Tino Rangatiratanga: Indigenous (Māori) Sovereignty and the Messy Realities of Reconciliation Efforts at the 2023 FIFA Women's World Cup
Bibliographic record
Abstract
Organizers of the 2023 FIFA Women's World Cup event made explicit their aim to "be and do better" regarding the inclusion and representation of Indigenous peoples. This was particularly important because in seeking to jointly secure the right to host the event, both Aotearoa New Zealand and Australia made much of including and showcasing Indigenous cultures in their respective countries. Subsequently, organizers incorporated Indigenous flags, language, and rituals throughout the event. FIFA appointed cultural advisors to enhance cultural understanding among teams. However, the Spanish national team, "La Roja," sparked controversy by posting a video mocking the haka, "Ka Mate," a cultural treasure to Māori, the Indigenous people of Aotearoa New Zealand. This led to public outcry, calls for apology, and efforts to reconcile relations. In this commentary, we explore this incident, critiquing FIFA and the current state of event management regarding the inclusion of Indigeneity and engagement with Indigenous 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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.020 | 0.013 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 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".