Co-producing maps as boundary objects: Bridging Labrador Inuit knowledge and oceanographic research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Climate change is affecting the marine environment in Nunatsiavut, leading to changing sea ice thickness and seasonal timing, and increasing water temperatures. This impacts the lives of Labrador Inuit, whose culture, economy, and history are deeply tied to marine spaces. Recently, research partnerships involving Inuit communities in Nunatsiavut have increased, creating space for Labrador Inuit in large scale marine research agendas. While including Labrador Inuit knowledge is critical for making research relevant to communities, there are challenges to engaging it alongside oceanographic scientific knowledge, as both stem from unique ontologies, at times having different values, scales, and languages of understanding. Boundary work offers a lens to analyze how boundary objects can foster connections between Labrador Inuit knowledge and oceanographic research. This research offers a conceptual exploration of this subject through analysing the co-production of maps representing Labrador Inuit knowledge of ocean features which, as data, were then applied in oceanographic research problems. Framing these maps as boundary objects demonstrates their utility in mobilizing Inuit knowledge into scientific approaches, acknowledging limitations with respect to knowledge that cannot be spatially rendered.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it