Financing Federal Nomination Contests in Canada – An Overview of the 2004 Experience
Bibliographic record
Abstract
The passage of Bill C-24 brought sweeping changes to the financing of party leadership, candidate nomination, and election contests. Many of these changes were implemented for the first time in the context of the 2004 federal election. We take advantage of the extensive financial data on contributions and expenditures associated with nomination campaigns collected by Elections Canada during the lead-up to the 2004 campaign in order to provide the first definitive and exhaustive depiction of this “secret garden” of Canada’s parties. Because of the fragmentary nature of existing evidence on nomination contests in Canada, we engage in an exploratory analysis of the spending in pursuit of a party’s nomination. We identify significant party and gender differences in the experience of nomination spending. We also ask whether intra-party conflict in the nomination process is associated with any electoral consequence in the subsequent campaign. In this respect, only the Conservatives appear to have been electorally punished when their candidates had to survive nomination contests. We think this likely reflects a local expression of the acrimony associated with the merger that produced this party in 2003. More generally, then, we conclude that the internal conflict associated with nomination contests does not generally threaten (or, for that matter, invigorate) local party associations. Apart from some growing pains as candidates adjust to the new regulatory regime, the provisions introduced in Bill C-24 have worked well in their first
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.029 | 0.006 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".