Les élections provinciales dans le Québec
Bibliographic record
Abstract
This essay on electoral geography, the first, perhaps, to be published in Canada, is divided into four distinct parts. The first one deals with the themes of the twenty five provincial electoral campaigns. It includes maps showing the results of the votation in every county of the Province, as divided between the two main political parties, the Liberal and the Conservative. The second part, almost exclusively graphic, examines the political attitude of every provincial county. To circumvent the various problems, graphic curves have been established, indicating the percentage of the liberal and conservative voters and of the nonvoters. In a third part, some aspects of a very particular electoral phenomenon, abstention, are studied. After all possible causes of error had been discarded, a nonvoter curve was obtained, which is used, in particular, to study the fluctuations of the parties. Finally, the influence of the rural vote, a basic element in a long life ministerial party, the geographical distribution of the parties and its evolution within the regions according to certain causes v.g. economic crises, and the Québec electoral System, in relation to the vote and to the parties, are analyzed in a last part about the conditions of political life in the Province of Québec.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.001 |
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".