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Record W4385668199 · doi:10.1002/2688-8319.12258

Collaboration between local Indigenous and visiting non‐Indigenous researchers: Practical challenges and insights from a long‐term environmental monitoring program in the Canadian Arctic

2023· article· en· W4385668199 on OpenAlex
Samuel Richard, H. Grant Gilchrist, Holly L. Hennin, Vivian M. Nguyen

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEcological Solutions and Evidence · 2023
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsCarleton UniversityEnvironment and Climate Change Canada
FundersArcticNetNunavut General Monitoring PlanNunavut Wildlife Research TrustCarleton University
KeywordsIndigenousEiderBest practiceGovernment (linguistics)Citizen sciencePopulationArcticGeographyEnvironmental resource managementEnvironmental planningPublic relationsPolitical scienceSociologyEcology

Abstract

fetched live from OpenAlex

Abstract There is a growing appreciation for the value of collaborative research projects involving local Indigenous and visiting non‐Indigenous researchers. Examples of such partnerships are now numerous and diverse, and best practices and respectful approaches have been well presented, including the five priorities of the National Inuit Strategy on Research (NISR) defined by Inuit Tapiriit Kanatami in Canada. However, the application of best practices remains challenging, and examples of ‘on‐the‐ground’ implementation remain scarce in the literature. We present a practical case study in which scientists from the Federal Department of Environment and Climate Change Canada and Inuit have co‐delivered a multidecade‐long monitoring program of nesting common eider ducks Somateria mollissima in the Arctic. We review our experience as southern‐based government researchers in this collaboration. We reflect on successes and, more importantly, on the practical challenges that prevent the full implementation of best practices in our program. First, we highlight challenges to co‐designing a data collection protocol that combines both Indigenous and Western scientific methods. We show how combining the strengths of Inuit Knowledge and rigorous random sampling design has led to a more powerful approach to eider population monitoring. Second, we review how the federal government's administrative approaches are poorly suited for employing seasonal Indigenous workers living in remote communities, particularly in Canada. We argue that to deliver respectful employment and payment practices, the financial and hiring administration of collaborative projects must be based at the community level. Finally, we show how sociocultural factors have made it challenging to ensure the safety of all field workers consistently. To increase their perceived value and uptake, we suggest that safety guidelines must be co‐designed by visiting researchers and local partners for each project to ensure that they are appropriate to the local culture, field conditions, and the nature of the fieldwork. Based on our experience, we draw attention to gaps that still exist between the best practices of collaborative research and factors that hamper their practical implementation. We invite other research teams to do the same so that, collectively, we can improve collaborative approaches nationally and internationally.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.240
GPT teacher head0.443
Teacher spread0.202 · 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