Provincial Battles, National Prize?
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
In parliamentary systems like Canada, voters directly contribute to the election outcome only in their own riding. However, the focus of election campaigns is often national, emphasizing the leader rather than the local candidate, and national rather than regional polls. This suggests that elections are national contests, but election outcomes clearly demonstrate that support for parties varies strongly by province. Focusing on the 2015 Canadian election campaigns in British Columbia, Ontario, and Quebec, three large provinces with different subnational party systems, Provincial Battles, National Prize? evaluates whether we should understand elections in Canada as national wars or individual provincial clashes. The authors draw upon voter and candidate surveys, party campaign behaviour, and media coverage of the election to document how political parties vary their messages and strategies across provinces, how the media communicate and frame those messages, and how voters ultimately respond. The study shows that provincial variations in party support reflect differences in voters' political preferences rather than differences in party messages or media coverage. A novel and comprehensive study, Provincial Battles, National Prize? is the first and only thorough treatment of the party, media, and voter aspects of a federal election campaign through a subnational lens.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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