Another Digital Divide? Evidence That Elimination of Paper Voting Could Lead to Digital Disenfranchisement
Bibliographic record
Abstract
Internet voting is currently used in binding elections in 10 countries, and is being considered in many others. In almost all instances where it has been implemented, it is offered as a complementary method of voting; often with the aim to make voting easier and thereby improve turnout. In many municipalities in Canada, however, the adoption of online voting has meant the simultaneous elimination of paper ballots. Drawing on data from a large survey of paper and Internet voters in the 2014 municipal elections in the province of Ontario, Canada, this article examines the effects of eliminating paper ballots on electors based on their digital literacy. We show that digital access and literacy are strongly related to voting method when paper ballots are an option. When paper ballots are unavailable, however, the voting population is made up of more technologically savvy electors, though this effect is delayed and does not occur in the first election without paper ballots. We interpret this finding to indicate that the elimination of paper ballots can disenfranchise those on the wrong side of the digital divide.
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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 | 0.005 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 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".