Bibliographic record
Abstract
However, when probing below the surface of these celebratory results, one discovers a very large number of paradoxical and disquieting fault lines that hardly find any echo in the overall tone of the survey results, and that would appear to be systematically kept out of Canadians’ consciousness: the largest yet recorded cleavage between Quebecers (34%) and other Canadians (83%) expressing a sense of pride in being Canadian; boasting confidence in the health care system, despite a large number of serious studies pointing to an imminent crisis situation – and consequently considerable reluctance in the citizenry to agree to any sort of fundamental reform; a similar schizophrenia and denial that any change is required in the face of the impending pension crisis; paradoxical support for the current high level of immigration concomitant with high and increasing concern that immigrants integrate less and less well economically, and do not adopt Canadian mores, etc. On all these fronts (and there are many more) there is a certain culture of contentment, and even when significant concerns break through the citizen’s denial system, and are reluctantly acknowledged, it would appear that they never trigger any commitment to significant correctives. Contentment and inertia prevail.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.025 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.010 | 0.017 |
| Insufficient payload (model declined to judge) | 0.015 | 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".