The (complex) effect of internet voting on turnout: Theoretical and methodological considerations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The adoption of remote internet voting can be a rather complex reform. In theory and praxis, geographical units can either decide to adopt or not to adopt i‐voting. Those that adopt it can differ in the mode of i‐voting adoption (i.e., internet‐only voting, or also in‐person voting), and the timing of adoption (i.e., some geographical units might adopt it earlier than others). How does the decision to adopt internet voting, the mode of adoption and the timing of adoption influence turnout? Using data spanning the municipal elections in Ontario, Canada from 2000 to 2018, we try to answer these research questions. Generally, we find that allowing internet voting, regardless of the availability of in‐person voting, does not influence turnout over the long term. However, we do find a temporal pattern, in that some of the most participatory municipalities adopted internet voting the earliest. We also detect a novelty effect; a sizable increase in turnout during the first ever election in which internet voting was introduced, which vanished in following elections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it