Debating the Voting Age: How Canadian Legislators Grapple with the Federal Voting Age
Bibliographic record
Abstract
Choosing a minimum voting age for an election is a decision that democratic countries make at some point in their history but remains an issue that is periodically revisited. And yet, we know too little about how legislators frame support or opposition to changing the voting age. This article uses frame analysis to explore the arguments made by Canadian legislators to support or oppose changes to its federal voting age. This article poses three research questions and examines two periods of parliamentary debates (1901–1972 and 1972–2022). The analysis finds that the arguments used by legislators in both periods changed very little and that Canadian legislators used changing the voting age as a tool to encourage young citizens to participate in formal institutions of the political process (such as voting) and to discourage youth from protesting or from taking political actions outside of formal institutions.
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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 | 0.025 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.034 | 0.021 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".