Examining the Effects of 2SLGBTQI+ Candidates on 2SLGBTQI+ Voter Turnout in Canada
Bibliographic record
Abstract
Affinity theory suggests that 2SLGBTQI+ candidates might empower and motivate 2SLGBTQI+ voters to become more politically engaged because they demonstrate that the political system is open to queer participation and voices. However, most research has focused on high-profile 2SLGBTQI+ candidates. Little attention has been paid to the impact of local candidates, particularly in a multi-party parliamentary system. This paper explores this candidate-voter affinity by incorporating information about the 70 2SLGBTQI+ candidates who ran in the 2021 Canadian federal election into survey results of the 2021 Canadian Election Study (CES). Comparing responses of 2SLGBTQI+ voters in districts with 2SLGBTQI+ candidates to those of 2SLGBTQI+ voters who do not have such candidates to select enables us to demonstrate the impact of these affinities on voter turnout. Our results reveal positive affinities, meaning 2SLGBTQI+ individuals are indeed more likely to vote and their turnout is higher in the districts with 2SLGBTQI+ candidates.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".