Bibliographic record
Abstract
Canadian party politics collapsed in the early 1990s. This book is about that collapse, about the end of a party system, with a unique pattern of party organization and competition, that had governed Canada's national politics for several decades, and about the ongoing struggle to build its successor. Rebuilding Canadian Party Politics discusses the breakdown of the old party system, the emergence of the Reform Party and the Bloc Qu�b�cois, and the fate of the Conservative and New Democratic Parties. It focuses on the internal workings of parties in this new era, examining the role of professionals, new technologies, and local activists. To understand the ambiguities of our current party system, the authors attended local and national party meetings, nomination and leadership meetings, and campaign kick-off rallies. They visited local campaign offices to observe the parties' grassroots operations and conducted interviews with senior party officials, pollsters, media and advertising specialists, and leader-tour directors. Written in a lively and accessible style, this book will interest students of party politics and Canadian political history, as well as general readers eager to make sense of the changes reshaping national politics today.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.030 | 0.008 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".