Canadian Gallup Poll, May 1983, #473_1
Bibliographic record
Abstract
This Gallup poll seeks the opinions of Canadians, on both political and social issues. The questions ask opinions about what decisions the Prime Minsiter should make and other political issues within the country, such as separatism. There are also questions on other topics of interest and importance to the country and government, including the price of food and drunk drivers. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: attending church; the church's involvement in politics; directing the country towards socialism; the effects of confederation on regions in Canada; the effect of free trade on Canada; the ideal number of children a family should have; the price of food; sending drunk drivers to jail; the strength of separatism in Quebec; the treatment of Aboriginals by the government; whether or not the Prime Minister should encourage courts to be tough on law breakers; whether or not the Prime Minister should encourage foregin investment; whether or not the Prime Minister should expand social welfare; and whether or not the Prime Minister should reduce government spending. Basic demographic variables are also included.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.025 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.065 | 0.047 |
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".