Making Brave Space: Beading, Reconciliation, and Urban Indigenous Geographies
Bibliographic record
Abstract
While cities have historically sought to displace and exclude Indigenous peoples through a multitude of state-sanctioned discriminatory policies such as the Indian Act, today, Indigenous peoples and cultures are flourishing across Canada’s urban landscape and are creating new urban Indigenous geographies. Young Indigenous peoples are part and parcel of the vibrancy of urban Indigenous communities, especially given their involvement in promoting Indigenous cultures to wider audiences through social media. This project focuses on the spaces of solidarity and cultural exchange created by beadwork. This traditional art form and practice represents an important marker of Indigenous identity and a true form of cultural resurgence. While beadwork can represent a clear expression of one’s identity in the city, it also provides opportunities for social gathering and exchange. One such example are beading circles where participants gather to bead and socialize. Focusing on the city of Ottawa, Canada’s national capital, the study brings together the experiences of 13 post-secondary Indigenous students and artists, considering the role of beading circles on university campuses and how they can serve as what one interlocutor termed “brave spaces” and as sites of cultural and social exchange between Indigenous and non-Indigenous students. It is argued that these networks of learning, exchange, and solidarity enable the formation of an urban sense of place while contributing to an Indigenous right to the city and to difference, ultimately furthering the process of Indigenous urbanism and the national project of truth, reconciliation, and healing.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.037 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.013 |
| 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".