Bibliographic record
Abstract
This volume contains a selection of papers presented at E-Vote-ID 2024, the Ninth International Joint Conference on Electronic Voting, held on October 2-4, 2024.This is the first time the conference was held on the Mediterranean coast in Tarragona (Spain).The conference venue, in the fishermen's harbor of Tarragona, represents Catalan and Mediterranean cultures' singularity, bringing a new spirit to the conference and contributing to diversifying the venues where E-Vote-ID was held.The E-Vote-ID Conference resulted from merging EVOTE and Vote-ID and counting up to 20 years since the first E-Vote conference in Austria.Since that conference in 2004, over 1800 experts have attended the venue, including scholars, practitioners, representatives of various authorities, electoral managers, vendors, and PhD students.The conference collected the most relevant debates on the development of Electronic Voting and Electoral Technologies, from aspects relating to security and usability through to practical experiences and applications of voting systems, also including legal, social, or political aspects, amongst others, turning out to be an important global reference point concerning these issues.This year, as in previous editions, the conference consisted of:-Security, Usability, and Technical Issues Track; -Governance of E-Voting Track; -Election and Practical Experiences Track; -PhD Colloquium; -Poster and Demo Session.E-VOTE-ID 2024 received 36 submissions for consideration in the first two tracks (Technical and Governance Tracks), each being reviewed by 3 to 5 program committee members using a double-blind review process.As a result, 10 papers were accepted for this volume, representing 36% of the submitted proposals.The selected papers cover a wide range of topics connected with electronic voting, including experiences and revisions of the actual uses of E-
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".