, Ihe scene of Ihe crime, the suspect's residence or hangout. In the polk« slation, at the very least, you will keep warm and dry, you will
106
r        r         r        r         t        r         r        t         i        '
SELECTINO   A   CASI
and you can expect several nrresls and bookings on .my visit. r, so far you are being guided by quite practical influences.
E BESEARCM FOCUS
focusing yon i research, you neceSMfily ■•<•' making a thtOIttt .ill v guided oice. By opting to (ocas on particular Individuals, events or processes, you , elect i n>: p.utinilai theoretical framewoiks. ľor instance, a locus on differential behaviour between police officers and suspects with different characteristics may draw on some version of (he structural determinants of action. Conversely, a focus on how law» are interpreted in practice (cf. Sudnow, 1968b), may derive from a concern with the creative power of common-sense interpretive procedures.
GťNHWu7|NC FURIHIB
When your study is wedded to other studies which share your theoretical orientation, a single police station ina\ pio\ uli- enough data In develop .ill (the generali/.ilums you want about, sny, how common-sense rtMOPJng works. However. i( you have a more 'slriieliir.il' bent, it may now be necessary to widen your sample in two ways: first, lo add more observations of arrests in this poli« e station; and second, lo compare it with nlhei stations, perhaps in a range of areas.
In all these case.. Ihe sample is not random bul theoretical: il is
designed to provide I close-up. detailed or meticulous view of particular units which may constitute ... eases which are relevant lo or appear within the wider
universe. (Mason, l*»%:92)
Choosing 'deviant' eases
Mason notes thai you must overcome any tendency to selecí a i ase which is likely toSUppOtl yOUřargument. Instead, il makes sense U> seek out negative instances as defined by the theory with which you are workiny,
For instance, in a study of the tone-, that may make trade unions undemocratic, lipsei et al. (1962) delibei itelv . hose lo study a US printing union. Because Ihls union bad unusually strong democratic Institutions it constituted a vital deviant case compan-d with most American unions of the period. Upset's union was also deviant In terms of a highly respected theory which postulalcd an irresistible tendency towards 'oligarchy' in all formal organizations.
So Lipset el al. chose a deviant case because it offered a crucial lest of a Iheory. As our understanding of social processes improves, we are increasingly able to choose cases on such theoret» al grounds-Changing the she of your sampln during the research
So far we have K-en discussing theoretical nmpung as an i aie at the >larf of a research sludy However, we can also apply such sampling during ihe
107
99
PART   TWO           STARTING    OUT
course of a piece of research. Indeed, one of the strengths of qualitative research design is that it often allows for far greater (theoretically informed) flexibility than in most quantitative research designs, faMason puts it:
Theoretical or purposive sampling is a set oí procedures where the researcher manipulates their analysis, theory, and sampling activities mtfraclively during the research process, to a much greater extent than in statistical sampling. (1996: 100)
Such flexibility may be appropriate in the following cases:
•    As new factors emerge you may want to increase your sample in order to say more about them.
•    You may want to focus on a small part of your sample in early stages, y    using the wider sample for later tests of emerging generalizations.
-»   Unexpected generalizations in the course of data analysis lead you to seek out new deviant cases.
Alasuutari has described this process through using the analogy or an hourglass:
a narrow case-analysis is broadened ... tluough the search (or contrary and parallel cases, into an example of a broader entity. Thus the research process advances, in its final stages, towards a discussion of broader entities. We end up on die bottom of the hourglass. (1995: 156)
Alasuutari (1995: 155) illustrates this hourglass metaphor through his own study of the social consequences of Finnish urbanization in the 1970s. He chose local pubs as a site to observe these effects and eventually focused upon male'regulars'. This led to a second čtudy even more narrowly focused on a group where drinking was heavier and where many of the men were divorced. As he puts it: 'Ethnographic research of this kind is not so much generalization as extrapolation ... the results are related to broader entities' (1995:155).
GENERAUZABILITY AS PRESENT IN A SINGLE CASE
The fourth and final way of thinking about how we generalize in qualitative research is far more radical than our earlier alternatives. According to this approach, since the basic structu res of social order are to be found anywhere, it does not matter where we begin our research. Look at any case and you will find (he same order.
For this linguistically inspired approach, the possibility something exists is enough. As Periikyla suggests:
Social practices that are possible, i.e., possibilities of language use, are the central objects of all conversation analytical eise studies on interaction in particular institutional
loa
1,1                 i.i.i.l.l                 II
SELECTING   A   CASE
settings. The possibility of vanous practices can be considered generalizable even if the practices are not actualized in similar ways across different settings. (1997: 215)
Periikyla illustrates his argument by the example of his own study of AIDS counselling in a London teaching hospital (Periikyla, 1995). This study focused on specific questioning practices used by counsellors and their clients. As he puts it:
As possibilities, the practices that I analyzed are very likely to be generalizable. There is no reason to think that they could not be made possible by any competent inember of (at least any Western) society. In this sense, this study produced generalizable results. The results were not generalizable as descriptions of what other <ounsellors or other professionals do with their clients; but they were generalizable as descriptions of what any counsellor or other professional, with his or her clients, can do, given that he or she lias the same array of interactional competencies as the participants of the AIDS counselling sessions have. (1997:215-16)
As the most cogent proponent of this view once put it: 'tap into whomsoever, wheresoever and we get much the same things' (Sacks, 1984: 22). Sacks had a strategy of working with any data that crossed his path. This clearly conflicts both with the standard approach of quantitative social scientists, who usually work with random samples from particular populations, and with the common defensiveness of their qualitative brethren about the representativeness of the cases that they study.
Sacks's lack of defensiveness on this issue stems from his argument about the obvious pervasiveness of the social forms (or what he calls the 'machinery') with which he is concerned. For example, Sacks notes the ability of a child to learn a culture from very limited contacts and of the sociolinguist Whorf to build a Navajo grammar from talking to just one person (1992, Vol. 1: 485).
The pervasiveness of structures which these examples suggest implies to Sacks that it does not matter what data you select. AS he argues:
Mow if one figures that thafs the way things are... then it really wouldn't matter very much what it is you look at - if you look at it carefully enough. And you may well find that you [have] got an enormous generalizability because things are so arranged that you could get them; given that for a [societal] member encountering a very limited environment, he has to be able to do that, and things are so arranged as to permit him to. (1992, Vol. 1: 4S5)
However, apprentice researchers have to be very cautious about simply parroting Sacks's 'solution' to the problem of the generalizability of research findings. This solution is really only appropriate to the most basic research on social order guided by theoretically sophisticated positions like Sacks's own conversation analytic (CA) approach (or, perhaps, French structuralism). If you are interested in this sort of research, you should now attempt Exercise 8.2.
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PART   TWO           STARTING   OUT
Within CA, following Sacks: i
the baseline assumption is that the results ate or should be ganerallzable to the whole domain of ordinary conversations, and to a certain extent even across linguistic and cultural boundaries. (Perakyla, 1995: 214)
However, Perakyla notes that even this depends on (he type of CA research:
Even though the most primordial conversational practices and structures —such as hirn-taking or adjacency pairs - are almost universal, there are others, such as openings of telephone calls (see Schegloff, 1986; Houtkoop-Steenstra, 1991;
Undsrrom, 1994), which show considerable variation in different cultures. This variation can only be tackled through gradual accumulation of studies on ordinary conversation in different cultures and social milieux. (1995: 214)
H
Perakylä's observation about the need for comparative work shows that even the most potentially radical approach, like CA, has to take seriously the issue of the empirical genera I izabi lily of its findings. Sometimes, an appeal lo 'possibilities' will be sufficient. Often, however, other examples will be required.
CONCLUDING REMARKS
In this chapter, I have set out various strategies which you can use to defend your research against the charge that it 'merely' depends upon a single case. My overall message is that there is usually no need to be defensive about the claims of qualitative research. As Howard Becker argues:
Sampling is a major problem for any kind ot research. We can't study every case ot whatever we're interested in, nor should we want to. Every scientific enterprise tries to find out something thai will apply to a/en/lhing of a certain kind by studying a few example*, (he results of the study being, as we say 'gcnerahzable' to all members of that class of stuff. We need the sample to persuade people that we know something about the whole class. (1998: 67)
Following Becker, sampling troubles quantitative researchers too. Indeed, as we have seen, the relative flexibility of qualitative research can improve the gcneralizability of our findings by allowing us to include new cases after initial findings are achieved.
The crucial issue here seems to be thinking through one's theoretical priorities. Providing that you have done that and can demonstrate a research design driven by those priorities, nobody should have cause for complaint.
So the secret seems to be to substitute theoretical cogency for the statistical language of quantitative research. In this sense, as Alasuutari has suggested, perhaps 'generalizability' is the wrong word to describe what we attempt to achieve in qualitative research. As he puts it:
110
SELECTING   A   CASE
Generalization is ... la| word ... that should be reserved for surveys only. What-can be analyzed instead is how the researcher demonstrates that the analysis relates to tilings beyond the material at hand ... extrapolation better captures the typical procedure in qualitative research. {1995: 156-7)
SUMMARY
In this chapter, I have discussed four positive answers to the question of how we can generalize from qualitative data:
•    combining qualitative research with quantitative measures of populations
•     purposive sampling guided by time and resources
•     theoretical sampling
•     using an analytic model which assumes that generalizability is present in the existence of any case.
NOTE
1 As Clive Scale (personal correspondence) has pointed out, theoretical sampling may have more to do with generating theories than with empirical generalization. 1 take up Scale's point at the end of this chapter in relation to Alasuutari's argument that the idea of empirical generalization 'should be reserved for survevs only' (1995:156).
Further reading
The most thorough book on this topic is Clive Seale's The Quality of Qualitative Research (Sage, 1999).
Other useful discussions are: Jennifer Mason, Qualitative Researching (Sage, 1996), Chapters 5-7; Pertti Alasuutari, Researching Culture (Sage, 1995), Chapter 12 'Generalization'; and Howard Becker, Tricks of the Trade (University of Chicago Press, 1998) Chapter 3 'Sampling'.
Robert Stake's chapter 'Case studies' is a good account of the conventional qualitative methods position on generalizability (in N. Denzin and Y. Lincoln (eds). Handbook of Qualitative Research. Sage, 1994). Anssi Peräkylä's chapter 'Reliability and validity in research based upon transcripts' is an excellent, more specialist treatment (in David Silverman (ed.). Qualitative Research, Sage, 1997).
Ill
PART    TWO           STARTING   OUT
Exercise 8.1
Imagine thai you havo the resources lo sludy four cases of the phenomenon in which you ar<i interested. Following my discussion ol Slako (1994; see Table 8.1 J, draw up a lypology lo indicate the universe of cases potentially available. This typology should include botwocn six and twelve possible cases.
Now explain why you propose to select your four cases in terms of the logic of purposive sampling.
Exercise 8.2
Using conversation analysis, Harvey Sacks lias argued: 'tap into whomsoever, wherosoevor and wo got much tho same things' (1984: 22).
Consider how far your own theoretical model might allow you to use Sacks's argument to justify working with a very small dataset.
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í
9
Writing a Research Proposal
According to Janice Morse (1994), qualitative research is difficult to sell to funding agencies. This is because:
•    Qualitative research is unstructured.
•    The results of qualitative research are unpredictable.
•    The outcome is uncertain (1994: 227).
How, then, can one convince fundcrs to support a piece of qualitative research? Or a potential university supervisor to support your research proposal?
To answer these questions satisfactorily means shifting away from your own concerns and thinking about the questions that the rcader(s) of your research proposal will be asking. Many of these questions are set out in Table 9.1.
TABLE 9.1     Questions o research proposal must answer
1    Why should onyone be mreresled in my research?
2    Is the research design credible, achievable ond carefully explained?
3    Is the resoccher capable o( doing the research?
Source: adapted from Marshall and Rossntan, 1 °89: 23
How can you properly (and successfully) answer these questions?
•    He practical
•    Be persuasive
•    Make broader links
•    Aim for crystal clarity
•    Plan before you write.
Each of these suggestions are explained below.
BE PRACTICAL
One way to persuade non-specialists, Morse suggests, is to show the specific ways that your research can address a social problem or solve an organizational trouble (e.g. staff turnover).
PART     TWO             STARTINO     OUT
Such a concern with practical problems cannot be shrugged off even if you are proposing to do a purely academic piece of research with no expectation that it will be read outside Ihe university. Academic funding bodies are increasingly demanding practical pay-offs as well as analytic insights. For instance, Kelly (1998:112) quotes a policy statement by the body thai funds social science PhDs in the UK:
Any lingering public perception of social science as a source of irrelevant, introverted and incoherent output is set 'or radical alteration ... In future, research which makes a difference lo the heallh and wealth of Ute population, rather than merely supports 'ivory lower' academic excellence, will be (he ESRC's priority. (Student Information: Economic and Social Research Council, 1996)
The issue of audiences for your research is discussed further in Chapter 24. However, if what you are proposing is *basic research', i.e. a study deriving from debates and concepts internal to social science, then all is not lost. You can strengthen the persuasiveness of your case by showing non-specialists why they ought to lake your ideas seriously. One way to do that is to write a persuasive proposal as explained below.
BE PERSUASIVE
ll is easy to gel very wrapped up in the subject and think thai, because we are convinced of the particular value of <>ur research, others will be too. The way in which the proposal is presented can enable the reader to appreciate what you are planning to do. (Kelly, 1998: 121)
Kelly is reminding us that, in framing a research proposal, one must think first of the audience who is going to read it (and judge it). This means that it should set out to convince such readers that this is something worlh supporting:
The first principle of granlsmanship is to recognize that a good proposal is an argument... for the researcher's project. The proposal must make a case to the granting agency that the research question is interesting [and] that the study is important... Thus the proposal must be written persuasively. (Morse: 1994: 226)
Morse is suggesting that you try to 'sell' your proposal. This means that you must recognize that the craft of selling (your proposal, yourself) is not incongruent with working in a university. 'Ivory towers' were never so isolated as the term suggests!
However, this persuasiveness must be balanced with a realistic understanding about what you can achieve within a few years as a single researcher. Like any good salesperson, do not oversell your goods!
MAKE BROADER LINKS
Realism need not mean that you must present your research as entirely a narrow, anaemic exercise. Even if you cannot cover every aspect of the field
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^___________■■■■■
WRITING     A     RE3CARCH     P R •.'■' I* '-' - A i
yourself, you should demonstrate your understanding of the broader implications of your proposed research. One way to do that is to hint at a wider context:
place the problem in context to show, for instance, that 'when we understand this, we will be able to work on that'. (Morse. 1994: 227)
Of course, you will be studying very few cases or maybe only a single case. De positive about the gains as well as Ihe losses of this! Show how a relatively small database will enable you to conduct an in-depth analysis (see Chapters 8 and 13). And argue that your case can indicate far larger phenomena:
The writer must show how, in examining a specific setting or group of individuals, she is studying a case of a larger phenomenon. (Marshall and Rossman, 1989:12)
AIM FOR CRYSTAL CLARITY
The proposal should use language and terminology that is understandable to an intelligent lay person as well as to a subject expert. (Cryer, 1996:15)
Although it is tempting to seek to display your newly acquired technical jargon, bear in mind that your proposal is likely to be read, in the first instance, by a faculty member who is not a specialisl in your area of the discipline. So never be content with a proposal which can look like a siream of (perhaps undigested) theories or concepts. Always aim for clear language that describes your research in a way lhal non-specialists can comprehend.
As Morse suggests, this means that you should resist the temptation lo lapse into pure jargon: 'because some of Ihe reviewers will be from other disciplines., the proposal writer should assume nothing and explain everything' (Morse, 1994: 227).
By explaining everything, you will have demonstrated the ability to think (and write) clearly. Not only is this the way to write a research proposal, it is also the best indicator that your research itself will be organized in a clear and logical way:
A sloppily prepared proposal will, at best, send a message to the agency thai if it funds the proposal, the research may also be sloppy. (1994: 226-7)
For inslance, your objectives 'should be clear and il shottld be easy to decide whether they have been achieved or not' (Kelly, 1998: 117). The ways to achieve this are:
•    De concise (there is no reason why a proposal for a piece of student research should be more lhan 500 words).
•    Use short, simple sentences.
•    Use headings as in Table 9.2.
lis
TABLE 9 2    A Structure tor a Qualitative Research PropoKÜ
•      1    TüW
2    Abstfoct (runner advice on tirlei oitd abwrods is found in Cnopler 17)
3    ßoekflround or introduction: e.y. contemporary debates in social policy and social science
4    Statement of purpose or aims: trie research question (The inleltocruol problernls) I may help ion* *fowah Ais research h (oreí      '|
5    Review of *»• relevant literatúre: showing »st importance of the pro|ect h the context of (he classic or definitivo pieces of research in 'his area
ó    Methods: description of casofsl chosen, procedures for dalo collection and data analysis in terms of (a) their appropriateness to you' theoretical orienfabon ond (b) how they satisfy criteria of voiio% and reliobifay [see Choosers 7 and 13)
7    Flr.tr.al Issues (see Chapter 15)
B    Disiemlnotion ond policy rolovonce: explain how you will communicate yowr findings (see Choplers 16 and 24)
9    Timetable: indicating the length of time to be devoted to each stage of the research 10    Befarences «se a sterdord system Lie ** Morvord system '
1 Harvord svstom in the main body of your text (not in footnotes), give surname of author, followed by dole ana nago reference In your references, give author (with initials), dale, title, ploco of publication, publisher and page references (for artldes or chapters) Source adapted from AAorse, 199* 228. Kelly, 1998: 115-21; RuoWam and New**. 1992: 18
PLAN BEFORE YOU WRITE
The wnter must show thai tlw design Is the result oi a «era» of decisions that she made because or knowledge gained from Ihe... literature. (Marshall and Rossman,
1069i 13)
Not only mtist the proposal demonstrate that it is based on an intelligent understanding of the existing literature, it must show that you have thought about the time you will need to conduct each stage of the research from obtaining access to writing up your data analysis- So, as Sara Arber notes, your research proposal will partly be judged by how you state you are going to use your time:
You need to adopt a systematic and logical approach to research, Ihe key to which b the planning and management of your time. (1993:33)
Kelly (1998: 120-1, adapted here) niters an example from an interview study planned to last 32 weeks:
Week 2     Submit proposal to University Ethical Committee.
Week 6     Draw up sample.
Week H     Begin interviews.
VVeek 15    Kml interviews.
Week 23   Complete data analysis.
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Week 26   first draft sent out for comments. Week 32   Submission of final report.
We are not born with a natural ability to prepare research timetables! To help you plan such a timetable, seek the assistance of a trusted teacher in your department. Failing that, seek out an existing research student. With their help, make a list of all the options available in relation to your research problem, method and casefs) to be studied. Now you are in a better position to write a reasoned research proposal that explains the actual choices you have made
Table 9.2 provides a model structure for such a proposal. When you have read it, you should attempt Exercise 9,1.
SUMMARY
When preparing a research proposal, try to find answers to Ihrer questions;
1    Why should anyone be interested in my research?
2    Is the research design credible, achievable and carefully explained?
3    Is the researcher capable of doing the research?
You can answer these questions better by fol lowing five principles:
•    Be practical
•    Be persuasive
•    Make broader links
•    Aim for crystal clarity
•    Plan before you write.
Further reading
A research proposal is crafted according to the level of your research. Beginning researchers should turn to: Moira Kelly, V/ritíng a reseorch proposal', inC. Seole{ed.J, Researching Society and Culture [%oge, 1998), pp. 111-22.
At PhD level, a useful reference is: Pat Cryor, The Research Stvdenťs Guide to Success (Open University Press, 1996), Chopter 2.
Beyond ihe PhD, you should consult: Janice Morse 'Designing funded qualitative research', in N. Denzin and Y. Lincoln (eds), Handbook of Qualitative Research (Soge, 1994), pp. 220-35.
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