The Quick Count and Election Observation

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THE QUICK COUNT AND ELECTION OBSERVATION The application of the principles of question design can be most easily illustrated by working through an example: 91 Suppose observers want to know whether polling stations opened on time on election day. One possibility is to simply construct a question as in version A. Version A: “Did the polling station you were observing open on time on election morning?” "Yes "No But there are several problems with this wording of the question. First, observers will almost certainly have in their minds different ideas about just when a polling station is in fact “open.” Is a polling station “open” when the election officials are all present? Is it “open” when all of the election officials and party agents are present and after all of the materials have been set out? Or, is a polling station “open” at the moment that the first voter casts their ballot? Moreover, we need to be very clear about what “on time” means? If a polling station is supposed to be “open” at 6:00 am and the first voter casts a ballot at 6:25, has the polling station actually “opened on time?” Variations in how these concepts are understood pose problems of validity and reliability. If observers have in mind different views about what “on time” means, and it is left up to observers to decide what “on time” means, then the observers will produce unreliable measures. Version B of the same question is both a more valid and more reliable way to ask the very same question. Version B: “When did the first voter cast a ballot at the polling station?” "Before 7:00 "Between 7:00 and 8:00 "After 8:00 "Did not open This particular version of the question has several advantages: • First, this question wording reduces any ambiguity about the question of when a polling station actually “opens,” and it provides a clear guideline to observers for what qualifies as “on time.” There is no conceptual ambiguity, and so there is vailidity. • Second, because the response categories are varied across time, analysts can examine the distribution of “opening times” that will reveal the scale and scope of administration problems in getting polling stations “open.“ These categories allow responses to vary in meaningful ways; the “usefulness test” is satisfied. Also, the measurement categories are clear; there is no room for observers to provide their own interpretation of what is “late” or “early.” Consequently, the measurement will be reliable. Note too that the response categories in version B of the question satisfy both of the measurement rules: the categories are exhaustive and mutually exclusive.
CHAPTER SIX: THE QUALITATIVE COMPONENT OF THE QUICK COUNT 92 • Third, this version of the question also supplies us with an important additional piece of information; it tells us which polling stations did not open at all. There is a caveat to the above example: The concern about late opening of polling stations is not simply a guage of administrative organization. It is also an indicator of whether prospective voters had a genuine opportunity to vote. Late openings do not measure whether anyone was disenfranchised as a consequence of the problem. An observer outside the polling station determining how many people left lines due to long waits might better measure that. Even that indicator does not address whether those persons returned later. These are the types of issues to discuss when designing an observation and its forms. ANALYZING QUALITATIVE DATA Analyzing data within very short time constraints is no easy task. Data analysts usually have to begin to prepare for the job well in advance of election day by: • gathering contextual information; • developing a clear election-day plan; • creating a software “shell” for the presentation of graphics; and • establishing a working protocol for management of results produced by the analysis team. Typically, the most useful contextual data to gather are those from previous elections (when available). Pre-Election Preparation During the run-up to elections, analysts gather different kinds of contextual information that will help them to interpret the qualitative data. Contextual Data Typically, the most useful contextual data to gather are those from previous elections (when available), especially from the election immediately preceding the present observation. For example, consider the case of voter turnout. Voter turnout indicates levels of citizen participation on election day and citizen participation is an important measure of the health of an election process. But how do you know if voter turnout is “high” or “unusually low?” At least two kinds of benchmarks are helpful for making these kinds of evaluations. The most obvious benchmark comes from documentation of the recent electoral history of the country. Was voter turnout in the present election “unusually low” when compared with levels of voter turnout in the previous election, or with other national elections in the recent past? International benchmark comparisons might also be helpful, but these comparisons have to be made cautiously because electoral rules have significant effects on levels of voter turnout. Voter turnout is typically systematically higher in countries using proportional representation than in majoritarian electoral systems. Any international comparisons have to take such factors as electoral rules into account. Prior
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A P P E N D I C E S 144 WORK PLAN F
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A P P E N D I C E S 146 APPENDIX 3A
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A P P E N D I C E S 148 EXAMPLE OF
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A P P E N D I C E S 150 APPENDIX 3C
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A P P E N D I C E S 152 APPENDIX 3D
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A P P E N D I C E S 154 APPENDIX 4
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A P P E N D I C E S 162 DIAGRAM OF
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A P P E N D I C E S 164 SAMPLE OBSE
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A P P E N D I C E S 166 EXAMPLE OF
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A P P E N D I C E S 168 the polling
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A P P E N D I C E S 170 How to Cond
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A P P E N D I C E S 172 SAMPLE OBSE
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A P P E N D I C E S 174 APPENDIX 9B
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A P P E N D I C E S 176 MALAWI DATA
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A P P E N D I C E S 178 PROMOTIONAL
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