Voting Behaviour and Habits Within Federal Elections
Bibliographic record
Abstract
Since 1990, voter turnout in Canadian federal elections has consistently declined. This decline could be explained by age, generational, cultural changes and economic factors such as income. However, there have been certain elections that had a substantial increase in voter turnout such as the 2006 and 2015 elections which both resulted in a new governing political party. Both of these elections saw the winning parties mobilize supporters who were typically absent and refrained from voting, and despite this increase, voter turnout would continue to decline in the following elections. Therefore, this presentation will look at themes such as age, generational replacement, education and income to help explain the reason for the decline in voter turnout. Voting trends and patterns will also be observed from the more recent federal elections starting from 2004 up to the 2021 federal election to get a better understanding of observing these elections. The research will also look at the United Nations Sustainable Development Goals such as Goal 10, reducing inequalities for minorities, racialized and Indigenous communities and the barriers they face when it comes to voting.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".