Arctic governance, indigenous knowledge, science and technology in times of climate change
Bibliographic record
Abstract
Purpose This paper aims to place a discussion of traditional knowledge and the indigenous voice within the framework of Arctic governance. Design/methodology/approach The study involves literature review spanning different disciplines and highlighting important case studies. Findings The advance of low-cost, portable technology has brought about tremendous opportunities for indigenous people. Knowledge and observation are no longer monopolised by scholars, filmmakers or politicians based in the West. Film has proved to be a powerful tool for cultural preservation while the internet (video sharing sites and social media platforms in particular) have empowered local communities and facilitated their involvement in political activism and local governance. New ways to represent themselves have been a crucial step forward, yet the new goal is to work towards greater recognition of the “indigenous voice” and ensure traditional knowledge is not treated as anecdotal and irrelevant in managing Arctic affairs.. Research limitations/implications The conclusions reached in the discussion need to be further explored by extending the research into Inuit communities to survey how technology can facilitate and impact collaborative forms of governance in the Arctic. Practical implications This research provides an increased understanding of how technology transforms power relations. Policymakers can see that the indigenous community in the Arctic is not lodged in the past. Their increased use of new technology can serve as an effective oversight of political decisions and economic initiatives, particularly those relating to oil and gas exploration in the region. Social implications Indigenous views and knowledge are literally crossing borders through media. Initially perceived as a cultural threat, film, video and internet are now regarded as powerful technology tools for cultural preservation and empowerment of local communities. In other words, the modern communication patterns are a crucial mean of indigenous population take part of the current global debate, express their concerns, reinforce their values and traditions and have an active voice in the globalised world. Originality/value This paper illustrates how technology helps indigenous communities to address different economic, environmental, cultural, educational, research and other issues in the Arctic. Robust evidence is presented to support the call for traditional knowledge to become an integral part of decision-making processes across all institutions of governance 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.027 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".