Connecting Indigenous Placemakers Highlights Report
Bibliographic record
Abstract
Connecting Indigenous Placemakers was a week-long practitioners’ retreat and one-day public symposium held on Menecing, the Toronto Island (Treaty 13a). It was supported by the Mississaugas of the Credit First Nation (MCFN) and Ngā Aho Māori Designers’ Network. Based on the success in Aotearoa New Zealand of supporting Indigenous placemaking practitioners and shaping opportunities through a network, the 2019 gathering created a supportive space for Indigenous creatives to be on the land, work on collective and individual projects, build relationship with one another, share knowledge, and shape broader discourse on Indigenous placemaking in Toronto. As retreat participants integrated the teachings of Menecing, the Treaty Lands and Territory of the MCFN and a gathering place of many Nations, the group began referring to the project as Maanjiwe Nendamowinan, the Gathering of Minds. This co-creative experience made clear the primacy of Place (an entity with a specific identity). That is, “we don’t make place – Place makes us”. Grounded in Menecing and in dialogue with many voices, we present highlights and key themes to emerge from the gathering: Connecting with and caring for Place; Nourishment and healing; and Gathering strength.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.089 | 0.007 |
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".