“It Seemed Like Forever!” Shrinking Spaces of Conviviality at the Border of Norway and Russia
Bibliographic record
Abstract
Conviviality" is a useful term for exploring interactions and relationships taking place between different groups of people.While conviviality may arise through everyday processes, rhythms, and senses of belonging, it may also be made possible or limited by social structures, power relations and politics when taking place across borders."Conviviality" as a theoretical perspective has mainly previously dealt with places within a border, and to a lesser extent has been linked to borders and boundary areas, and especially then in circumpolar areas.We use the concept of "border conviviality," focusing on the intersection of changing geo-political contexts and changing personal contexts, to develop a theoretical look at "people-to-people" cooperation-and cohabitation through "conviviality" and how these were created, changed, and challenged in Kirkenes, a small town on the border of Norway and Russia, in the months following the Russian fullscale invasion of Ukraine in February 2022.We find that such a concept may provide a broader understanding of the dynamic nature of space and place associated with cooperation and "unification."Additionally, we contend that the way in which "conviviality" is meaningfully linked to "borders" is shaped by how people live, work, and collaborate.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| 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".