How to Be a Heroic Explorer in a Friendly Arctic: A Chronotopic Approach to Self-Representation in Vilhjalmur Stefansson’s The Friendly Arctic: The Story of Five Years in Polar Regions (1921)
Bibliographic record
Abstract
This dissertation deals with the exploration account The Friendly Arctic: The Story of Five Years in Polar Regions (1921), written by Canadian-American anthropologist and explorer Vilhjalmur Stefansson (1879–1962). Stefansson’s story is based on his experiences during the Canadian Arctic Expedition, which traversed and mapped stretches of ocean and land in the Canadian Arctic in the years 1913–1918. The methodological and theoretical approach of the study is largely based on Mikhail Bakthin’s concept of the chronotope, which is combined with relevant concepts and analytical approaches from narrative theory and method. In order to understand Stefansson’s narrative self-representation in The Friendly Arctic, the study contends, two interdependent—and potentially conflicting—chronotopes that give form to his narrative must be examined: a friendly Arctic chronotope and a quest chronotope, which combine elements of plot and character, story and discourse. Against this background, the self-representation of Stefansson as Arctic explorer (basing his characteristic explorative techniques on Inuit knowledge) may sometimes be seen as ambivalent, and there is a similar tension in the narrative representation of his friendly Arctic. The study is of relevance to the field of travel and exploration literature, and is influenced by recent work on Arctic discourses.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.030 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".