Conceptualizing indicators as boundary objects in integrating Inuit knowledge and western science for marine resource management
Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.007 | 0.033 |
| Scholarly communication | 0.022 | 0.028 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".