Bibliographic record
Abstract
This article sheds light on the issue of national identity as related to the Tourist Association of Iceland, which was founded near the end of the 1920s. Written Association sources illustrate how the leading participants interpreted their work ideologically, with nationalistic connotations. Not only did they see themselves as heirs of Iceland’s celebrated first settler, Ingólfur Arnarson, but they applied this picture of themselves to the nation as a whole. While engaged in opening up the country—in particular its uninhabited highlands—and in building up a modern travel infrastructure, they interpreted these undertakings as parallel to Iceland’s initial settlement. They therefore viewed themselves as pioneers who had taken on the mission of pacifying the still frightening Icelandic environment and providing access to its resources. In this way, they would not merely contribute to modernizing their country, but also to cultivating a positive national self-image. This self-image was based to a large degree on self-assertion over nature, as well as on portraying the nation as the most northerly preserver of culture within European civilization. Curiously, this meant assigning attributes to Iceland’s own interior that depicted it as a “Far North,” a North that ought to be challenged and wherever possible conquered.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".