The importance of continuous dialogue in community-based wildlife monitoring: case studies of dzan and łuk dagaii in the Gwich’in Settlement Area
Why this work is in the frame
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Bibliographic record
Abstract
Rapid environmental change in the Arctic elicits numerous concerns for ecosystems, natural resources, and ways of life. Robust monitoring is essential to adaptation and management in light of these challenges, and community-based monitoring (CBM) projects can enhance these efforts by highlighting traditional knowledge, ensuring that questions are locally important, and informing natural resource conservation and management. Implementation of CBM projects can vary widely depending on project goals, the communities, and the partners involved, and we feel there is value in sharing CBM project examples in different contexts. Here, we describe two projects in the Gwich’in Settlement Area (GSA), Canada, and highlight the process in which local management agencies set monitoring and research priorities. Dzan (muskrat; Ondatra zibethicus (Linnaeus, 1766)) and łuk dagaii (broad whitefish; Coregonus nasus (Pallas, 1776)) are species of great cultural importance and are the focus of CBM projects conducted with concurrent social science research. We share challenges and lessons from our experiences, offer insights into operating CBM projects in the GSA, and present resources for researchers interested in pursuing wildlife research in this region. CBM projects provide rich opportunities for benefitting managers, communities, and external researchers, particularly when the projects are built on a foundation of careful and continuous dialogue between partners. Arctic gwinagoo’ee gwa’àn khanhts’àt ejùk t’igwinjik k’iighè’ nan kak jidìi nihàh goo’aii tthak ts’àt nits’òo tr’igwindaii geenjit gwiiyeendoo niinji’gwidhat. Ejùk t’igwinjik gwizh’it tr’igwiheendaii ts’àt guk’andehtr’ahnahtyaa geenjit gwijiinchii goo’àii ts’àt kaiik’it gwizhìt yi’eenoo nits’òo tr’igwiindài’ gwinjik guk’andehtr’ahnahtyaa k’iighè’ kaiik’it gwizhìt t’angiinch’uu geenjit guuhadahkat gwijiinchii gwihee’aa ts’àt daginuu, juudin nan ts’àt nan kak gwinahshii tthak k’aginahtii kat guuvàh gugwitaandak. Nits’òo gwitr’it gugwahahtsaa, kaiik’it kat, ts’àt diiyah gwizhìt tr’iinlii nits’òo gwihee’aa k’iighè’ nihłinehch’i’ gwinjik kaiik’it gwizhìt guk’andehtr’ahnahtyaa goo’aii geenjit diiyah gugwaandàk gwijiinchii goo’aii niidadhanh. Canada gwizhìt Gwich’in Nan Sridatr’igwijiinlik gwizhìt nits’òo gwitr’it gugwahahtsaa ts’àt guk’andehtr’ahnahtyaa ts’àt nits’òo gwizhìt tr’igwahnah’aa zhat danh geenjit diiyah gugwaandàk. Dzan ts’àt łuk dagaii, tr’igwindaii geenjit gwiiyeendoo t’atr’ijąhch’uu k’iighè’ kaiik’it gwizhìt guk’andehtr’ahnahtyaa gwijiinchii gòo’aii aii geenjit jùk nits’òo tr’igwindaii gwinjik gwizhìt tr’igwahnah’aa geenjit gwitr’it gugwahahtsah. Nikhwigwitr’it gwizhìt gwits’agwighah gwįį’è’ ts’àt dagwiidi’ìn’ geenjit diiyah gwaandàk k’iighè’, nits’òo GSA gwizhìt geenjit gwitr’it gugwahahtsaa ts’àt juudìn nan kak nin gwindaii gwizhìt gugwahnah’aa giiniindhan guuts’àt tr’ihiidandal niidadhanh. Juudìn jii geenjit gwitr’it gugwahtsii kat nihts’àt gigįįkhii k’iighè’ kaiik’it gwizhìt gwiinzii guk’andehtr’ahnahtyah, gwitr’it gwichìt kat, kaiik’it kat ts’àt uu’òk gwizhìt gugwinah’in jii k’iighè’ gwiinzii digugwitr’it gugwahahtsah.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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