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Record W4415595048 · doi:10.1177/03091333251391084

Communicating science from the Arctic: A collaborative protocol to mitigate harm

2025· article· en· W4415595048 on OpenAlexaffabout
Rachel Pain, Jen Bagelman, Brian Kowikchuk, Carmen ‘Kaguna' Kuptana, Eriel Lugt, Darryl Tedjuk, Maéva Gauthier

Bibliographic record

VenueProgress in Physical Geography Earth and Environment · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHarmSituatedIndigenousProcess (computing)Adaptation (eye)Community resilienceTraditional knowledgeScience communicationPsychological resilience

Abstract

fetched live from OpenAlex

Scientists increasingly engage communities living in researched places as an attempt to mitigate harm and produce more equitable research. However, these efforts are not always successful. This paper focuses on the communication of research to the wider world, a key area of activity that is seldom undertaken jointly. Research communications and outputs may unintentionally reinforce harmful ideas and actions that disbenefit communities. For example, they may represent people as passive victims of environmental change, or call for solutions that appear to resolve one problem but have damaging side effects. Instead, through co-production, communities can assert shared ownership of communications, identify risks and priorities, and control the representation of land, water, and people in academic and public debates and in policy. This paper reports the process by which a communications protocol was developed collaboratively by community researchers and academics, for a study of Inuvialuit youth resilience and innovative adaptation to climate change. It discusses the implementation of the protocol, which we suggest has potential for wider use in scientific research. The paper provides researchers with a template that may be adapted for different studies, issues, and communities. This Collaborative Perspective, co-authored by Inuvialuit, Canadian and UK academic and community researchers, aims to contribute to the growing literatures on science co-production and community self-determination in research and its impacts. The critical discussion is situated in imperatives to decolonise research processes, responding to calls from Indigenous scientists to disrupt the hegemony of western scientific knowledge.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.511
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.089
GPT teacher head0.406
Teacher spread0.317 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2025
Admission routes2
Has abstractyes

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Same venueProgress in Physical Geography Earth and EnvironmentSame topicClimate Change Communication and PerceptionFrench-language works237,207