Canadian Gallup Poll, November 1985, #503_1
Bibliographic record
Abstract
This Gallup poll seeks the opinions of Canadians, on both political and social issues. The questions ask opinions about political leaders and political issues within the country. There are also questions on other topics of interest and importance to the country and government, such as the standard of living, the sale of wine and predictions for 1986. The respondents were also asked questions so that they could be grouped according to geographical variables. Topics of interest include: Achille Lauro ship episode; approval of what Greenpeace does; attending church; the biggest threat to Canada in the future; the chances of a world war in the next 10 years; changing the standard of living; the effects of regional differences on Canada; effects of the Tuna Fish issue; the Federal government's handling of the Tuna Fish issue; the hours of sports watched on TV per week; justification of the U.S. act against terrorism; knowledge of Greenpeace; the political leader that would make the best Prime Minister; predictions for 1986; the sale of beer in the province; the sale of wine in the province; the satisfaction with the direction of the country; and watching the Toronto Blue Jays in the MLB playoffs. Basic demographics 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 | 0.008 | 0.019 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.054 | 0.049 |
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".