Census of Population, 1991 [Canada]: Profile Series, Part B [Long form] [B2020]
Bibliographic record
Abstract
The enumeration area (EA), as the basic geographical unit of census data collection, is the smallest standard geographic area for which census data are normally available. All Standard geographic areas are composed of one or more complete enumeration areas.Reference maps showing EAs are published separately. Enumeration areas (EAs) never cut across any standard geographic areas recognized by the census. Therefore the boundaries and codes of EAs change from census to census, reflecting population shifts, changes to census subdivisions and geographic area boundaries and changes to census representative workload criteria. The 1991 census was taken in accordance with the boundaries of the 195 federal electoral districts (FEDs) identified by the 1987 Representation Order to the Electoral Boundaries Readjustment Act. A federal electoral district (FED) is that area entitled to return a member to serve in the House of Commons. This product provides a profile of enumeration areas (EAs) within federal electoral districts. Part B, provides data collected from a 20% sample of households for the same geographic areas, on characteristics such as home language, ethnic origin, place of birth, education, religion, labour force activity, housing costs, and income.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.027 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.026 |
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".