The hidden rise of new women candidates seeking election to the House of Commons, 2000 – 2008
Bibliographic record
Abstract
Women’s candidacy and election are tracked over four Canadian national elections from 2000 to 2008. These elections brought a dramatic expansion in women candi-dates, but only a small increase in the number elected. Simu-lations of alternative electoral outcomes indicate only minor impact due to the shift from Liberal to Conservative gov-ernments. Women candidates from all major parties are found to have been similarly successful as men with the same party and incumbency status. Analysis of the candi-date-pool composition reveals that there were too few new women candidates in 2000 even to maintain the status quo in the House. Increases in 2004 and 2006 brought candida-cies into balance with the House composition. In 2008 the recruitment rate exceeded the House proportion meaning-fully. Since the Conservatives caught up part-way to the other parties in nominating new women candidates in 2008, the gender composition of the House became far less sensi-tive to voters’ partisan preferences than was the case earlier. The results show that the flat numbers elected arose not from stagnation in recruitment of new women candidates, but rather from two relatively large fluctuations: a cross-party collapse in 2000, followed by a cross-party resurgence. Women’s share of non-incumbent major-party candidacies and turned-over seats nearly doubled over the eight-year period, both reaching the one-third mark for the first time in 2008. This cross-party resurgence is shown to have carried over to the 2011 election.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".