Arctic Drama to Sámi Theatre – Cultural Clashes Towards Decolonisation: In Shared Dialogic Spaces
Bibliographic record
Abstract
Summary This article deals with the concept of Arctic Drama, which is about how there is a relationship between drama and cultural clashes in the perspective of shared cultures in the northern Scandinavian area, which is defined as arctic in the geographical sense. In this vast area the Sámi people historically and to the present day have been living from reindeer herding in a nomadic lifestyle, giving them a close relationship to nature. Norwegians and Swedes colonised this area historically, especially the coast for fishing.There have been strong cultural clashes since the Viking ages, but colonisation mainly started later by introducing Christianity by force in the 16 th century. Since the Romantic age, these ethno-cultural clashes have been reflected in drama and theatre, and some plays by Henrik Ibsen and Knut Hamsun echo these tensions. An independent theatre of the Sámi people as well as of other indigenous people in Greenland and Canada, like the Inuits, would also develop some theatrical strategies based in a dramaturgy that could be described as a “spiral dramaturgy”. Cultural independence has contributed to a decolonisation process, contributing to even out the cultural clashes in theatre and drama, which could be defined as postcolonial towards decolonisation. This article focuses on the area of arctic Scandinavia.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.030 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".