The Life and Death of an Issue: Canadian Political Science and Quebec Politics
Bibliographic record
Abstract
Abstract How has English-speaking Canadian political science conceived of the relationship between Quebec and Canada? Why has an issue that has been considered central for more than three decades become less attractive, if not marginal, within the discipline? The aim is to examine, from this example, the overlapping relationship between science and politics. The intent is also to show that Canadian political science has examined the Quebec/Canada relationship from four different angles: 1) its interest in Quebec politics was part of the urgency of the moment, based on a crisis that challenged the foundations of the political system; 2) it questioned the legitimacy of the sources of the dispute, namely the compatibility between the new expressions of Quebec nationalism with the presumed principles on which the Canadian political community had been founded; 3) Quebec nationalism also encouraged a reflection on the existence (or not) of “English Canada” as a sociological and political reality; 4) the combination of the first three factors caused the prescriptions for getting out of, or resolving, the crisis to evolve over time, to the point of rendering research on this issue obsolete.
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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.036 | 0.015 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 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 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".