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Record W3047012769 · doi:10.1139/as-2019-0012

The importance of continuous dialogue in community-based wildlife monitoring: case studies of dzan and łuk dagaii in the Gwich’in Settlement Area

2020· article· en· W3047012769 on OpenAlexaffvenueabout
Rachel A. Hovel, Jeremy R. Brammer, Emma E. Hodgson, Amy Amos, Trevor C. Lantz, Chanda Kalene Turner, Tracey A. Proverbs, Sarah Lord

Bibliographic record

VenueArctic Science · 2020
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsGovernment of CanadaUniversity of VictoriaSimon Fraser UniversityEnvironment and Climate Change Canada
Fundersnot available
KeywordsWildlifeSettlement (finance)Environmental resource managementNatural resourceValue (mathematics)Resource (disambiguation)Natural resource managementArcticGeographyEnvironmental planningBusinessPolitical scienceEcologyComputer scienceEnvironmental science

Abstract

fetched live from OpenAlex

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.736
Threshold uncertainty score0.525

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0320.011
Scholarly communication0.0050.004
Open science0.0030.009
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.141
GPT teacher head0.421
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2020
Admission routes3
Has abstractyes

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