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Record W3036495308 · doi:10.1139/as-2019-0013

Conceptualizing indicators as boundary objects in integrating Inuit knowledge and western science for marine resource management

2020· article· en· W3036495308 on OpenAlex

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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueArctic Science · 2020
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsDalhousie University
Fundersnot available
KeywordsScope (computer science)Knowledge managementResource management (computing)Resource (disambiguation)Environmental resource managementNatural resource managementEcosystem-based managementCorporate governanceBusinessMaritime boundaryNatural resourceComputer sciencePolitical scienceEcologyEcosystem

Abstract

fetched live from OpenAlex

A complex co-management system exists across Inuit Nunangat, whereby federal, provincial, territorial governments and Inuit organizations manage natural resources cooperatively. Under Inuit land claim agreements, Inuit knowledge, western science, and co-produced knowledge are to be used side by side to support decision-making. However, the mechanisms of effectively integrating these knowledge systems to inform decision-makers remain poorly understood. This limits Inuit self-determination, hinders knowledge production, impedes resource governance improvements, and exacerbates communication barriers leading to tensions in marine resource management. It is also a barrier for scientists to utilize Inuit knowledge that exists in a different capacity, and vice versa. We discuss marine resource management indicators, positioning them as potential “boundary objects” around which different knowledge systems converge. We explore their role for not only monitoring ecosystems, but also for integrating knowledge in co-management. We summarize efforts at developing indicators and explore the extent to which they can take on information from different knowledge systems in support of improved co-management decision-making. Finally, we identify how indicators can be used as a facilitation tool for integrating knowledge systems while also generating new research questions and bringing forward management challenges that would otherwise remain out of the scope of researchers and resource managers. Ilagijauninginnut piliriqatigiigunnarninginnullu pitaqarmat Inuit Nunangat, pijjutigillugu gavamatuqakkut, gavamaillu aviktursimajuni, nunalingnillu gavamagijaujut ammalu Inuit katujjiqatigiingit piliriqatigiittiarpangninginnut nunalirijaraangata. Inuit angirutinga, Inuit qaujimajatuqangi, qallunaalu qaujisartulirijjutigijangit, ammalu piliriqatigiigunnarninginnut qaujimajangitigut aturtauttiariaqarningani piliriqatigiittiarlutik ikajurtigiittiarlutik isumaliuriniaraangata. Taimanninganut, tukisijausimanirijanga saqititaunasuartillugu qaujimajatuqarijaujut isumaliurutauniartillugit tukisiajauttiangimmat. Ajurutigijaujuq Inuit pivaallirutigijunnartanga, piliriarijaungilluni qaujimajaugaluartillugu, ajurutiqartutitut pivaallirutigijunnataraluanginnit, kisianilu ajurutiqainnaujarllutik tusaumaqattautingiluartunut pijjutigijanga ajurutigingmagu imarmiutalirijikkunnu lu pilirijigivaktanginnut. Ajurutigijaugivuq qaujisartiuvaktuni tukisinasuattiariaksaq Inuit qaujimajatuqanginni pitaqattiaraluartillugu asingitigut, ammalu igluanunga tukisinasuarllugu. Uqausirivangmijavut imatmiutalirijaraangata pilirijigijauvaktut, piliriarijjutigijaujunnarniarninginnut “ajurutiujunut piqutiit” tamakkua ajjigiingittuni qaujimajaqartuni tukisiumaqattautilirunnarlutik. Qimirujavut qanuilingagaluarmangaata tamakkuatuinnaungittut nunamiutalimaalu imarmilu ammalu saqitinasuarllugu qaujimajaujut piliriqatingiigiaqarnirmit. Piliriarinasuartavut katirsurllugit saqittijumanirmut piliriqatigiittialirunnarnirmut ammalu qaujivallianirijavut angilirtigiarlugu tukisijauvalliajunut ajjigiingitillugi ikajurutaulirunnarninganut piliriqatigiitialirlutik isumaliurutauqattarniartillugit. Asuilaak, uqarunnalirpugut qaujisarutauniartut aturtaujunnalirput piliriarijjutigilugit qaujimaqattautivallialirnirmut pivallialirtillugit tukisiqattautivalliatilluta qaujisarutiksaniglu nutaanik apiqutiksanik ammalu pilirianguvallianiartillugu ajungijjutigijunnartanginnit katujjiqatingiingniartilluta pitaqarajalaungikkaluartillugi qaujisartinut ammalu nunalirivaktuni pilirijiit.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0050.002
Scholarly communication0.0000.000
Open science0.0000.002
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 head0.043
GPT teacher head0.393
Teacher spread0.350 · 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