How to compare and analyse risks of internet voting versus other modes of voting
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
Internet voting (I-voting) has been very topical and it has been used in elections in North America, Europe and elsewhere. The advantages of its use include increased participation from infirmed, elderly and itinerant voters and quicker vote tabulation. Its disadvantages stem from the inherent lack of control and transparency from allowing votes from homes and other locations rather than from controlled polling stations, which may lead to voter fraud or inadvertent spoilage of 'virtual' ballots. Much of this balancing-off of pros and cons is done on a qualitative basis with little attempt at quantifying the risks using an established methodology. The application of a well-known risk analysis method, Operationally Critical Threat, Asset and Vulnerability Evaluation (OCTAVE) has merely been proposed. In this paper, we extend this general proposal and describe key constructs for applying OCTAVE to perform risk analysis for voting alternatives in general. Governments or other institutions can then use this methodology to perform quantitative risk analysis to compare different voting alternatives including I-voting, as well as poll, mail-in and telephone voting.
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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 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