A Community-Based Approach to Mapping Gwich'in Observations of Environmental Changes in the Lower Peel River Watershed, NT
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
In Canada's western Arctic climate change is driving rapid ecological changes. Ongoing and locally-driven environmental monitoring, in which systematic observations of environmental conditions are recorded and synthesized, is required to understand and respond to climate change and other human impacts. Indigenous peoples' traditional ecological knowledge is increasingly used as the basis for regional monitoring, as there is a need for detailed, place-specific information that is consistent with local ways of understanding and interacting with the environment. In this project, participatory multimedia mapping was used with Teetł'it Gwich'in land users and youth from Fort McPherson, Northwest Territories, Canada to record information about local environmental conditions and changes. Gwich'in monitors made trips on the land to document environmental conditions and changes using geotagged photo and video observations. Subsequently, land users provided detailed information about each observation in follow-up interviews, which were added to a web-based map displaying participants' photos and videos. In this paper, we present the outcomes from the first year of research, explore the diverse types of knowledge this approach can contribute to environmental monitoring, and identify areas of convergence between traditional ecological knowledge and scientific research in the Arctic. Our work shows that this approach can make an important contribution to monitoring environmental changes associated with climate change in a way that is locally relevant and culturally appropriate.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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