Visions of time in geospatial ontologies from Indigenous peoples: a case study with the Eastern Cree in Northern Quebec
Bibliographic record
Abstract
Geography (e.g., features, topology, relationships) is relatively well-developed in ontology research. Integrating time and temporal referencing of geographic concepts in ontologies remains understudied with serious ramifications when we attempt to apply ontological models. The gap is heightened when considering Indigenous concepts of time as existing geospatial and temporal ontologies limit the knowledge that is acquired, modelled, and made interoperable with existing systems. Our case study with the Cree Nation of Wemindji in Northern Canada utilizes ethnography and qualitative analysis methods to compare Cree concepts of space-time with time in conventional geospatial ontologies. The study reveals four assumptions that differentiate Indigenous space-time from conventional ontologies, namely: 1. Time can be a repeating cycle instead of a line; 2. The past and the future have agency, which contrasts with the positioning in the present; 3. Geographic entities are dynamic processes rather than fixed physical objects; 4. Time is inseparable from a place rather than merely a fourth dimension added to a three-dimensional space model. We propose an alternate spatio-temporal ontology that better integrates Indigenous concepts and improves the interoperability of data.
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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 | 0.003 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".