Islands as legible geographies: perceiving the islandness of Kalaallit Nunaat (Greenland)
Bibliographic record
Abstract
Despite considerable research within the field of island studies, no consensus has yet been reached as to what it is that makes islands special.Around the world, islands and archipelagos are shaped by diverse spatialities and relationalities that make it difficult to identify clear general characteristics of islandness.This paper argues that one such 'active ingredient' of islandness, which is present across many forms of island spatiality, is the idea that islands are 'legible geographies': spaces of heightened conceptualisability, spaces that are exceptionally easy to imagine as places.The paper uses the case of Kalaallit Nunaat (Greenland) to show how island geographical legibility has influenced a territory's cultural and political development over time, even though Kalaallit Nunaat is such a large island that it can never be experienced as an island but can only be perceived as an island from a satellite or cartographic perspective.I ultimately argue that islandness can have significant effects on a place's development but that it can be difficult to isolate these effects from other factors that may themselves have been influenced by islandness.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".