Canadian Gallup Poll, January 1980, #433a
Bibliographic record
Abstract
This Gallup poll seeks the opinions of Canadians, on predominantly political issues. The questions ask opinions about political leaders and other political issues within the country such as which party would be best suited to handle various problems and defeating budget proposals in the House of Commons. There are also questions on other topics of interest and importance to the country and government, such as unemployment and inflation. The respondents were also asked questions so that they could be grouped according to geographic and social variables. Topics of interest include: the best party to handle energy issues; the best party to handle inflation; the best party to handle unemployment; the best party to keep the country together; the biggest threat to Canada in the future; defeating budget proposals in the House of Commons; fighting inflation; interest in the upcoming Federal election; levels of satisfaction with Prime Minister Clark; married women who work; opinions about Broadbent as the leader of the NDP; opinions about Trudeau as the Liberal party leader; overthrowing the government; problems facing Canada; Quebec separation; Sovereignty-association for Quebec; and who would make the best Prime Minister. 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 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.021 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.045 | 0.035 |
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".