Making Democracy Accessible: Making Canadian Political Processes More Inclusive
Bibliographic record
Abstract
Canadians with disabilities continue to face barriers to exercise their democratic rights. Specifically, Canadians with disabilities face barriers to being able to vote. Barriers to accessibility prevent individuals with disabilities from voting. Furthermore, individuals with disabilities are ignored by politicians and candidates. Currently, individuals with disabilities remain a marginalized group in society and by not being able to vote or influence public-policy, individuals with disabilities cannot make changes to improve their lives. This leads to individuals with disabilities being unable to make necessary changes in public policy. A democratic deficit exists amongst Canadians with disabilities. The lack of participation of individuals with disabilities presents itself as a systemic barrier.\nThus, my research aims to address this democratic deficit and offer recommendations for solving this issue. This deficit is evidenced by the deficiency of accessibility within Canadian elections, the lack of recognition by politicians at the federal and provincial levels, and barriers to participating in the electoral process and policy-making. The key recommendations that will be addressed in this research include: enacting universal legislation throughout Canada that promotes inclusivity in political processes, implementing electronic voting, and increasing the use of mail-in voting. The overall goal of this research is to raise attention to the democratic deficit that individuals with disabilities are facing. By raising attention to this issue, various systemic barriers to political participation can be addressed and democracy can become accessible for all Canadians. In all, my research aims to make Canadian society more accessible.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.031 | 0.016 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".