Relocating a Sense of Place Using the Participatory Geoweb
Bibliographic record
Abstract
The interactive capability and ease of use of Geoweb technologies suggest great potential for Aboriginal communities to store, manage, and communicate place-related knowledge. For the Métis, who have a long history of dispossession and dispersion in Canada, the Geoweb offers an opportunity in realizing the desire to articulate a coherent sense of place for their people. This paper reports on a community-based research project involving the University of British Columbia (UBC) and the Métis Nation of British Columbia (MNBC) – the political body representing the Métis people in BC. The project includes the creation of a Geoweb tool specifically designed to facilitate the (self) articulation of a Métis community in contemporary BC. It examines how Geoweb technologies have been used to create a participatory, crowd-sourced Historical Document Database (HDD) that takes meaning through the interface of a map. The paper further explores how the data contributed by members of the Métis community have been used to capture, communicate, and represent community memories in the dispersed membership. It concludes by examining challenges that have emerged related to platform stability and institutional relations related to the ongoing sustainability of the HDD.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".