Does the Local Candidate Matter? Candidate Effects in the Canadian Election of 2000
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article ascertains the impact of local candidates on vote choice in the 2000 Canadian election. The authors show that 44 per cent of Canadian voters formed a preference for a local candidate and that this preference had an effect on vote choice independent of how people felt about the parties and the leaders. The findings suggest that the local candidate was a decisive consideration for 5 per cent of Canadian voters, 6 per cent outside Quebec and 2 per cent in Quebec. Although preference for a local candidate had a similar effect on urban and rural voters, as well as on voters of varying degrees of sophistication, the findings revealed that rural voters and more sophisticated voters were more likely to have formed a preference for their local candidate. As a consequence, the local candidate was more likely to be a decisive consideration for more sophisticated rural voters.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it