North American Indigenous Soccer: Visibility, Intergenerational Healing & Schelangen in Global Football
Bibliographic record
Abstract
This study addresses the relationship between intergenerational trauma of ongoing United States and Canadian colonialism as it impacts Native American and Aboriginal First Nations Peoples and ways global football contributes practices of intergenerational healing. I argue that Indigenous soccer operates as a mechanism of decolonization and re-membering for Indigenous Peoples who inherit colonial traumas. Indigenous soccer directly challenges hegemonic sports culture as typically marked by Indian mascotry and Native invisibility. While cultural historians have shown how American sports are used as colonial technologies of assimilation, violent gendering, labor and militarism, the story of Indigenous soccer has not been studied. As a Lummi footballer, I utilize Native voices from Coast Salish Tribes of Washington State and British Columbia, Mohawk and Cree First Nations Canada, Southwest tribes from New Mexico Pueblos and Navajo Nation, and Kiowa Territories in Oklahoma to illustrate Indigenous soccer identities and schelangen, or way of life in Lummi. As soccer in North America challenges hegemonic ideologies of nationalism, instrumental Indigenous footballers are demanding visibility, like the late Canadian Hall of Fame First Nations Aboriginal footballer Snuneymuxw Harry Xulsimalt Manson and U.S. World Cup participant Kiowa Native Chris Bau Daigh Wondolowski. Using the theoretical framework of Tulalip scholar Stephanie Fryberg's “theory of invisibility,” I tell and analyze Indigenous soccer stories as evidence that Indigenous visibility, in soccer or otherwise, provides intergenerational healing. I begin to fill the gap in the sports culture and U.S.-Canada colonialism discourse, with the goal of making Indigenous soccer locally accessible as an instrument of decolonial healing for generations of Indigenous North American Peoples.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".