The compactness of federal electoral districts in Canada in the 1980s and 1990s: an exploratory analysis
Bibliographic record
Abstract
Considerations of the compactness and aesthetics of electoral districts have loomed large in the litigation surrounding the last round of US redistricting. For a variety of reasons, we expect that there will be increasing pressure on Canadian electoral cartographers to provide opportunities for protected minorities to be represented in the country's federal legislature. As a result, we expect that future electoral maps may well embody a tradeoff between compactness and other representational and cartographic desiderata. We look for evidence of this in an exploratory analysis of the last two federal electoral maps (adopted in 1987 and 1996) and in so doing we offer the first country‐wide assessment of the compactness of Canadian federal electoral districts (FEDs). The results demonstrate the importance of natural boundaries in the achievement of district compactness. Strong evidence of a decline in the compactness of FEDs between the two maps is not forthcoming, however. Thus there is relatively little sign that Canadian electoral districts will be open to the kind of aesthetically‐based legal challenges that American Congressional Districts faced in the 1990s. However, the analyses we report establish an important baseline against which the next electoral map, to be produced following the 2001 census, can be compared.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.012 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".