Bibliographic record
Abstract
The North has been imagined and represented for centuries by artists and writers of the Western world, which has led, over time and the accumulation of successive layers of discourses, to the creation of “imagined North” – ranging from the “North” of Scandinavia, Greenland, Russia, to the “Far North” or the poles. Westerners have reached the North Pole only a century go, which makes the “North” the product of a double perspective: an outside one – made especially of Western images – and an inside one – that of Northern cultures (Inuit, Sami, Cree, etc.). The first are often simplified and the second, ignored. If we wish to understand what the “North” is in an overall perspective, we must ask ourselves two questions: how do images define the North, and which ethical principles should govern how we consider Northern cultures in order to have a complete view (including, in particular, those that have been undervalued by the South)? In this article, the author tries to address these two questions, first by defining what are the imagined North and then by proposing an inclusive program to “recomplexify” the cultural Arctic.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.030 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".