MétaCan
Menu
Back to cohort
Record W4402716930 · doi:10.1007/978-3-031-72244-8_6

Absentee Online Voters in the Northwest Territories:Attitudes and Impacts on Participation

2024· book-chapter· en· W4402716930 on OpenAlexafffundabout
Nicole Goodman, Helen A. Hayes, Stephen B. Dunbar

Bibliographic record

VenueLecture notes in computer science · 2024
Typebook-chapter
Languageen
FieldComputer Science
TopicInternet Traffic Analysis and Secure E-voting
Canadian institutionsIndustry, Tourism and InvestmentGovernment of Northwest TerritoriesMcGill UniversityBrock University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsComputer scienceOperations researchEngineering

Abstract

fetched live from OpenAlex

Abstract Despite being deployed in Canadian municipal elections since 2003, online ballots were not used in binding elections at higher levels of government until the Northwest Territories’ adoption of online voting for absentee voters in its territorial elections in 2019 and 2023. Municipal and Indigenous use of online voting in Canada are well studied, but implementation at higher orders of government have not yet been examined. Drawing on an original data set of online voters in the 2023 Northwest Territories territorial election, we examine who votes online in higher order elections, attitudes towards the voting mode, and its impact on engagement. Throughout our analysis, we simultaneously compare these data to original data from online voter exit surveys conducted during the 2022 Ontario municipal elections. We find that uncommitted voters outside of Yellowknife would not have voted without the online option. Similarly, for municipal voters, we find that age and past voting record correlate with whether the online option influenced electors to cast a ballot.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.275
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueLecture notes in computer scienceSame topicInternet Traffic Analysis and Secure E-votingFrench-language works237,207