Embracing Indigenous Knowledge in Arctic Economic Development: A Pathway towards ESG and Indigenous Sustainable Finance Integration
Bibliographic record
Abstract
As industrial activities in the Arctic intensify with more players and capital prospects from international players, it is important to have rules on how to conduct business and make investments which prioritise optimal environmental, social, and governance (ESG) factors or outcomes. This article focuses on voluntary sustainability and ESG compliance and reporting initiatives related to the Arctic context. In 2015, the Arctic Investment Protocol was introduced as an initial endeavour to tackle this issue by establishing a framework that promotes sustainable investment in the Arctic, in alignment with global Environmental, Social, and Governance (ESG) principles. In June 2022, the Inuit Circumpolar Council published eight protocols in the document “Circumpolar Inuit Protocols for Equitable and Ethical Engagement (EEE)”. The shift appears to be in the role Indigenous Peoples take in the formation of rules for conducting business and investment in the Arctic. Protocols released by the Inuit Circumpolar Council build on holistic and collaborative co-production of knowledge and recognise that people are integral parts of the environment, prioritising the importance of Indigenous Knowledge (IK). This article aims to elaborate on the requirement for a paradigm shift that values the collaboration of diverse perspectives for sustainable solutions, where Arctic Indigenous Peoples’ knowledge is viewed as part of the solution for achieving Arctic economic development by integrating environmental, social, and governance (ESG) principles along with Indigenous Sustainable Finance. In the context of ESG investment principles and Indigenous Sustainable Finance, it has become increasingly crucial to recognise and incorporate the wisdom and traditional practices of Arctic Indigenous Peoples. This article traces the development of sustainability frameworks in the Arctic, examines the Inuit Circumpolar Council’s eight protocols, and proposes solutions for the future development of sustainability frameworks in the Arctic.
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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 | 0.019 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.018 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".