Bibliographic record
Abstract
Citizenship is more than a passport. It defines who “we Canadians ” are, and describes the kind of community “we ” wish to become. Citizens have rights, they have responsibilities, and they need access to jobs, services, and supports. The balance among these rights and responsibilities changes over time in response to the core values of citizens, their implicit contract with the state, and the economic and political context. This REFLEXION focuses on the key economic and social choices that will shape our common citizenship in coming years. During the post-war years, Canadians forged a common citizenship out of their experiences with the Depression and the Second World War, with the help of a prolonged economic expansion. During that time, standards of living increased, a broad middle class emerged, and social programs such as medicare were established. A strong synergy was created between economic and social policy. However, this progress was interrupted in the 1970s by a downward shift in the rate of economic growth. As economic problems mounted, new ideas about the roles of the state and of markets took hold. For the past 20 years, Canada has rolled back layers of institutions and protections central to the post-war model of citizenship. Driven
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.069 | 0.017 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".