Bibliographic record
Abstract
Northern political affairs are, to put it mildly, in “transition.” Political turnover continues in the Territorial North. American President Donald Trump continues his chaotic ways, most recently (November 2025) through the release of the “America First” national security strategy that raises serious questions about Canadian sovereignty in the Arctic. Russian adventurism in the Far North remains a looming threat. Climate change is having an outsized impact across the region. It is not all worrisome. Indigenous re-empowerment and self-determination across the Circumpolar North continues to broaden, along with expansions in governance. There are significant commercial successes for northern Indigenous economic development corporations (and Alaska Native Corporations). The establishment of First Nations education and health authorities and Indigenous-led wildlife management regimes in Canada, among other initiatives, promise a different and exciting future in the North. For the Northern Review, it has been a distinct privilege to be a small part of the Arctic futures re-imagining process, helping to challenge the status quo. We encourage, in a variety of transnational and multidisciplinary perspectives, wide-ranging and thought-provoking analysis and commentary on northern issues. While we make a concerted effort to tap the exceptional knowledge and expertise of people living and working in the North, we also welcome contributions from scholars and professionals currently based elsewhere. We all share a concern for the just, inclusive, and creative evolution of the Arctic. Our 58th volume continues in this vein. We start by celebrating the life and professional contributions of Mary Ehrlander, a superb Alaskan scholar and since 2013 a valued member of our editorial board, who sadly passed away earlier this year. Mary had also published articles in the journal in 2007 and 2010, with fascinating comparative research exploring the history of alcohol in the Circumpolar North. Mary will be missed by many, for reasons that her University of Alaska Fairbanks colleague Brandon Boylan makes very clear. We appreciated her kind and insightful contributions, and we’re grateful that she connected us with Brandon, who has now joined the Northern Review as a senior editor. We are already finding his expertise and measured advice very helpful. There is much to learn from and share with our Alaskan neighbours and friends, and we are glad to continue this valuable collaboration across our international border. The research papers in this volume cast a broad net over northern issues, from legends in the South Nahanni River Valley and the role that stories can play in colonization, to the raging current debate about critical minerals and the complexities of our relationship with them. Another contribution explores the challenges of data collection in northern communities, and contemplates how the evidence and methodologies used can skew policy making. These are all, in markedly different ways, issues of wide concern and importance across the North. The Northern Review continues to invite commentaries on Indigenous research frameworks and academic scholarship. A research perspective paper explores one of these frameworks and how it was applied in a project in Old Crow, Yukon, offering guidance for what is still sometimes seen as an uneasy intersection of knowledge systems. A unique reflection paper also brings an important and valuable perspective, making the case for researchers and practitioners to bring their heart to conservation science, as well as the numbers. Finally, a thoughtful commentary on the urgent push to develop northern Ontario resources argues for the importance of continuing baseline studies to protect scientific integrity, health, and Indigenous self-determination. This paper also speaks to themes of pan-northern significance. Constructive provocation remains a hallmark of the many and varied contributions to the Northern Review. We look forward to welcoming ever more perspectives from researchers and thinkers, North and South, as we ponder the grand and important issues of our time. If northern policy is to change—and it is, and will continue to shift in coming years—it is vital that we have informed, insightful, and creative commentary on best paths forward for the Peoples of the North.
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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.121 | 0.076 |
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".