Indigenous Adoption of Internet Voting: A Case Study of Whitefish River First Nation
Bibliographic record
Abstract
Indigenous communities and organizations are increasingly using digital technologies to build community capacity, strengthen community consultation, and improve political participation. In particular, Internet voting is a type of technology to which First Nations have been drawn. This article explores Whitefish River First Nation's (WRFN) experience introducing Internet voting in the course of ratifying a new matrimonial real property law (MRP). Specifically, we examine the implications of Internet voting for political participation and electoral administration at the community level. Although community members’ uptake of Internet voting was very modest, we find the experience of adoption had other subtle impacts on community capacity, specifically in terms of empowering the community to pass its own laws and connecting youth and elders. With respect to administration, Internet voting provided an opportunity to connect with community members using technology, to modernize voting processes, and to better accommodate community members needs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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 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".