Gaming Extractivism: Indigenous Resurgence, Unjust Infrastructures, and the Politics of Play in Elizabeth LaPensée’s<i>Thunderbird Strike</i>
Bibliographic record
Abstract
Background: Indigenous-led struggles against fossil fuel infrastructure in North America have become increasingly visible. These struggles occur on the ground as well as through cultural production that performs cultural resistance. Analysis: This article examines Anishinaabe, Métis, and settler-Irish media theorist and artist Elizabeth LaPensée’s video game Thunderbird Strike as a form of Indigenous cultural resistance to extractivism. Conclusion and implications: Thunderbird Strike expresses the necessity of halting the expansion of extractivism by inviting players to participate in the sabotage of unjust infrastructure. In asking players to enact the very forms of generative resistance that the game articulates at a narratological level, Thunderbird Strike reveals the possibilities for video games to prefigure the transition to a decolonial, post-extractive future.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.022 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".