Between the Dreamtime and the GPS / The Metaphysics of Indigenous Mapping
Bibliographic record
Abstract
Although many scholars have written about the relationships between land, mapping, power relations, and sovereignty, very few have explored the relationship between the imbricated fields of Aboriginal mapping, Indigenous aesthetics and placemaking, and the ways in which Aboriginal maps, both customary and contemporary, contribute to the conversation about remembering, Indigenous knowledge production, and cultural survivance.1 If maps construct rather than reproduce the world (Wood 2008: 92), how can the documentation and creation of an Indigenous mapping archive assist in bringing forward Indigenous worldviews, in particular those that emphasize the significant interrelationships between land, aesthetics, and Indigenous senses of place? To date no such archive exists. This doctoral project sets out to conceptualize and design a mobile Indigenous mapping archive that will carry within its walls an exhibition of Indigenous artists’ maps, a mapping library, two digital interfaces, Indigenous teachings, and ceremonial artifacts. The importance of this archive lies in its ability to assist settler and Indigenous communities to mutually grapple with how land matters to Indigenous Peoples in what is now known as Canada, and specifically with the gap between “what is known and what is merely seen” (Wood 2008: 92).
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.045 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| 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".