Candidate recruitment

LGC Elections Centre, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK b

Department of Geographical Sciences, University of Bristol, Bristol, UK Received 4 April 2007; revised 9 November 2007; accepted 10 November 2007

Keywords: Electoral bias; Electoral geography; Third parties

Corresponding author. Tel.: þ44 (0)1752 232619; fax: þ44

(0)1752 232785.

E-mail addresses:[email protected](G. Borisyuk),

[email protected] (R. Johnston), mthrasher@plymouth. ac.uk(M. Thrasher),[email protected](C. Rallings).

Electoral Studies 27 (2008) 245e256

www.elsevier.com/locate/electstud

Although most of my work has been undertaken while using aggregate data there are

some recent exceptions. In 2006, Mary Shears of the Elections Centre introduced a

national survey of local election candidates. The survey has been conducted annually

since then with candidates selected randomly from nomination lists and invited to

participate. About one thousand responses are collected each year and I have pooled

these data noting where the same or similar questions have been asked. I have also

combined the individual-level data with ward and authority-level measures and

weighting data to correct for response bias (see Appendix 13 for a more detailed

description of this procedure).

Two recent publications are included here (Appendices 12 & 13) that reflects the kind

of research that is being undertaken with these data. I noted earlier (Appendix 8) that

the aggregate data analysis of women‟s under-representation in local government could

only advance our knowledge to a certain extent. Appendix 12 aims to take the analysis

a step further by, inter alia, discovering from women candidates some of the processes

that brought them to stand, the support they received from others and whether their

experiences were different to those of men. It appears that women are less likely than

men to take the decision to stand; they are more likely to be asked to stand. By contrast,

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the relatively small group of non-white candidates and those aged below 45 years that

stand are more likely to make their own decision (Appendix 12, pp. 231-3). As far as

the candidates are concerned the problems of under-recruitment lie mainly with supply-

side issues coupled with a feeling that local parties might be doing more to select

members of these under-represented groups.

For the paper examining ethnic candidates in local elections (Appendix 13) we again

collaborated with Richard Webber, using his OriginInfo software to identify candidate

ethnicity. This was partly to test his software reliability and partly to consider the

nature and extent of sample/response bias for the Local Candidate surveys. The first

part of the paper, therefore, (Appendix 13, pp. 247-8) uses the software to classify the

ethnic origins of all candidates standing for election. Next, we compare the list

selected to be invited to complete a questionnaire with all candidates in order to

measure any sample bias. Because we use random sampling we were reasonably

confident that such bias would be avoided and we were correct in this interpretation.

The next procedure was to test for response bias by comparing the list of candidates

that did or did not respond. This provided evidence of response bias with a lower

response rate from Black, Asian and other minority ethnic candidates. The subsequent

analysis was able to correct for this bias.

BME candidates are more likely to be younger and better educated but fewer women

are recruited from among this group. Such candidates are electorally inexperienced,

have stronger ties with community related organisations and are more likely to make

their own decision to stand for election rather than being approached by a fellow party

member. Community ties are also evident when respondents are asked about their

experiencing positive support from this quarter (Appendix 13, pp. 256-7).

General Discussion

These research papers seek to expand our understanding about voters and parties in

Britain. Generally speaking, the research has relied upon aggregate data (especially

local and parliamentary election data) but in recent years I have been working

extensively with survey-level data also. These different types of data present rather

separate challenges. One continuing task with the aggregate data is to check for errors

and inconsistencies and, where possible, to amend the original records. When the

number of candidates and elections numbers in the many thousands as happens with the

local elections this can be a daunting task, particularly when the contests occurred

decades ago. One major task has been the treatment of missing data. For example, one

important piece of information that local authorities often failed to record was the

number of ballot paper issued for elections to multimember wards. This was handled

by an algorithm that took account of various patterns of party competition. A similar

approach was used for the electoral forecasting model when local parties began to

withdraw candidates from these contests (see Appendix 7) and in weighting opinion

poll data when the frequency of polls began to vary widely.

The survey data present different kinds of problems as anyone who has worked with

these types of data can attest. In one sense, however, our recent work has transformed

this „necessary chore‟ into a research programme in its own right. Recent papers that

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have used the annual candidates‟ survey have described the methodological innovations

that we have developed to measure any sampling bias and, more importantly perhaps,

the nature and extent of response bias. These papers have also united the aggregate and

individual-level data analysis because we are extending our application of name

recognition software from the survey to the aggregate data in order to explore the

relationship between candidate ethnicity and patterns of vote distributions.

Facing and solving challenges in the research process often leads to methodological

innovations that were not planned but instead evolved. The papers included in the first

section on electoral bias, for example, provide a useful description of this process. It

began with an initial discussion about the limitations of the Brookes method for

three party competition in Britain and the need to search for a more effective approach

to decomposing bias. One of the papers included here is rare amongst academic

publications – a description of a research process that ultimately failed. But the failure

led us to reassess our original thinking and then to develop a successful methodology.

In turn, that methodology was then applied and has hopefully expanded our

understanding of the operation of the different bias components at UK general elections

from 1983 onwards.