Indigenous and Migrant Embodied Cartographies
Bibliographic record
Abstract
The Odeimin Runners Club is an Indigenous and Black-Persons-of-Colour (IBPOC) media arts collective (the “Collective”) creating an online story map using an open-source satellite mapping platform. By tracing activities and connections in our engagements with each other and our communities, our counter-mapping project re-traces trade and ceremonial routes between the north of Turtle Island and the Caribbean archipelago, linking stories, videos and artworks to traditional territories. This paper addresses the process of a pilot project making three 16mm experimental films. Process cinema methodologies that incorporate plants and organic materials in film processing were applied in the first phase of the project to produce three short films using Bolex film cameras. The films are themed on human survival, land connection, “rematriation” and BIPOC counter-mapping, threading our knowledge and stories together as we visit each other’s territories. In the making, Indigenous and performative cartographic methods were also used to map the inter-relations between the histories and futures of the land. An interactive website was created to integrate these methodologies while giving public access to the films during online exhibitions. The interactivity of the platform establishes connections between the films and filmmakers, both formally and thematically, wherein sharing traditional wisdom, imparting important knowledge, and offering support and strength to one another, facilitate the navigation of current political and environmental instabilities facing the authors’ communities. The authors conclude by suggesting future explorations aimed at building an interactive online mapping experience for communities to deepen and widen connections between their respective communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 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".