Sami-digital storytelling: Survivance and revitalization in Indigenous digital games
Bibliographic record
Abstract
This article examines how digital games on Sami culture can draw attention to Indigenous issues when produced in collaboration with Sami community members. Through a case study that probes the design, game mechanics, and user experience of Gufihtara eallu (2018), this article frames Indigenous digital games and game development as a form of digital storytelling that is able to educate players on Indigenous knowledge systems and intangble cultural heritage. By looking at the way Gufihtara eallu engages Sami oral traditions in particular, this article demonstrates how digital games are capable of embodying Indigenous methodologies in such a way as to not flatten understandings of Indigenous traditions to a mythologized historical moment; instead, games produced by and for Indigenous people are capable of presenting storytelling traditions as contemporary, interactive, and constantly evolving, incorporating traditional themes as much as contemporary issues that are being perpetually redefined by modern Sami experience and new technologies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".