IMALIRIJIIT: a community-based environmental monitoring program in the George River watershed, Nunavik, Canada
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
There is increasing interest in community-based environmental monitoring (CBEM) in Canada’s North in response to the rising impacts of resource exploitation and climate change, and with increased recognition of indigenous knowledge. IMALIRIJIIT, meaning those who study water in Inuktitut, is a CBEM program involving science land camps, capacity-building workshops, and scientific data collection with the participation of youth, elders, local experts, and researchers. It was coinitiated by the Inuit community of Kangiqsualujjuaq (Nunavik, Quebec) and university researchers. This hands-on and land-based program aims to establish a sustainable environmental monitoring program of the George River, before the start of a rare earth elements (REEs) mining project in its upper watershed. The community was concerned about potential impacts on the river, as it is crucial to fishing, hunting, and gathering. The community therefore wanted its own independent and long-term environmental monitoring program to collect baseline data and promote local capacity-building. IMALIRIJIIT includes water-quality measurements, bio-indicators, contaminant and REE biomonitoring in traditional food, remote-sensing analysis of water-quality parameters and vegetation change at the watershed scale, as well as interactive mapping of traditional ecological. IMALIRIJIIT outcomes and challenges are discussed to identify conditions for successful implementation of CBEM and environmental stewardship.
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 | 0.001 | 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 | 0.007 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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