Sour Grapes? Party Donors and Canadian Leadership Primaries
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
Abstract Political parties around the world are adopting primaries to select leaders and legislative candidates. While a large, though inconclusive, literature has emerged in the American context to explore the consequences of primaries, little attention has been devoted to other national contexts. Exploring patterns of financial donation, this study examines whether individuals who supported a losing leadership candidate are less likely to exhibit subsequent financial commitment to the party compared to those donors whose preferred candidate won the internal election. Drawing upon a novel dataset that includes tens of thousands of donors to recent leadership elections in Canada, we demonstrate that intra-party winners (i.e. those who supported the winning leadership candidate) are more likely to be financially committed to the party in the year after the election than those who supported losers. Results suggest that open and inclusive elections, while participatory in nature, may come at a cost for political parties as losers withdraw from the party in the wake of their loss.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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