Bibliographic record
Abstract
Many Canadian parties are shifting their process for selecting leaders from delegate conventions to methods that -- at least in theory -- allow all members to vote for the leader. In the leadership selections of the 1990s, Alberta’s governing Conservatives used a primary balloting system, the opposition Liberal Party allowed members to vote by phone, and the NDP held a traditional leadership convention. In Quasi-Democracy? David Stewart and Keith Archer examine political parties and leadership selection in Alberta using mail-back surveys administered to voters who participated in the Conservative, Liberal, and NDP leadership conventions elections of the 1990s. Leadership selection events, they contend, provide rare opportunities for observing the internal workings of the parties and people who “stand between the politicians and the electorate.” Using participant accounts and material from the press media, the authors analyze the factors that influence leadership selection in each party, develop attitudinal profiles of the supporters of the parties, and examine the party activists with respect to their backgrounds in provincial and federal politics. Quasi-Democracy ? will be invaluable reading for students and scholars of party democracy and representation, and for those interested in the intricate machinations of the political process in Alberta.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".