Public Opinion on Federalism in Canada, Mexico, and the United States in 2003
Bibliographic record
Abstract
This research reports on public opinion surveys on intergovernmental and federal issues conducted in Canada, Mexico, and the United States in March and April 2003. In all three countries, respondents most often see their federal government as being the least effective, least efficient, and least trustworthy. Respondents from Canada appear least supportive of their federal government and most supportive of their local governments; those from Mexico appear most supportive of their state governments; respondents from the United States appear more “balanced” in their support of the various orders of government. Also, far greater regional differences in opinion exist in Canada than in Mexico or the United States. Support for more decentralized federalism is found to be strong in all these federal countries. This research also updates long-term trend data for the United States. Compared with respondents from previous years, U.S. respondents in 2003 showed a measurable uplick in support for the federal government, compared with state and local governments. This support seems to be a carryover from the terrorist attacks of 11 September 2001.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".