Ryall Anka, Johan Schimanski, and Henning Howlid Wærp, eds. Arctic Discourses.
Bibliographic record
Abstract
This rich and diverse collection of literary essays related to post-Romantic Arctic Discourses and counter-discourses was generated by an international collaborative network built up around the multi-faceted "Arctic Discourses" project at the University of Tromsø (2006Tromsø ( -2009)).Edited by the three project leaders-Anka Ryall (English), Johan Schimanski (Comparative Literature) and Henning Howlid Wærp (Scandinavian Literature)-this volume demonstrates the multiplicity of representations and images of the Arctic found in and formed by texts written from around 1840 to the present from a variety of cultures, time periods and genres.In addition, numerous theoretical frameworks are used to examine these images.This diversity, as the editors point out, makes Arctic Discourses fairly unique, as most previous studies have focused on individual cultures or nations and have privileged Anglo-American literatures, discourses and perspectives.The multifarious nature of this collection is also evident when reading over the list of contributors who range from well-established scholars such as Sherrill Grace to those newer to academia.While nearly half of the contributors are connected to the University of Tromsø, the others work at universities in Canada, Britain, Germany, Sweden and Denmark.Arctic Discourses contains fifteen chapters which are thoughtfully ordered into two parts-"Discovering the Arctic" and "Imagining and Reimagining the Arctic"-preceded by the editors' introduction.This clearly written introduction provides valuable context by discussing the term Arctic Discourses-defined here as "accounts of the Arctic and appeals to Arctic images… within which we form our expectations of the Arctic" (Ryall, Schimanski, and Wærp x)-the distinctions and relationships between dominant discourses and counter-discourses, the notion of "answering back from the Arctic" and the ways in which dominant Western discourses may gradually change.The broad range of perspectives in the various chapters are outlined, as well as the thread which connects them, namely "an interest in studying the formation of the images and representations of the Arctic that have persisted over time and have received new functions in the interplay of different discursive contexts" (Ryall, Schimanski, and Wærp, xiii).Brief comments about several useful theoretical frameworks, and remarks on each of the fifteen chapters round out the introduction.The seven chapters in "Discovering the Arctic" focus primarily on Arctic exploration accounts.In the first chapter, Hanna Eglinger draws upon a variety of personal exploration narratives from multiple expeditions in her discussion of paradoxical metaphors and parabolic narratives, and this is followed by an article by Johan Schimanski and Ulrike Spring which focuses on numerous
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.011 |
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".