Parties, Candidates and Citizens On-Line - Åbo Akademi

Notes
1 Source: http://www.nua.com/surveys/how_many_online/europe.html, accessed September 2004.
2 The comparison figure (d’Hondt) is calculated based on the party’s total number of votes in each district.
The candidate who ranks number one in votes within the party receives the party’s total votes as his/her
comparison figure. The second in rank receives the party’s total divided by two as his/her comparison
figure, etc. In each district a fixed number of seats, based upon the population in the district, are “up for
grabs”. The candidates of all parties are ranked according to their comparison figures and those ranking
above the district’s margin for election are elected.
3 Source: the election website of the Finnish ministry of justice: www.vaalit.fi, accessed September 2004.
4 In all, 734 of these websites were located on independent URL-domains. Moreover, 96 candidate sites
were linked to from the party’s websites and located under the party’s domain. A total of 40 incumbent
MPs linked their campaign site from their section on the parliament’s official site. Candidates receiving a
brief presentation in the election section on their party’s website were excluded from the sample.
5 The election website of the Finnish Ministry of Justice (www.vaalit.fi) and the website of Statistics
Finland (www.stat.fi) proved useful in determining the independent variables. Many thanks to Ph.D. Tom
Carlson who collected the data required for most of the independent variables.
6 Changes made were mainly done in order to bring the scheme up-to-date. Moreover, some of the
dichotomous variables were changed into counts in order to better capture differences between candidate
sites.
7 As several coders were involved in the content coding, inter-coder reliability was checked according to
the formula suggested by Holsti (1969: 140), resulting in a very satisfactory average reliability of R=.89.
Many thanks to the students who assisted in the content coding.
8Unfortunately, as candidate education and SES could not be established for a large enough census of
candidates, the two variables were excluded from the model in Table 2.
9 Initial tests revealed strong correlations (average r=.809) between the district’s average degree of
urbanization and other constituency level demographical variables (age- and educational structure). As
including all three variables had an adverse effect on the regression model’s explanatory power, the degree
of urbanization was chosen as a single indicator for constituency demographics.
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